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nix log /nix/store/h6x4vpnzlrljrxx0w2ws9zl5f31mgj4s-python3.10-cvxpy-1.3.0.drv
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| Sourcing python-remove-tests-dir-hook | |
| Sourcing python-catch-conflicts-hook.sh | |
| Sourcing python-remove-bin-bytecode-hook.sh | |
| Sourcing pip-build-hook | |
| Using pipBuildPhase | |
| Using pipShellHook | |
| Sourcing pip-install-hook | |
| Using pipInstallPhase | |
| Sourcing python-imports-check-hook.sh | |
| Using pythonImportsCheckPhase | |
| Sourcing python-namespaces-hook | |
| Sourcing python-catch-conflicts-hook.sh | |
| Sourcing pytest-check-hook | |
| Using pytestCheckPhase | |
| @nix { "action": "setPhase", "phase": "unpackPhase" } | |
| unpacking sources | |
| unpacking source archive /nix/store/1zpr5m7ilj71z69phdm9zji9b8x31gpx-cvxpy-1.3.0.tar.gz | |
| source root is cvxpy-1.3.0 | |
| setting SOURCE_DATE_EPOCH to timestamp 1672777016 of file cvxpy-1.3.0/setup.cfg | |
| @nix { "action": "setPhase", "phase": "patchPhase" } | |
| patching sources | |
| @nix { "action": "setPhase", "phase": "configurePhase" } | |
| configuring | |
| no configure script, doing nothing | |
| @nix { "action": "setPhase", "phase": "buildPhase" } | |
| building | |
| Executing pipBuildPhase | |
| Creating a wheel... | |
| [33mWARNING: The directory '/homeless-shelter/.cache/pip' or its parent directory is not owned or is not writable by the current user. The cache has been disabled. Check the permissions and owner of that directory. If executing pip with sudo, you should use sudo's -H flag.[0m[33m | |
| [0mProcessing /build/cvxpy-1.3.0 | |
| Running command Preparing metadata (pyproject.toml) | |
| running dist_info | |
| creating /build/pip-modern-metadata-dc3k321o/cvxpy.egg-info | |
| writing /build/pip-modern-metadata-dc3k321o/cvxpy.egg-info/PKG-INFO | |
| writing dependency_links to /build/pip-modern-metadata-dc3k321o/cvxpy.egg-info/dependency_links.txt | |
| writing requirements to /build/pip-modern-metadata-dc3k321o/cvxpy.egg-info/requires.txt | |
| writing top-level names to /build/pip-modern-metadata-dc3k321o/cvxpy.egg-info/top_level.txt | |
| writing manifest file '/build/pip-modern-metadata-dc3k321o/cvxpy.egg-info/SOURCES.txt' | |
| reading manifest file '/build/pip-modern-metadata-dc3k321o/cvxpy.egg-info/SOURCES.txt' | |
| reading manifest template 'MANIFEST.in' | |
| adding license file 'LICENSE' | |
| writing manifest file '/build/pip-modern-metadata-dc3k321o/cvxpy.egg-info/SOURCES.txt' | |
| creating '/build/pip-modern-metadata-dc3k321o/cvxpy-1.3.0.dist-info' | |
| Preparing metadata (pyproject.toml) ... [?25l[?25hdone | |
| Building wheels for collected packages: cvxpy | |
| Running command Building wheel for cvxpy (pyproject.toml) | |
| running bdist_wheel | |
| running build | |
| running build_py | |
| creating build | |
| creating build/lib.linux-x86_64-cpython-310 | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy | |
| copying cvxpy/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy | |
| copying cvxpy/error.py -> build/lib.linux-x86_64-cpython-310/cvxpy | |
| copying cvxpy/settings.py -> build/lib.linux-x86_64-cpython-310/cvxpy | |
| copying cvxpy/version.py -> build/lib.linux-x86_64-cpython-310/cvxpy | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/utilities | |
| copying cvxpy/utilities/scopes.py -> build/lib.linux-x86_64-cpython-310/cvxpy/utilities | |
| copying cvxpy/utilities/linalg.py -> build/lib.linux-x86_64-cpython-310/cvxpy/utilities | |
| copying cvxpy/utilities/canonical.py -> build/lib.linux-x86_64-cpython-310/cvxpy/utilities | |
| copying cvxpy/utilities/debug_tools.py -> build/lib.linux-x86_64-cpython-310/cvxpy/utilities | |
| copying cvxpy/utilities/deterministic.py -> build/lib.linux-x86_64-cpython-310/cvxpy/utilities | |
| copying cvxpy/utilities/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/utilities | |
| copying cvxpy/utilities/perspective_utils.py -> build/lib.linux-x86_64-cpython-310/cvxpy/utilities | |
| copying cvxpy/utilities/grad.py -> build/lib.linux-x86_64-cpython-310/cvxpy/utilities | |
| copying cvxpy/utilities/coeff_extractor.py -> build/lib.linux-x86_64-cpython-310/cvxpy/utilities | |
| copying cvxpy/utilities/cvxpy_upgrade.py -> build/lib.linux-x86_64-cpython-310/cvxpy/utilities | |
| copying cvxpy/utilities/power_tools.py -> build/lib.linux-x86_64-cpython-310/cvxpy/utilities | |
| copying cvxpy/utilities/sign.py -> build/lib.linux-x86_64-cpython-310/cvxpy/utilities | |
| copying cvxpy/utilities/key_utils.py -> build/lib.linux-x86_64-cpython-310/cvxpy/utilities | |
| copying cvxpy/utilities/versioning.py -> build/lib.linux-x86_64-cpython-310/cvxpy/utilities | |
| copying cvxpy/utilities/replace_quad_forms.py -> build/lib.linux-x86_64-cpython-310/cvxpy/utilities | |
| copying cvxpy/utilities/shape.py -> build/lib.linux-x86_64-cpython-310/cvxpy/utilities | |
| copying cvxpy/utilities/performance_utils.py -> build/lib.linux-x86_64-cpython-310/cvxpy/utilities | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/interface | |
| copying cvxpy/interface/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/interface | |
| copying cvxpy/interface/matrix_utilities.py -> build/lib.linux-x86_64-cpython-310/cvxpy/interface | |
| copying cvxpy/interface/scipy_wrapper.py -> build/lib.linux-x86_64-cpython-310/cvxpy/interface | |
| copying cvxpy/interface/base_matrix_interface.py -> build/lib.linux-x86_64-cpython-310/cvxpy/interface | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/reductions | |
| copying cvxpy/reductions/cvx_attr2constr.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions | |
| copying cvxpy/reductions/chain.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions | |
| copying cvxpy/reductions/flip_objective.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions | |
| copying cvxpy/reductions/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions | |
| copying cvxpy/reductions/solution.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions | |
| copying cvxpy/reductions/reduction.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions | |
| copying cvxpy/reductions/utilities.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions | |
| copying cvxpy/reductions/canonicalization.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions | |
| copying cvxpy/reductions/matrix_stuffing.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions | |
| copying cvxpy/reductions/inverse_data.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions | |
| copying cvxpy/reductions/eval_params.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/problems | |
| copying cvxpy/problems/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/problems | |
| copying cvxpy/problems/objective.py -> build/lib.linux-x86_64-cpython-310/cvxpy/problems | |
| copying cvxpy/problems/param_prob.py -> build/lib.linux-x86_64-cpython-310/cvxpy/problems | |
| copying cvxpy/problems/xpress_problem.py -> build/lib.linux-x86_64-cpython-310/cvxpy/problems | |
| copying cvxpy/problems/iterative.py -> build/lib.linux-x86_64-cpython-310/cvxpy/problems | |
| copying cvxpy/problems/problem.py -> build/lib.linux-x86_64-cpython-310/cvxpy/problems | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/transforms | |
| copying cvxpy/transforms/indicator.py -> build/lib.linux-x86_64-cpython-310/cvxpy/transforms | |
| copying cvxpy/transforms/linearize.py -> build/lib.linux-x86_64-cpython-310/cvxpy/transforms | |
| copying cvxpy/transforms/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/transforms | |
| copying cvxpy/transforms/scalarize.py -> build/lib.linux-x86_64-cpython-310/cvxpy/transforms | |
| copying cvxpy/transforms/partial_optimize.py -> build/lib.linux-x86_64-cpython-310/cvxpy/transforms | |
| copying cvxpy/transforms/suppfunc.py -> build/lib.linux-x86_64-cpython-310/cvxpy/transforms | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/cvxcore | |
| copying cvxpy/cvxcore/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/cvxcore | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_power_tools.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_dqcp.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_qp_solvers.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_conic_solvers.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_sign.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_grad.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_dgp.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_curvature.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_quadratic.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_constraints.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_numpy.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_derivative.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_dgp2dcp.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_semidefinite_vars.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_examples.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_von_neumann_entr.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_domain.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_cone2cone.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_constant_atoms.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_atoms.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_problem.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_objectives.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_suppfunc.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_quad_form.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/ram_limited.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_param_cone_prog.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_convolution.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_versioning.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_lin_ops.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_complex.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_expressions.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/solver_test_helpers.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_linear_cone.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_dpp.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_benchmarks.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_nonlinear_atoms.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_monotonicity.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_matrices.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_valinvec2mixedint.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/base_test.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_custom_solver.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_mip_vars.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_shape.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_interfaces.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_python_backends.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_param_quad_prog.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_gurobi_write.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_kron_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| copying cvxpy/tests/test_perspective.py -> build/lib.linux-x86_64-cpython-310/cvxpy/tests | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/lin_ops | |
| copying cvxpy/lin_ops/canon_backend.py -> build/lib.linux-x86_64-cpython-310/cvxpy/lin_ops | |
| copying cvxpy/lin_ops/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/lin_ops | |
| copying cvxpy/lin_ops/lin_constraints.py -> build/lib.linux-x86_64-cpython-310/cvxpy/lin_ops | |
| copying cvxpy/lin_ops/lin_op.py -> build/lib.linux-x86_64-cpython-310/cvxpy/lin_ops | |
| copying cvxpy/lin_ops/lin_utils.py -> build/lib.linux-x86_64-cpython-310/cvxpy/lin_ops | |
| copying cvxpy/lin_ops/tree_mat.py -> build/lib.linux-x86_64-cpython-310/cvxpy/lin_ops | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/expressions | |
| copying cvxpy/expressions/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/expressions | |
| copying cvxpy/expressions/leaf.py -> build/lib.linux-x86_64-cpython-310/cvxpy/expressions | |
| copying cvxpy/expressions/cvxtypes.py -> build/lib.linux-x86_64-cpython-310/cvxpy/expressions | |
| copying cvxpy/expressions/variable.py -> build/lib.linux-x86_64-cpython-310/cvxpy/expressions | |
| copying cvxpy/expressions/expression.py -> build/lib.linux-x86_64-cpython-310/cvxpy/expressions | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/constraints | |
| copying cvxpy/constraints/zero.py -> build/lib.linux-x86_64-cpython-310/cvxpy/constraints | |
| copying cvxpy/constraints/second_order.py -> build/lib.linux-x86_64-cpython-310/cvxpy/constraints | |
| copying cvxpy/constraints/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/constraints | |
| copying cvxpy/constraints/psd.py -> build/lib.linux-x86_64-cpython-310/cvxpy/constraints | |
| copying cvxpy/constraints/exponential.py -> build/lib.linux-x86_64-cpython-310/cvxpy/constraints | |
| copying cvxpy/constraints/utilities.py -> build/lib.linux-x86_64-cpython-310/cvxpy/constraints | |
| copying cvxpy/constraints/nonpos.py -> build/lib.linux-x86_64-cpython-310/cvxpy/constraints | |
| copying cvxpy/constraints/constraint.py -> build/lib.linux-x86_64-cpython-310/cvxpy/constraints | |
| copying cvxpy/constraints/finite_set.py -> build/lib.linux-x86_64-cpython-310/cvxpy/constraints | |
| copying cvxpy/constraints/power.py -> build/lib.linux-x86_64-cpython-310/cvxpy/constraints | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/quad_over_lin.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/sigma_max.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/condition_number.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/lambda_max.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/norm.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/von_neumann_entr.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/pnorm.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/norm_inf.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/gmatmul.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/matrix_frac.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/lambda_sum_smallest.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/dist_ratio.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/cummax.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/norm_nuc.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/axis_atom.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/eye_minus_inv.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/sum_smallest.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/tr_inv.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/pf_eigenvalue.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/max.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/suppfunc.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/geo_mean.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/inv_prod.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/one_minus_pos.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/mixed_norm.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/dotsort.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/perspective.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/lambda_sum_largest.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/min.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/quad_form.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/length.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/gen_lambda_max.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/log_sum_exp.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/sum_squares.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/atom.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/harmonic_mean.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/sign.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/sum_largest.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/total_variation.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/norm1.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/lambda_min.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/log_det.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| copying cvxpy/atoms/prod.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/interface/numpy_interface | |
| copying cvxpy/interface/numpy_interface/ndarray_interface.py -> build/lib.linux-x86_64-cpython-310/cvxpy/interface/numpy_interface | |
| copying cvxpy/interface/numpy_interface/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/interface/numpy_interface | |
| copying cvxpy/interface/numpy_interface/sparse_matrix_interface.py -> build/lib.linux-x86_64-cpython-310/cvxpy/interface/numpy_interface | |
| copying cvxpy/interface/numpy_interface/matrix_interface.py -> build/lib.linux-x86_64-cpython-310/cvxpy/interface/numpy_interface | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dqcp2dcp | |
| copying cvxpy/reductions/dqcp2dcp/tighten.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dqcp2dcp | |
| copying cvxpy/reductions/dqcp2dcp/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dqcp2dcp | |
| copying cvxpy/reductions/dqcp2dcp/sets.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dqcp2dcp | |
| copying cvxpy/reductions/dqcp2dcp/dqcp2dcp.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dqcp2dcp | |
| copying cvxpy/reductions/dqcp2dcp/inverse.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dqcp2dcp | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone | |
| copying cvxpy/reductions/dcp2cone/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone | |
| copying cvxpy/reductions/dcp2cone/dcp2cone.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone | |
| copying cvxpy/reductions/dcp2cone/cone_matrix_stuffing.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers | |
| copying cvxpy/reductions/solvers/constant_solver.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers | |
| copying cvxpy/reductions/solvers/compr_matrix.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers | |
| copying cvxpy/reductions/solvers/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers | |
| copying cvxpy/reductions/solvers/bisection.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers | |
| copying cvxpy/reductions/solvers/solver.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers | |
| copying cvxpy/reductions/solvers/defines.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers | |
| copying cvxpy/reductions/solvers/solving_chain.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers | |
| copying cvxpy/reductions/solvers/utilities.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers | |
| copying cvxpy/reductions/solvers/intermediate_chain.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers | |
| copying cvxpy/reductions/solvers/kktsolver.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/reductions/discrete2mixedint | |
| copying cvxpy/reductions/discrete2mixedint/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/discrete2mixedint | |
| copying cvxpy/reductions/discrete2mixedint/valinvec2mixedint.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/discrete2mixedint | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/reductions/eliminate_pwl | |
| copying cvxpy/reductions/eliminate_pwl/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/eliminate_pwl | |
| copying cvxpy/reductions/eliminate_pwl/eliminate_pwl.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/eliminate_pwl | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/reductions/complex2real | |
| copying cvxpy/reductions/complex2real/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/complex2real | |
| copying cvxpy/reductions/complex2real/complex2real.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/complex2real | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/reductions/qp2quad_form | |
| copying cvxpy/reductions/qp2quad_form/qp_matrix_stuffing.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/qp2quad_form | |
| copying cvxpy/reductions/qp2quad_form/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/qp2quad_form | |
| copying cvxpy/reductions/qp2quad_form/qp2symbolic_qp.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/qp2quad_form | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp | |
| copying cvxpy/reductions/dgp2dcp/util.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp | |
| copying cvxpy/reductions/dgp2dcp/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp | |
| copying cvxpy/reductions/dgp2dcp/dgp2dcp.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/reductions/cone2cone | |
| copying cvxpy/reductions/cone2cone/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/cone2cone | |
| copying cvxpy/reductions/cone2cone/approximations.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/cone2cone | |
| copying cvxpy/reductions/cone2cone/affine2direct.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/cone2cone | |
| copying cvxpy/reductions/cone2cone/exotic2common.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/cone2cone | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying cvxpy/reductions/dcp2cone/atom_canonicalizers/quad_form_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying cvxpy/reductions/dcp2cone/atom_canonicalizers/sigma_max_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying cvxpy/reductions/dcp2cone/atom_canonicalizers/perspective_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying cvxpy/reductions/dcp2cone/atom_canonicalizers/power_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying cvxpy/reductions/dcp2cone/atom_canonicalizers/von_neumann_entr_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying cvxpy/reductions/dcp2cone/atom_canonicalizers/quad_over_lin_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying cvxpy/reductions/dcp2cone/atom_canonicalizers/rel_entr_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying cvxpy/reductions/dcp2cone/atom_canonicalizers/pnorm_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying cvxpy/reductions/dcp2cone/atom_canonicalizers/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying cvxpy/reductions/dcp2cone/atom_canonicalizers/entr_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying cvxpy/reductions/dcp2cone/atom_canonicalizers/log_sum_exp_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying cvxpy/reductions/dcp2cone/atom_canonicalizers/log_det_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying cvxpy/reductions/dcp2cone/atom_canonicalizers/mul_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying cvxpy/reductions/dcp2cone/atom_canonicalizers/logistic_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying cvxpy/reductions/dcp2cone/atom_canonicalizers/tr_inv_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying cvxpy/reductions/dcp2cone/atom_canonicalizers/geo_mean_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying cvxpy/reductions/dcp2cone/atom_canonicalizers/xexp_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying cvxpy/reductions/dcp2cone/atom_canonicalizers/suppfunc_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying cvxpy/reductions/dcp2cone/atom_canonicalizers/indicator_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying cvxpy/reductions/dcp2cone/atom_canonicalizers/kl_div_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying cvxpy/reductions/dcp2cone/atom_canonicalizers/huber_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying cvxpy/reductions/dcp2cone/atom_canonicalizers/exp_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying cvxpy/reductions/dcp2cone/atom_canonicalizers/log_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying cvxpy/reductions/dcp2cone/atom_canonicalizers/lambda_sum_largest_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying cvxpy/reductions/dcp2cone/atom_canonicalizers/log1p_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying cvxpy/reductions/dcp2cone/atom_canonicalizers/normNuc_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying cvxpy/reductions/dcp2cone/atom_canonicalizers/lambda_max_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying cvxpy/reductions/dcp2cone/atom_canonicalizers/matrix_frac_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers | |
| copying cvxpy/reductions/solvers/conic_solvers/cbc_conif.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers | |
| copying cvxpy/reductions/solvers/conic_solvers/glop_conif.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers | |
| copying cvxpy/reductions/solvers/conic_solvers/copt_conif.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers | |
| copying cvxpy/reductions/solvers/conic_solvers/glpk_mi_conif.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers | |
| copying cvxpy/reductions/solvers/conic_solvers/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers | |
| copying cvxpy/reductions/solvers/conic_solvers/xpress_conif.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers | |
| copying cvxpy/reductions/solvers/conic_solvers/scs_conif.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers | |
| copying cvxpy/reductions/solvers/conic_solvers/diffcp_conif.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers | |
| copying cvxpy/reductions/solvers/conic_solvers/gurobi_conif.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers | |
| copying cvxpy/reductions/solvers/conic_solvers/conic_solver.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers | |
| copying cvxpy/reductions/solvers/conic_solvers/ecos_conif.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers | |
| copying cvxpy/reductions/solvers/conic_solvers/ecos_bb_conif.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers | |
| copying cvxpy/reductions/solvers/conic_solvers/cvxopt_conif.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers | |
| copying cvxpy/reductions/solvers/conic_solvers/scip_conif.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers | |
| copying cvxpy/reductions/solvers/conic_solvers/scipy_conif.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers | |
| copying cvxpy/reductions/solvers/conic_solvers/clarabel_conif.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers | |
| copying cvxpy/reductions/solvers/conic_solvers/mosek_conif.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers | |
| copying cvxpy/reductions/solvers/conic_solvers/sdpa_conif.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers | |
| copying cvxpy/reductions/solvers/conic_solvers/pdlp_conif.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers | |
| copying cvxpy/reductions/solvers/conic_solvers/nag_conif.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers | |
| copying cvxpy/reductions/solvers/conic_solvers/cplex_conif.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers | |
| copying cvxpy/reductions/solvers/conic_solvers/glpk_conif.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/lp_solvers | |
| copying cvxpy/reductions/solvers/lp_solvers/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/lp_solvers | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/qp_solvers | |
| copying cvxpy/reductions/solvers/qp_solvers/gurobi_qpif.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/qp_solvers | |
| copying cvxpy/reductions/solvers/qp_solvers/osqp_qpif.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/qp_solvers | |
| copying cvxpy/reductions/solvers/qp_solvers/qp_solver.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/qp_solvers | |
| copying cvxpy/reductions/solvers/qp_solvers/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/qp_solvers | |
| copying cvxpy/reductions/solvers/qp_solvers/xpress_qpif.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/qp_solvers | |
| copying cvxpy/reductions/solvers/qp_solvers/copt_qpif.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/qp_solvers | |
| copying cvxpy/reductions/solvers/qp_solvers/proxqp_qpif.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/qp_solvers | |
| copying cvxpy/reductions/solvers/qp_solvers/cplex_qpif.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/qp_solvers | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/reductions/eliminate_pwl/atom_canonicalizers | |
| copying cvxpy/reductions/eliminate_pwl/atom_canonicalizers/min_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/eliminate_pwl/atom_canonicalizers | |
| copying cvxpy/reductions/eliminate_pwl/atom_canonicalizers/cumsum_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/eliminate_pwl/atom_canonicalizers | |
| copying cvxpy/reductions/eliminate_pwl/atom_canonicalizers/cummax_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/eliminate_pwl/atom_canonicalizers | |
| copying cvxpy/reductions/eliminate_pwl/atom_canonicalizers/max_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/eliminate_pwl/atom_canonicalizers | |
| copying cvxpy/reductions/eliminate_pwl/atom_canonicalizers/minimum_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/eliminate_pwl/atom_canonicalizers | |
| copying cvxpy/reductions/eliminate_pwl/atom_canonicalizers/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/eliminate_pwl/atom_canonicalizers | |
| copying cvxpy/reductions/eliminate_pwl/atom_canonicalizers/dotsort_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/eliminate_pwl/atom_canonicalizers | |
| copying cvxpy/reductions/eliminate_pwl/atom_canonicalizers/norm1_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/eliminate_pwl/atom_canonicalizers | |
| copying cvxpy/reductions/eliminate_pwl/atom_canonicalizers/norm_inf_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/eliminate_pwl/atom_canonicalizers | |
| copying cvxpy/reductions/eliminate_pwl/atom_canonicalizers/sum_largest_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/eliminate_pwl/atom_canonicalizers | |
| copying cvxpy/reductions/eliminate_pwl/atom_canonicalizers/maximum_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/eliminate_pwl/atom_canonicalizers | |
| copying cvxpy/reductions/eliminate_pwl/atom_canonicalizers/abs_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/eliminate_pwl/atom_canonicalizers | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/reductions/complex2real/canonicalizers | |
| copying cvxpy/reductions/complex2real/canonicalizers/matrix_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/complex2real/canonicalizers | |
| copying cvxpy/reductions/complex2real/canonicalizers/pnorm_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/complex2real/canonicalizers | |
| copying cvxpy/reductions/complex2real/canonicalizers/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/complex2real/canonicalizers | |
| copying cvxpy/reductions/complex2real/canonicalizers/inequality_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/complex2real/canonicalizers | |
| copying cvxpy/reductions/complex2real/canonicalizers/param_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/complex2real/canonicalizers | |
| copying cvxpy/reductions/complex2real/canonicalizers/equality_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/complex2real/canonicalizers | |
| copying cvxpy/reductions/complex2real/canonicalizers/variable_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/complex2real/canonicalizers | |
| copying cvxpy/reductions/complex2real/canonicalizers/psd_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/complex2real/canonicalizers | |
| copying cvxpy/reductions/complex2real/canonicalizers/constant_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/complex2real/canonicalizers | |
| copying cvxpy/reductions/complex2real/canonicalizers/aff_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/complex2real/canonicalizers | |
| copying cvxpy/reductions/complex2real/canonicalizers/abs_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/complex2real/canonicalizers | |
| copying cvxpy/reductions/complex2real/canonicalizers/soc_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/complex2real/canonicalizers | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/reductions/qp2quad_form/atom_canonicalizers | |
| copying cvxpy/reductions/qp2quad_form/atom_canonicalizers/quad_form_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/qp2quad_form/atom_canonicalizers | |
| copying cvxpy/reductions/qp2quad_form/atom_canonicalizers/power_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/qp2quad_form/atom_canonicalizers | |
| copying cvxpy/reductions/qp2quad_form/atom_canonicalizers/quad_over_lin_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/qp2quad_form/atom_canonicalizers | |
| copying cvxpy/reductions/qp2quad_form/atom_canonicalizers/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/qp2quad_form/atom_canonicalizers | |
| copying cvxpy/reductions/qp2quad_form/atom_canonicalizers/huber_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/qp2quad_form/atom_canonicalizers | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying cvxpy/reductions/dgp2dcp/atom_canonicalizers/pf_eigenvalue_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying cvxpy/reductions/dgp2dcp/atom_canonicalizers/quad_form_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying cvxpy/reductions/dgp2dcp/atom_canonicalizers/mulexpression_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying cvxpy/reductions/dgp2dcp/atom_canonicalizers/power_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying cvxpy/reductions/dgp2dcp/atom_canonicalizers/prod_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying cvxpy/reductions/dgp2dcp/atom_canonicalizers/quad_over_lin_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying cvxpy/reductions/dgp2dcp/atom_canonicalizers/pnorm_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying cvxpy/reductions/dgp2dcp/atom_canonicalizers/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying cvxpy/reductions/dgp2dcp/atom_canonicalizers/norm1_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying cvxpy/reductions/dgp2dcp/atom_canonicalizers/add_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying cvxpy/reductions/dgp2dcp/atom_canonicalizers/nonpos_constr_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying cvxpy/reductions/dgp2dcp/atom_canonicalizers/mul_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying cvxpy/reductions/dgp2dcp/atom_canonicalizers/parameter_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying cvxpy/reductions/dgp2dcp/atom_canonicalizers/geo_mean_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying cvxpy/reductions/dgp2dcp/atom_canonicalizers/xexp_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying cvxpy/reductions/dgp2dcp/atom_canonicalizers/constant_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying cvxpy/reductions/dgp2dcp/atom_canonicalizers/gmatmul_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying cvxpy/reductions/dgp2dcp/atom_canonicalizers/trace_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying cvxpy/reductions/dgp2dcp/atom_canonicalizers/div_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying cvxpy/reductions/dgp2dcp/atom_canonicalizers/eye_minus_inv_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying cvxpy/reductions/dgp2dcp/atom_canonicalizers/norm_inf_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying cvxpy/reductions/dgp2dcp/atom_canonicalizers/one_minus_pos_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying cvxpy/reductions/dgp2dcp/atom_canonicalizers/exp_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying cvxpy/reductions/dgp2dcp/atom_canonicalizers/sum_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying cvxpy/reductions/dgp2dcp/atom_canonicalizers/log_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying cvxpy/reductions/dgp2dcp/atom_canonicalizers/zero_constr_canon.py -> build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/cvxcore/python | |
| copying cvxpy/cvxcore/python/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/cvxcore/python | |
| copying cvxpy/cvxcore/python/cvxcore.py -> build/lib.linux-x86_64-cpython-310/cvxpy/cvxcore/python | |
| copying cvxpy/cvxcore/python/canonInterface.py -> build/lib.linux-x86_64-cpython-310/cvxpy/cvxcore/python | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/expressions/constants | |
| copying cvxpy/expressions/constants/parameter.py -> build/lib.linux-x86_64-cpython-310/cvxpy/expressions/constants | |
| copying cvxpy/expressions/constants/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/expressions/constants | |
| copying cvxpy/expressions/constants/constant.py -> build/lib.linux-x86_64-cpython-310/cvxpy/expressions/constants | |
| copying cvxpy/expressions/constants/callback_param.py -> build/lib.linux-x86_64-cpython-310/cvxpy/expressions/constants | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine | |
| copying cvxpy/atoms/affine/partial_trace.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine | |
| copying cvxpy/atoms/affine/hstack.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine | |
| copying cvxpy/atoms/affine/sum.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine | |
| copying cvxpy/atoms/affine/vstack.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine | |
| copying cvxpy/atoms/affine/bmat.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine | |
| copying cvxpy/atoms/affine/conv.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine | |
| copying cvxpy/atoms/affine/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine | |
| copying cvxpy/atoms/affine/affine_atom.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine | |
| copying cvxpy/atoms/affine/trace.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine | |
| copying cvxpy/atoms/affine/index.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine | |
| copying cvxpy/atoms/affine/unary_operators.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine | |
| copying cvxpy/atoms/affine/imag.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine | |
| copying cvxpy/atoms/affine/diff.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine | |
| copying cvxpy/atoms/affine/conj.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine | |
| copying cvxpy/atoms/affine/transpose.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine | |
| copying cvxpy/atoms/affine/add_expr.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine | |
| copying cvxpy/atoms/affine/cumsum.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine | |
| copying cvxpy/atoms/affine/upper_tri.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine | |
| copying cvxpy/atoms/affine/binary_operators.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine | |
| copying cvxpy/atoms/affine/reshape.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine | |
| copying cvxpy/atoms/affine/vec.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine | |
| copying cvxpy/atoms/affine/diag.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine | |
| copying cvxpy/atoms/affine/partial_transpose.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine | |
| copying cvxpy/atoms/affine/wraps.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine | |
| copying cvxpy/atoms/affine/kron.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine | |
| copying cvxpy/atoms/affine/real.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine | |
| copying cvxpy/atoms/affine/promote.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine | |
| creating build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise | |
| copying cvxpy/atoms/elementwise/huber.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise | |
| copying cvxpy/atoms/elementwise/log.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise | |
| copying cvxpy/atoms/elementwise/inv_pos.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise | |
| copying cvxpy/atoms/elementwise/loggamma.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise | |
| copying cvxpy/atoms/elementwise/log1p.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise | |
| copying cvxpy/atoms/elementwise/__init__.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise | |
| copying cvxpy/atoms/elementwise/ceil.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise | |
| copying cvxpy/atoms/elementwise/minimum.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise | |
| copying cvxpy/atoms/elementwise/maximum.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise | |
| copying cvxpy/atoms/elementwise/scalene.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise | |
| copying cvxpy/atoms/elementwise/neg.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise | |
| copying cvxpy/atoms/elementwise/power.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise | |
| copying cvxpy/atoms/elementwise/xexp.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise | |
| copying cvxpy/atoms/elementwise/entr.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise | |
| copying cvxpy/atoms/elementwise/log_normcdf.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise | |
| copying cvxpy/atoms/elementwise/rel_entr.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise | |
| copying cvxpy/atoms/elementwise/square.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise | |
| copying cvxpy/atoms/elementwise/exp.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise | |
| copying cvxpy/atoms/elementwise/kl_div.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise | |
| copying cvxpy/atoms/elementwise/pos.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise | |
| copying cvxpy/atoms/elementwise/elementwise.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise | |
| copying cvxpy/atoms/elementwise/abs.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise | |
| copying cvxpy/atoms/elementwise/logistic.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise | |
| copying cvxpy/atoms/elementwise/sqrt.py -> build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise | |
| copying cvxpy/py.typed -> build/lib.linux-x86_64-cpython-310/cvxpy | |
| running build_ext | |
| building '_cvxcore' extension | |
| creating build/temp.linux-x86_64-cpython-310 | |
| creating build/temp.linux-x86_64-cpython-310/cvxpy | |
| creating build/temp.linux-x86_64-cpython-310/cvxpy/cvxcore | |
| creating build/temp.linux-x86_64-cpython-310/cvxpy/cvxcore/python | |
| creating build/temp.linux-x86_64-cpython-310/cvxpy/cvxcore/src | |
| g++ -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -I/nix/store/q88zzcq9dwfy4kq644p584a1z9vam6mv-libxcrypt-4.4.33/include -fPIC -Icvxpy/cvxcore/src/ -Icvxpy/cvxcore/python/ -Icvxpy/cvxcore/include/ -I/nix/store/0n4y44dnaxafqs7cg625aldrb152x7bx-python3-3.10.10/include/python3.10 -I/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/core/include -c cvxpy/cvxcore/python/cvxcore_wrap.cxx -o build/temp.linux-x86_64-cpython-310/cvxpy/cvxcore/python/cvxcore_wrap.o -O3 -std=c++11 -Wall -pedantic -Wextra -Wno-unused-parameter | |
| In file included from /nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/core/include/numpy/ndarraytypes.h:1940, | |
| from /nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/core/include/numpy/ndarrayobject.h:12, | |
| from /nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/core/include/numpy/arrayobject.h:5, | |
| from cvxpy/cvxcore/python/cvxcore_wrap.cxx:2846: | |
| /nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning is a GCC extension | |
| 17 | #warning "Using deprecated NumPy API, disable it with " \ | |
| | ^~~~~~~ | |
| /nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp] | |
| g++ -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -I/nix/store/q88zzcq9dwfy4kq644p584a1z9vam6mv-libxcrypt-4.4.33/include -fPIC -Icvxpy/cvxcore/src/ -Icvxpy/cvxcore/python/ -Icvxpy/cvxcore/include/ -I/nix/store/0n4y44dnaxafqs7cg625aldrb152x7bx-python3-3.10.10/include/python3.10 -I/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/core/include -c cvxpy/cvxcore/src/LinOpOperations.cpp -o build/temp.linux-x86_64-cpython-310/cvxpy/cvxcore/src/LinOpOperations.o -O3 -std=c++11 -Wall -pedantic -Wextra -Wno-unused-parameter | |
| g++ -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -I/nix/store/q88zzcq9dwfy4kq644p584a1z9vam6mv-libxcrypt-4.4.33/include -fPIC -Icvxpy/cvxcore/src/ -Icvxpy/cvxcore/python/ -Icvxpy/cvxcore/include/ -I/nix/store/0n4y44dnaxafqs7cg625aldrb152x7bx-python3-3.10.10/include/python3.10 -I/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/core/include -c cvxpy/cvxcore/src/Utils.cpp -o build/temp.linux-x86_64-cpython-310/cvxpy/cvxcore/src/Utils.o -O3 -std=c++11 -Wall -pedantic -Wextra -Wno-unused-parameter | |
| g++ -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -I/nix/store/q88zzcq9dwfy4kq644p584a1z9vam6mv-libxcrypt-4.4.33/include -fPIC -Icvxpy/cvxcore/src/ -Icvxpy/cvxcore/python/ -Icvxpy/cvxcore/include/ -I/nix/store/0n4y44dnaxafqs7cg625aldrb152x7bx-python3-3.10.10/include/python3.10 -I/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/core/include -c cvxpy/cvxcore/src/cvxcore.cpp -o build/temp.linux-x86_64-cpython-310/cvxpy/cvxcore/src/cvxcore.o -O3 -std=c++11 -Wall -pedantic -Wextra -Wno-unused-parameter | |
| g++ -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -I/nix/store/q88zzcq9dwfy4kq644p584a1z9vam6mv-libxcrypt-4.4.33/include -shared -lgomp build/temp.linux-x86_64-cpython-310/cvxpy/cvxcore/python/cvxcore_wrap.o build/temp.linux-x86_64-cpython-310/cvxpy/cvxcore/src/LinOpOperations.o build/temp.linux-x86_64-cpython-310/cvxpy/cvxcore/src/Utils.o build/temp.linux-x86_64-cpython-310/cvxpy/cvxcore/src/cvxcore.o -L/nix/store/0n4y44dnaxafqs7cg625aldrb152x7bx-python3-3.10.10/lib -o build/lib.linux-x86_64-cpython-310/_cvxcore.cpython-310-x86_64-linux-gnu.so -O3 | |
| installing to build/bdist.linux-x86_64/wheel | |
| running install | |
| running install_lib | |
| creating build/bdist.linux-x86_64 | |
| creating build/bdist.linux-x86_64/wheel | |
| creating build/bdist.linux-x86_64/wheel/cvxpy | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/utilities | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/utilities/scopes.py -> build/bdist.linux-x86_64/wheel/cvxpy/utilities | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/utilities/linalg.py -> build/bdist.linux-x86_64/wheel/cvxpy/utilities | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/utilities/canonical.py -> build/bdist.linux-x86_64/wheel/cvxpy/utilities | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/utilities/debug_tools.py -> build/bdist.linux-x86_64/wheel/cvxpy/utilities | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/utilities/deterministic.py -> build/bdist.linux-x86_64/wheel/cvxpy/utilities | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/utilities/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/utilities | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/utilities/perspective_utils.py -> build/bdist.linux-x86_64/wheel/cvxpy/utilities | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/utilities/grad.py -> build/bdist.linux-x86_64/wheel/cvxpy/utilities | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/utilities/coeff_extractor.py -> build/bdist.linux-x86_64/wheel/cvxpy/utilities | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/utilities/cvxpy_upgrade.py -> build/bdist.linux-x86_64/wheel/cvxpy/utilities | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/utilities/power_tools.py -> build/bdist.linux-x86_64/wheel/cvxpy/utilities | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/utilities/sign.py -> build/bdist.linux-x86_64/wheel/cvxpy/utilities | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/utilities/key_utils.py -> build/bdist.linux-x86_64/wheel/cvxpy/utilities | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/utilities/versioning.py -> build/bdist.linux-x86_64/wheel/cvxpy/utilities | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/utilities/replace_quad_forms.py -> build/bdist.linux-x86_64/wheel/cvxpy/utilities | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/utilities/shape.py -> build/bdist.linux-x86_64/wheel/cvxpy/utilities | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/utilities/performance_utils.py -> build/bdist.linux-x86_64/wheel/cvxpy/utilities | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/interface | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/interface/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/interface | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/interface/matrix_utilities.py -> build/bdist.linux-x86_64/wheel/cvxpy/interface | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/interface/numpy_interface | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/interface/numpy_interface/ndarray_interface.py -> build/bdist.linux-x86_64/wheel/cvxpy/interface/numpy_interface | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/interface/numpy_interface/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/interface/numpy_interface | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/interface/numpy_interface/sparse_matrix_interface.py -> build/bdist.linux-x86_64/wheel/cvxpy/interface/numpy_interface | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/interface/numpy_interface/matrix_interface.py -> build/bdist.linux-x86_64/wheel/cvxpy/interface/numpy_interface | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/interface/scipy_wrapper.py -> build/bdist.linux-x86_64/wheel/cvxpy/interface | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/interface/base_matrix_interface.py -> build/bdist.linux-x86_64/wheel/cvxpy/interface | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/reductions | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/cvx_attr2constr.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/reductions/dqcp2dcp | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dqcp2dcp/tighten.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dqcp2dcp | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dqcp2dcp/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dqcp2dcp | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dqcp2dcp/sets.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dqcp2dcp | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dqcp2dcp/dqcp2dcp.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dqcp2dcp | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dqcp2dcp/inverse.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dqcp2dcp | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/chain.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/flip_objective.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solution.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/reduction.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/dcp2cone.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers/quad_form_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers/sigma_max_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers/perspective_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers/power_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers/von_neumann_entr_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers/quad_over_lin_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers/rel_entr_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers/pnorm_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers/entr_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers/log_sum_exp_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers/log_det_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers/mul_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers/logistic_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers/tr_inv_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers/geo_mean_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers/xexp_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers/suppfunc_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers/indicator_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers/kl_div_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers/huber_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers/exp_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers/log_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers/lambda_sum_largest_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers/log1p_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers/normNuc_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers/lambda_max_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/atom_canonicalizers/matrix_frac_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dcp2cone/cone_matrix_stuffing.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dcp2cone | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/constant_solver.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/conic_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers/cbc_conif.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/conic_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers/glop_conif.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/conic_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers/copt_conif.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/conic_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers/glpk_mi_conif.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/conic_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/conic_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers/xpress_conif.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/conic_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers/scs_conif.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/conic_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers/diffcp_conif.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/conic_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers/gurobi_conif.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/conic_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers/conic_solver.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/conic_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers/ecos_conif.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/conic_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers/ecos_bb_conif.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/conic_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers/cvxopt_conif.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/conic_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers/scip_conif.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/conic_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers/scipy_conif.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/conic_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers/clarabel_conif.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/conic_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers/mosek_conif.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/conic_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers/sdpa_conif.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/conic_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers/pdlp_conif.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/conic_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers/nag_conif.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/conic_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers/cplex_conif.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/conic_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/conic_solvers/glpk_conif.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/conic_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/compr_matrix.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/bisection.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/solver.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/lp_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/lp_solvers/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/lp_solvers | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/qp_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/qp_solvers/gurobi_qpif.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/qp_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/qp_solvers/osqp_qpif.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/qp_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/qp_solvers/qp_solver.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/qp_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/qp_solvers/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/qp_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/qp_solvers/xpress_qpif.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/qp_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/qp_solvers/copt_qpif.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/qp_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/qp_solvers/proxqp_qpif.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/qp_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/qp_solvers/cplex_qpif.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers/qp_solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/defines.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/solving_chain.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/utilities.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/intermediate_chain.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/solvers/kktsolver.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/solvers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/utilities.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/canonicalization.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/reductions/discrete2mixedint | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/discrete2mixedint/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/discrete2mixedint | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/discrete2mixedint/valinvec2mixedint.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/discrete2mixedint | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/matrix_stuffing.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/reductions/eliminate_pwl | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/eliminate_pwl/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/eliminate_pwl | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/reductions/eliminate_pwl/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/eliminate_pwl/atom_canonicalizers/min_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/eliminate_pwl/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/eliminate_pwl/atom_canonicalizers/cumsum_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/eliminate_pwl/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/eliminate_pwl/atom_canonicalizers/cummax_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/eliminate_pwl/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/eliminate_pwl/atom_canonicalizers/max_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/eliminate_pwl/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/eliminate_pwl/atom_canonicalizers/minimum_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/eliminate_pwl/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/eliminate_pwl/atom_canonicalizers/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/eliminate_pwl/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/eliminate_pwl/atom_canonicalizers/dotsort_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/eliminate_pwl/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/eliminate_pwl/atom_canonicalizers/norm1_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/eliminate_pwl/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/eliminate_pwl/atom_canonicalizers/norm_inf_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/eliminate_pwl/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/eliminate_pwl/atom_canonicalizers/sum_largest_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/eliminate_pwl/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/eliminate_pwl/atom_canonicalizers/maximum_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/eliminate_pwl/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/eliminate_pwl/atom_canonicalizers/abs_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/eliminate_pwl/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/eliminate_pwl/eliminate_pwl.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/eliminate_pwl | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/reductions/complex2real | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/complex2real/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/complex2real | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/complex2real/complex2real.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/complex2real | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/reductions/complex2real/canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/complex2real/canonicalizers/matrix_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/complex2real/canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/complex2real/canonicalizers/pnorm_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/complex2real/canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/complex2real/canonicalizers/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/complex2real/canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/complex2real/canonicalizers/inequality_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/complex2real/canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/complex2real/canonicalizers/param_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/complex2real/canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/complex2real/canonicalizers/equality_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/complex2real/canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/complex2real/canonicalizers/variable_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/complex2real/canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/complex2real/canonicalizers/psd_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/complex2real/canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/complex2real/canonicalizers/constant_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/complex2real/canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/complex2real/canonicalizers/aff_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/complex2real/canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/complex2real/canonicalizers/abs_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/complex2real/canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/complex2real/canonicalizers/soc_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/complex2real/canonicalizers | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/reductions/qp2quad_form | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/qp2quad_form/qp_matrix_stuffing.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/qp2quad_form | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/qp2quad_form/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/qp2quad_form | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/reductions/qp2quad_form/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/qp2quad_form/atom_canonicalizers/quad_form_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/qp2quad_form/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/qp2quad_form/atom_canonicalizers/power_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/qp2quad_form/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/qp2quad_form/atom_canonicalizers/quad_over_lin_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/qp2quad_form/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/qp2quad_form/atom_canonicalizers/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/qp2quad_form/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/qp2quad_form/atom_canonicalizers/huber_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/qp2quad_form/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/qp2quad_form/qp2symbolic_qp.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/qp2quad_form | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/inverse_data.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/eval_params.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/reductions/dgp2dcp | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/util.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dgp2dcp | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dgp2dcp | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/dgp2dcp.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dgp2dcp | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers/pf_eigenvalue_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers/quad_form_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers/mulexpression_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers/power_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers/prod_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers/quad_over_lin_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers/pnorm_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers/norm1_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers/add_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers/nonpos_constr_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers/mul_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers/parameter_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers/geo_mean_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers/xexp_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers/constant_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers/gmatmul_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers/trace_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers/div_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers/eye_minus_inv_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers/norm_inf_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers/one_minus_pos_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers/exp_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers/sum_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers/log_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/dgp2dcp/atom_canonicalizers/zero_constr_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/dgp2dcp/atom_canonicalizers | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/reductions/cone2cone | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/cone2cone/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/cone2cone | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/cone2cone/approximations.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/cone2cone | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/cone2cone/affine2direct.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/cone2cone | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/reductions/cone2cone/exotic2common.py -> build/bdist.linux-x86_64/wheel/cvxpy/reductions/cone2cone | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/error.py -> build/bdist.linux-x86_64/wheel/cvxpy | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/problems | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/problems/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/problems | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/problems/objective.py -> build/bdist.linux-x86_64/wheel/cvxpy/problems | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/problems/param_prob.py -> build/bdist.linux-x86_64/wheel/cvxpy/problems | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/problems/xpress_problem.py -> build/bdist.linux-x86_64/wheel/cvxpy/problems | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/problems/iterative.py -> build/bdist.linux-x86_64/wheel/cvxpy/problems | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/problems/problem.py -> build/bdist.linux-x86_64/wheel/cvxpy/problems | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/transforms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/transforms/indicator.py -> build/bdist.linux-x86_64/wheel/cvxpy/transforms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/transforms/linearize.py -> build/bdist.linux-x86_64/wheel/cvxpy/transforms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/transforms/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/transforms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/transforms/scalarize.py -> build/bdist.linux-x86_64/wheel/cvxpy/transforms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/transforms/partial_optimize.py -> build/bdist.linux-x86_64/wheel/cvxpy/transforms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/transforms/suppfunc.py -> build/bdist.linux-x86_64/wheel/cvxpy/transforms | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/cvxcore | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/cvxcore/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/cvxcore | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/cvxcore/python | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/cvxcore/python/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/cvxcore/python | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/cvxcore/python/cvxcore.py -> build/bdist.linux-x86_64/wheel/cvxpy/cvxcore/python | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/cvxcore/python/canonInterface.py -> build/bdist.linux-x86_64/wheel/cvxpy/cvxcore/python | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_power_tools.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_dqcp.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_qp_solvers.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_conic_solvers.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_sign.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_grad.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_dgp.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_curvature.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_quadratic.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_constraints.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_numpy.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_derivative.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_dgp2dcp.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_semidefinite_vars.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_examples.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_von_neumann_entr.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_domain.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_cone2cone.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_constant_atoms.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_atoms.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_problem.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_objectives.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_suppfunc.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_quad_form.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/ram_limited.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_param_cone_prog.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_convolution.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_versioning.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_lin_ops.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_complex.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_expressions.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/solver_test_helpers.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_linear_cone.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_dpp.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_benchmarks.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_nonlinear_atoms.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_monotonicity.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_matrices.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_valinvec2mixedint.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/base_test.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_custom_solver.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_mip_vars.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_shape.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_interfaces.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_python_backends.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_param_quad_prog.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_gurobi_write.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_kron_canon.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/tests/test_perspective.py -> build/bdist.linux-x86_64/wheel/cvxpy/tests | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/lin_ops | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/lin_ops/canon_backend.py -> build/bdist.linux-x86_64/wheel/cvxpy/lin_ops | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/lin_ops/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/lin_ops | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/lin_ops/lin_constraints.py -> build/bdist.linux-x86_64/wheel/cvxpy/lin_ops | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/lin_ops/lin_op.py -> build/bdist.linux-x86_64/wheel/cvxpy/lin_ops | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/lin_ops/lin_utils.py -> build/bdist.linux-x86_64/wheel/cvxpy/lin_ops | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/lin_ops/tree_mat.py -> build/bdist.linux-x86_64/wheel/cvxpy/lin_ops | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/py.typed -> build/bdist.linux-x86_64/wheel/cvxpy | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/settings.py -> build/bdist.linux-x86_64/wheel/cvxpy | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/expressions | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/expressions/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/expressions | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/expressions/leaf.py -> build/bdist.linux-x86_64/wheel/cvxpy/expressions | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/expressions/cvxtypes.py -> build/bdist.linux-x86_64/wheel/cvxpy/expressions | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/expressions/variable.py -> build/bdist.linux-x86_64/wheel/cvxpy/expressions | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/expressions/constants | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/expressions/constants/parameter.py -> build/bdist.linux-x86_64/wheel/cvxpy/expressions/constants | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/expressions/constants/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/expressions/constants | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/expressions/constants/constant.py -> build/bdist.linux-x86_64/wheel/cvxpy/expressions/constants | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/expressions/constants/callback_param.py -> build/bdist.linux-x86_64/wheel/cvxpy/expressions/constants | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/expressions/expression.py -> build/bdist.linux-x86_64/wheel/cvxpy/expressions | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/version.py -> build/bdist.linux-x86_64/wheel/cvxpy | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/constraints | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/constraints/zero.py -> build/bdist.linux-x86_64/wheel/cvxpy/constraints | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/constraints/second_order.py -> build/bdist.linux-x86_64/wheel/cvxpy/constraints | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/constraints/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/constraints | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/constraints/psd.py -> build/bdist.linux-x86_64/wheel/cvxpy/constraints | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/constraints/exponential.py -> build/bdist.linux-x86_64/wheel/cvxpy/constraints | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/constraints/utilities.py -> build/bdist.linux-x86_64/wheel/cvxpy/constraints | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/constraints/nonpos.py -> build/bdist.linux-x86_64/wheel/cvxpy/constraints | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/constraints/constraint.py -> build/bdist.linux-x86_64/wheel/cvxpy/constraints | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/constraints/finite_set.py -> build/bdist.linux-x86_64/wheel/cvxpy/constraints | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/constraints/power.py -> build/bdist.linux-x86_64/wheel/cvxpy/constraints | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/quad_over_lin.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/sigma_max.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/condition_number.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/lambda_max.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/norm.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/von_neumann_entr.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/pnorm.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/norm_inf.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/gmatmul.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/matrix_frac.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/lambda_sum_smallest.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/dist_ratio.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/cummax.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/norm_nuc.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/axis_atom.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/eye_minus_inv.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/sum_smallest.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/tr_inv.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/pf_eigenvalue.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/max.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/suppfunc.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/geo_mean.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/inv_prod.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/one_minus_pos.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/atoms/affine | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine/partial_trace.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/affine | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine/hstack.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/affine | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine/sum.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/affine | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine/vstack.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/affine | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine/bmat.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/affine | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine/conv.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/affine | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/affine | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine/affine_atom.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/affine | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine/trace.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/affine | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine/index.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/affine | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine/unary_operators.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/affine | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine/imag.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/affine | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine/diff.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/affine | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine/conj.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/affine | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine/transpose.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/affine | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine/add_expr.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/affine | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine/cumsum.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/affine | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine/upper_tri.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/affine | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine/binary_operators.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/affine | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine/reshape.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/affine | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine/vec.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/affine | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine/diag.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/affine | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine/partial_transpose.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/affine | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine/wraps.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/affine | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine/kron.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/affine | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine/real.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/affine | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/affine/promote.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/affine | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/mixed_norm.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/dotsort.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/perspective.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/lambda_sum_largest.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/min.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/quad_form.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/length.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/gen_lambda_max.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/log_sum_exp.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/sum_squares.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/atom.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/harmonic_mean.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/sign.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/sum_largest.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/total_variation.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/norm1.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/lambda_min.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| creating build/bdist.linux-x86_64/wheel/cvxpy/atoms/elementwise | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise/huber.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/elementwise | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise/log.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/elementwise | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise/inv_pos.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/elementwise | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise/loggamma.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/elementwise | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise/log1p.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/elementwise | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise/__init__.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/elementwise | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise/ceil.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/elementwise | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise/minimum.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/elementwise | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise/maximum.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/elementwise | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise/scalene.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/elementwise | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise/neg.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/elementwise | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise/power.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/elementwise | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise/xexp.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/elementwise | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise/entr.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/elementwise | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise/log_normcdf.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/elementwise | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise/rel_entr.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/elementwise | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise/square.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/elementwise | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise/exp.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/elementwise | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise/kl_div.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/elementwise | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise/pos.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/elementwise | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise/elementwise.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/elementwise | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise/abs.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/elementwise | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise/logistic.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/elementwise | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/elementwise/sqrt.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms/elementwise | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/log_det.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/cvxpy/atoms/prod.py -> build/bdist.linux-x86_64/wheel/cvxpy/atoms | |
| copying build/lib.linux-x86_64-cpython-310/_cvxcore.cpython-310-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/wheel | |
| running install_egg_info | |
| running egg_info | |
| writing cvxpy.egg-info/PKG-INFO | |
| writing dependency_links to cvxpy.egg-info/dependency_links.txt | |
| writing requirements to cvxpy.egg-info/requires.txt | |
| writing top-level names to cvxpy.egg-info/top_level.txt | |
| reading manifest file 'cvxpy.egg-info/SOURCES.txt' | |
| reading manifest template 'MANIFEST.in' | |
| adding license file 'LICENSE' | |
| writing manifest file 'cvxpy.egg-info/SOURCES.txt' | |
| Copying cvxpy.egg-info to build/bdist.linux-x86_64/wheel/cvxpy-1.3.0-py3.10.egg-info | |
| running install_scripts | |
| creating build/bdist.linux-x86_64/wheel/cvxpy-1.3.0.dist-info/WHEEL | |
| creating '/build/pip-wheel-mx7qqpxq/.tmp-15ohid3x/cvxpy-1.3.0-cp310-cp310-linux_x86_64.whl' and adding 'build/bdist.linux-x86_64/wheel' to it | |
| adding '_cvxcore.cpython-310-x86_64-linux-gnu.so' | |
| adding 'cvxpy/__init__.py' | |
| adding 'cvxpy/error.py' | |
| adding 'cvxpy/py.typed' | |
| adding 'cvxpy/settings.py' | |
| adding 'cvxpy/version.py' | |
| adding 'cvxpy/atoms/__init__.py' | |
| adding 'cvxpy/atoms/atom.py' | |
| adding 'cvxpy/atoms/axis_atom.py' | |
| adding 'cvxpy/atoms/condition_number.py' | |
| adding 'cvxpy/atoms/cummax.py' | |
| adding 'cvxpy/atoms/dist_ratio.py' | |
| adding 'cvxpy/atoms/dotsort.py' | |
| adding 'cvxpy/atoms/eye_minus_inv.py' | |
| adding 'cvxpy/atoms/gen_lambda_max.py' | |
| adding 'cvxpy/atoms/geo_mean.py' | |
| adding 'cvxpy/atoms/gmatmul.py' | |
| adding 'cvxpy/atoms/harmonic_mean.py' | |
| adding 'cvxpy/atoms/inv_prod.py' | |
| adding 'cvxpy/atoms/lambda_max.py' | |
| adding 'cvxpy/atoms/lambda_min.py' | |
| adding 'cvxpy/atoms/lambda_sum_largest.py' | |
| adding 'cvxpy/atoms/lambda_sum_smallest.py' | |
| adding 'cvxpy/atoms/length.py' | |
| adding 'cvxpy/atoms/log_det.py' | |
| adding 'cvxpy/atoms/log_sum_exp.py' | |
| adding 'cvxpy/atoms/matrix_frac.py' | |
| adding 'cvxpy/atoms/max.py' | |
| adding 'cvxpy/atoms/min.py' | |
| adding 'cvxpy/atoms/mixed_norm.py' | |
| adding 'cvxpy/atoms/norm.py' | |
| adding 'cvxpy/atoms/norm1.py' | |
| adding 'cvxpy/atoms/norm_inf.py' | |
| adding 'cvxpy/atoms/norm_nuc.py' | |
| adding 'cvxpy/atoms/one_minus_pos.py' | |
| adding 'cvxpy/atoms/perspective.py' | |
| adding 'cvxpy/atoms/pf_eigenvalue.py' | |
| adding 'cvxpy/atoms/pnorm.py' | |
| adding 'cvxpy/atoms/prod.py' | |
| adding 'cvxpy/atoms/quad_form.py' | |
| adding 'cvxpy/atoms/quad_over_lin.py' | |
| adding 'cvxpy/atoms/sigma_max.py' | |
| adding 'cvxpy/atoms/sign.py' | |
| adding 'cvxpy/atoms/sum_largest.py' | |
| adding 'cvxpy/atoms/sum_smallest.py' | |
| adding 'cvxpy/atoms/sum_squares.py' | |
| adding 'cvxpy/atoms/suppfunc.py' | |
| adding 'cvxpy/atoms/total_variation.py' | |
| adding 'cvxpy/atoms/tr_inv.py' | |
| adding 'cvxpy/atoms/von_neumann_entr.py' | |
| adding 'cvxpy/atoms/affine/__init__.py' | |
| adding 'cvxpy/atoms/affine/add_expr.py' | |
| adding 'cvxpy/atoms/affine/affine_atom.py' | |
| adding 'cvxpy/atoms/affine/binary_operators.py' | |
| adding 'cvxpy/atoms/affine/bmat.py' | |
| adding 'cvxpy/atoms/affine/conj.py' | |
| adding 'cvxpy/atoms/affine/conv.py' | |
| adding 'cvxpy/atoms/affine/cumsum.py' | |
| adding 'cvxpy/atoms/affine/diag.py' | |
| adding 'cvxpy/atoms/affine/diff.py' | |
| adding 'cvxpy/atoms/affine/hstack.py' | |
| adding 'cvxpy/atoms/affine/imag.py' | |
| adding 'cvxpy/atoms/affine/index.py' | |
| adding 'cvxpy/atoms/affine/kron.py' | |
| adding 'cvxpy/atoms/affine/partial_trace.py' | |
| adding 'cvxpy/atoms/affine/partial_transpose.py' | |
| adding 'cvxpy/atoms/affine/promote.py' | |
| adding 'cvxpy/atoms/affine/real.py' | |
| adding 'cvxpy/atoms/affine/reshape.py' | |
| adding 'cvxpy/atoms/affine/sum.py' | |
| adding 'cvxpy/atoms/affine/trace.py' | |
| adding 'cvxpy/atoms/affine/transpose.py' | |
| adding 'cvxpy/atoms/affine/unary_operators.py' | |
| adding 'cvxpy/atoms/affine/upper_tri.py' | |
| adding 'cvxpy/atoms/affine/vec.py' | |
| adding 'cvxpy/atoms/affine/vstack.py' | |
| adding 'cvxpy/atoms/affine/wraps.py' | |
| adding 'cvxpy/atoms/elementwise/__init__.py' | |
| adding 'cvxpy/atoms/elementwise/abs.py' | |
| adding 'cvxpy/atoms/elementwise/ceil.py' | |
| adding 'cvxpy/atoms/elementwise/elementwise.py' | |
| adding 'cvxpy/atoms/elementwise/entr.py' | |
| adding 'cvxpy/atoms/elementwise/exp.py' | |
| adding 'cvxpy/atoms/elementwise/huber.py' | |
| adding 'cvxpy/atoms/elementwise/inv_pos.py' | |
| adding 'cvxpy/atoms/elementwise/kl_div.py' | |
| adding 'cvxpy/atoms/elementwise/log.py' | |
| adding 'cvxpy/atoms/elementwise/log1p.py' | |
| adding 'cvxpy/atoms/elementwise/log_normcdf.py' | |
| adding 'cvxpy/atoms/elementwise/loggamma.py' | |
| adding 'cvxpy/atoms/elementwise/logistic.py' | |
| adding 'cvxpy/atoms/elementwise/maximum.py' | |
| adding 'cvxpy/atoms/elementwise/minimum.py' | |
| adding 'cvxpy/atoms/elementwise/neg.py' | |
| adding 'cvxpy/atoms/elementwise/pos.py' | |
| adding 'cvxpy/atoms/elementwise/power.py' | |
| adding 'cvxpy/atoms/elementwise/rel_entr.py' | |
| adding 'cvxpy/atoms/elementwise/scalene.py' | |
| adding 'cvxpy/atoms/elementwise/sqrt.py' | |
| adding 'cvxpy/atoms/elementwise/square.py' | |
| adding 'cvxpy/atoms/elementwise/xexp.py' | |
| adding 'cvxpy/constraints/__init__.py' | |
| adding 'cvxpy/constraints/constraint.py' | |
| adding 'cvxpy/constraints/exponential.py' | |
| adding 'cvxpy/constraints/finite_set.py' | |
| adding 'cvxpy/constraints/nonpos.py' | |
| adding 'cvxpy/constraints/power.py' | |
| adding 'cvxpy/constraints/psd.py' | |
| adding 'cvxpy/constraints/second_order.py' | |
| adding 'cvxpy/constraints/utilities.py' | |
| adding 'cvxpy/constraints/zero.py' | |
| adding 'cvxpy/cvxcore/__init__.py' | |
| adding 'cvxpy/cvxcore/python/__init__.py' | |
| adding 'cvxpy/cvxcore/python/canonInterface.py' | |
| adding 'cvxpy/cvxcore/python/cvxcore.py' | |
| adding 'cvxpy/expressions/__init__.py' | |
| adding 'cvxpy/expressions/cvxtypes.py' | |
| adding 'cvxpy/expressions/expression.py' | |
| adding 'cvxpy/expressions/leaf.py' | |
| adding 'cvxpy/expressions/variable.py' | |
| adding 'cvxpy/expressions/constants/__init__.py' | |
| adding 'cvxpy/expressions/constants/callback_param.py' | |
| adding 'cvxpy/expressions/constants/constant.py' | |
| adding 'cvxpy/expressions/constants/parameter.py' | |
| adding 'cvxpy/interface/__init__.py' | |
| adding 'cvxpy/interface/base_matrix_interface.py' | |
| adding 'cvxpy/interface/matrix_utilities.py' | |
| adding 'cvxpy/interface/scipy_wrapper.py' | |
| adding 'cvxpy/interface/numpy_interface/__init__.py' | |
| adding 'cvxpy/interface/numpy_interface/matrix_interface.py' | |
| adding 'cvxpy/interface/numpy_interface/ndarray_interface.py' | |
| adding 'cvxpy/interface/numpy_interface/sparse_matrix_interface.py' | |
| adding 'cvxpy/lin_ops/__init__.py' | |
| adding 'cvxpy/lin_ops/canon_backend.py' | |
| adding 'cvxpy/lin_ops/lin_constraints.py' | |
| adding 'cvxpy/lin_ops/lin_op.py' | |
| adding 'cvxpy/lin_ops/lin_utils.py' | |
| adding 'cvxpy/lin_ops/tree_mat.py' | |
| adding 'cvxpy/problems/__init__.py' | |
| adding 'cvxpy/problems/iterative.py' | |
| adding 'cvxpy/problems/objective.py' | |
| adding 'cvxpy/problems/param_prob.py' | |
| adding 'cvxpy/problems/problem.py' | |
| adding 'cvxpy/problems/xpress_problem.py' | |
| adding 'cvxpy/reductions/__init__.py' | |
| adding 'cvxpy/reductions/canonicalization.py' | |
| adding 'cvxpy/reductions/chain.py' | |
| adding 'cvxpy/reductions/cvx_attr2constr.py' | |
| adding 'cvxpy/reductions/eval_params.py' | |
| adding 'cvxpy/reductions/flip_objective.py' | |
| adding 'cvxpy/reductions/inverse_data.py' | |
| adding 'cvxpy/reductions/matrix_stuffing.py' | |
| adding 'cvxpy/reductions/reduction.py' | |
| adding 'cvxpy/reductions/solution.py' | |
| adding 'cvxpy/reductions/utilities.py' | |
| adding 'cvxpy/reductions/complex2real/__init__.py' | |
| adding 'cvxpy/reductions/complex2real/complex2real.py' | |
| adding 'cvxpy/reductions/complex2real/canonicalizers/__init__.py' | |
| adding 'cvxpy/reductions/complex2real/canonicalizers/abs_canon.py' | |
| adding 'cvxpy/reductions/complex2real/canonicalizers/aff_canon.py' | |
| adding 'cvxpy/reductions/complex2real/canonicalizers/constant_canon.py' | |
| adding 'cvxpy/reductions/complex2real/canonicalizers/equality_canon.py' | |
| adding 'cvxpy/reductions/complex2real/canonicalizers/inequality_canon.py' | |
| adding 'cvxpy/reductions/complex2real/canonicalizers/matrix_canon.py' | |
| adding 'cvxpy/reductions/complex2real/canonicalizers/param_canon.py' | |
| adding 'cvxpy/reductions/complex2real/canonicalizers/pnorm_canon.py' | |
| adding 'cvxpy/reductions/complex2real/canonicalizers/psd_canon.py' | |
| adding 'cvxpy/reductions/complex2real/canonicalizers/soc_canon.py' | |
| adding 'cvxpy/reductions/complex2real/canonicalizers/variable_canon.py' | |
| adding 'cvxpy/reductions/cone2cone/__init__.py' | |
| adding 'cvxpy/reductions/cone2cone/affine2direct.py' | |
| adding 'cvxpy/reductions/cone2cone/approximations.py' | |
| adding 'cvxpy/reductions/cone2cone/exotic2common.py' | |
| adding 'cvxpy/reductions/dcp2cone/__init__.py' | |
| adding 'cvxpy/reductions/dcp2cone/cone_matrix_stuffing.py' | |
| adding 'cvxpy/reductions/dcp2cone/dcp2cone.py' | |
| adding 'cvxpy/reductions/dcp2cone/atom_canonicalizers/__init__.py' | |
| adding 'cvxpy/reductions/dcp2cone/atom_canonicalizers/entr_canon.py' | |
| adding 'cvxpy/reductions/dcp2cone/atom_canonicalizers/exp_canon.py' | |
| adding 'cvxpy/reductions/dcp2cone/atom_canonicalizers/geo_mean_canon.py' | |
| adding 'cvxpy/reductions/dcp2cone/atom_canonicalizers/huber_canon.py' | |
| adding 'cvxpy/reductions/dcp2cone/atom_canonicalizers/indicator_canon.py' | |
| adding 'cvxpy/reductions/dcp2cone/atom_canonicalizers/kl_div_canon.py' | |
| adding 'cvxpy/reductions/dcp2cone/atom_canonicalizers/lambda_max_canon.py' | |
| adding 'cvxpy/reductions/dcp2cone/atom_canonicalizers/lambda_sum_largest_canon.py' | |
| adding 'cvxpy/reductions/dcp2cone/atom_canonicalizers/log1p_canon.py' | |
| adding 'cvxpy/reductions/dcp2cone/atom_canonicalizers/log_canon.py' | |
| adding 'cvxpy/reductions/dcp2cone/atom_canonicalizers/log_det_canon.py' | |
| adding 'cvxpy/reductions/dcp2cone/atom_canonicalizers/log_sum_exp_canon.py' | |
| adding 'cvxpy/reductions/dcp2cone/atom_canonicalizers/logistic_canon.py' | |
| adding 'cvxpy/reductions/dcp2cone/atom_canonicalizers/matrix_frac_canon.py' | |
| adding 'cvxpy/reductions/dcp2cone/atom_canonicalizers/mul_canon.py' | |
| adding 'cvxpy/reductions/dcp2cone/atom_canonicalizers/normNuc_canon.py' | |
| adding 'cvxpy/reductions/dcp2cone/atom_canonicalizers/perspective_canon.py' | |
| adding 'cvxpy/reductions/dcp2cone/atom_canonicalizers/pnorm_canon.py' | |
| adding 'cvxpy/reductions/dcp2cone/atom_canonicalizers/power_canon.py' | |
| adding 'cvxpy/reductions/dcp2cone/atom_canonicalizers/quad_form_canon.py' | |
| adding 'cvxpy/reductions/dcp2cone/atom_canonicalizers/quad_over_lin_canon.py' | |
| adding 'cvxpy/reductions/dcp2cone/atom_canonicalizers/rel_entr_canon.py' | |
| adding 'cvxpy/reductions/dcp2cone/atom_canonicalizers/sigma_max_canon.py' | |
| adding 'cvxpy/reductions/dcp2cone/atom_canonicalizers/suppfunc_canon.py' | |
| adding 'cvxpy/reductions/dcp2cone/atom_canonicalizers/tr_inv_canon.py' | |
| adding 'cvxpy/reductions/dcp2cone/atom_canonicalizers/von_neumann_entr_canon.py' | |
| adding 'cvxpy/reductions/dcp2cone/atom_canonicalizers/xexp_canon.py' | |
| adding 'cvxpy/reductions/dgp2dcp/__init__.py' | |
| adding 'cvxpy/reductions/dgp2dcp/dgp2dcp.py' | |
| adding 'cvxpy/reductions/dgp2dcp/util.py' | |
| adding 'cvxpy/reductions/dgp2dcp/atom_canonicalizers/__init__.py' | |
| adding 'cvxpy/reductions/dgp2dcp/atom_canonicalizers/add_canon.py' | |
| adding 'cvxpy/reductions/dgp2dcp/atom_canonicalizers/constant_canon.py' | |
| adding 'cvxpy/reductions/dgp2dcp/atom_canonicalizers/div_canon.py' | |
| adding 'cvxpy/reductions/dgp2dcp/atom_canonicalizers/exp_canon.py' | |
| adding 'cvxpy/reductions/dgp2dcp/atom_canonicalizers/eye_minus_inv_canon.py' | |
| adding 'cvxpy/reductions/dgp2dcp/atom_canonicalizers/geo_mean_canon.py' | |
| adding 'cvxpy/reductions/dgp2dcp/atom_canonicalizers/gmatmul_canon.py' | |
| adding 'cvxpy/reductions/dgp2dcp/atom_canonicalizers/log_canon.py' | |
| adding 'cvxpy/reductions/dgp2dcp/atom_canonicalizers/mul_canon.py' | |
| adding 'cvxpy/reductions/dgp2dcp/atom_canonicalizers/mulexpression_canon.py' | |
| adding 'cvxpy/reductions/dgp2dcp/atom_canonicalizers/nonpos_constr_canon.py' | |
| adding 'cvxpy/reductions/dgp2dcp/atom_canonicalizers/norm1_canon.py' | |
| adding 'cvxpy/reductions/dgp2dcp/atom_canonicalizers/norm_inf_canon.py' | |
| adding 'cvxpy/reductions/dgp2dcp/atom_canonicalizers/one_minus_pos_canon.py' | |
| adding 'cvxpy/reductions/dgp2dcp/atom_canonicalizers/parameter_canon.py' | |
| adding 'cvxpy/reductions/dgp2dcp/atom_canonicalizers/pf_eigenvalue_canon.py' | |
| adding 'cvxpy/reductions/dgp2dcp/atom_canonicalizers/pnorm_canon.py' | |
| adding 'cvxpy/reductions/dgp2dcp/atom_canonicalizers/power_canon.py' | |
| adding 'cvxpy/reductions/dgp2dcp/atom_canonicalizers/prod_canon.py' | |
| adding 'cvxpy/reductions/dgp2dcp/atom_canonicalizers/quad_form_canon.py' | |
| adding 'cvxpy/reductions/dgp2dcp/atom_canonicalizers/quad_over_lin_canon.py' | |
| adding 'cvxpy/reductions/dgp2dcp/atom_canonicalizers/sum_canon.py' | |
| adding 'cvxpy/reductions/dgp2dcp/atom_canonicalizers/trace_canon.py' | |
| adding 'cvxpy/reductions/dgp2dcp/atom_canonicalizers/xexp_canon.py' | |
| adding 'cvxpy/reductions/dgp2dcp/atom_canonicalizers/zero_constr_canon.py' | |
| adding 'cvxpy/reductions/discrete2mixedint/__init__.py' | |
| adding 'cvxpy/reductions/discrete2mixedint/valinvec2mixedint.py' | |
| adding 'cvxpy/reductions/dqcp2dcp/__init__.py' | |
| adding 'cvxpy/reductions/dqcp2dcp/dqcp2dcp.py' | |
| adding 'cvxpy/reductions/dqcp2dcp/inverse.py' | |
| adding 'cvxpy/reductions/dqcp2dcp/sets.py' | |
| adding 'cvxpy/reductions/dqcp2dcp/tighten.py' | |
| adding 'cvxpy/reductions/eliminate_pwl/__init__.py' | |
| adding 'cvxpy/reductions/eliminate_pwl/eliminate_pwl.py' | |
| adding 'cvxpy/reductions/eliminate_pwl/atom_canonicalizers/__init__.py' | |
| adding 'cvxpy/reductions/eliminate_pwl/atom_canonicalizers/abs_canon.py' | |
| adding 'cvxpy/reductions/eliminate_pwl/atom_canonicalizers/cummax_canon.py' | |
| adding 'cvxpy/reductions/eliminate_pwl/atom_canonicalizers/cumsum_canon.py' | |
| adding 'cvxpy/reductions/eliminate_pwl/atom_canonicalizers/dotsort_canon.py' | |
| adding 'cvxpy/reductions/eliminate_pwl/atom_canonicalizers/max_canon.py' | |
| adding 'cvxpy/reductions/eliminate_pwl/atom_canonicalizers/maximum_canon.py' | |
| adding 'cvxpy/reductions/eliminate_pwl/atom_canonicalizers/min_canon.py' | |
| adding 'cvxpy/reductions/eliminate_pwl/atom_canonicalizers/minimum_canon.py' | |
| adding 'cvxpy/reductions/eliminate_pwl/atom_canonicalizers/norm1_canon.py' | |
| adding 'cvxpy/reductions/eliminate_pwl/atom_canonicalizers/norm_inf_canon.py' | |
| adding 'cvxpy/reductions/eliminate_pwl/atom_canonicalizers/sum_largest_canon.py' | |
| adding 'cvxpy/reductions/qp2quad_form/__init__.py' | |
| adding 'cvxpy/reductions/qp2quad_form/qp2symbolic_qp.py' | |
| adding 'cvxpy/reductions/qp2quad_form/qp_matrix_stuffing.py' | |
| adding 'cvxpy/reductions/qp2quad_form/atom_canonicalizers/__init__.py' | |
| adding 'cvxpy/reductions/qp2quad_form/atom_canonicalizers/huber_canon.py' | |
| adding 'cvxpy/reductions/qp2quad_form/atom_canonicalizers/power_canon.py' | |
| adding 'cvxpy/reductions/qp2quad_form/atom_canonicalizers/quad_form_canon.py' | |
| adding 'cvxpy/reductions/qp2quad_form/atom_canonicalizers/quad_over_lin_canon.py' | |
| adding 'cvxpy/reductions/solvers/__init__.py' | |
| adding 'cvxpy/reductions/solvers/bisection.py' | |
| adding 'cvxpy/reductions/solvers/compr_matrix.py' | |
| adding 'cvxpy/reductions/solvers/constant_solver.py' | |
| adding 'cvxpy/reductions/solvers/defines.py' | |
| adding 'cvxpy/reductions/solvers/intermediate_chain.py' | |
| adding 'cvxpy/reductions/solvers/kktsolver.py' | |
| adding 'cvxpy/reductions/solvers/solver.py' | |
| adding 'cvxpy/reductions/solvers/solving_chain.py' | |
| adding 'cvxpy/reductions/solvers/utilities.py' | |
| adding 'cvxpy/reductions/solvers/conic_solvers/__init__.py' | |
| adding 'cvxpy/reductions/solvers/conic_solvers/cbc_conif.py' | |
| adding 'cvxpy/reductions/solvers/conic_solvers/clarabel_conif.py' | |
| adding 'cvxpy/reductions/solvers/conic_solvers/conic_solver.py' | |
| adding 'cvxpy/reductions/solvers/conic_solvers/copt_conif.py' | |
| adding 'cvxpy/reductions/solvers/conic_solvers/cplex_conif.py' | |
| adding 'cvxpy/reductions/solvers/conic_solvers/cvxopt_conif.py' | |
| adding 'cvxpy/reductions/solvers/conic_solvers/diffcp_conif.py' | |
| adding 'cvxpy/reductions/solvers/conic_solvers/ecos_bb_conif.py' | |
| adding 'cvxpy/reductions/solvers/conic_solvers/ecos_conif.py' | |
| adding 'cvxpy/reductions/solvers/conic_solvers/glop_conif.py' | |
| adding 'cvxpy/reductions/solvers/conic_solvers/glpk_conif.py' | |
| adding 'cvxpy/reductions/solvers/conic_solvers/glpk_mi_conif.py' | |
| adding 'cvxpy/reductions/solvers/conic_solvers/gurobi_conif.py' | |
| adding 'cvxpy/reductions/solvers/conic_solvers/mosek_conif.py' | |
| adding 'cvxpy/reductions/solvers/conic_solvers/nag_conif.py' | |
| adding 'cvxpy/reductions/solvers/conic_solvers/pdlp_conif.py' | |
| adding 'cvxpy/reductions/solvers/conic_solvers/scip_conif.py' | |
| adding 'cvxpy/reductions/solvers/conic_solvers/scipy_conif.py' | |
| adding 'cvxpy/reductions/solvers/conic_solvers/scs_conif.py' | |
| adding 'cvxpy/reductions/solvers/conic_solvers/sdpa_conif.py' | |
| adding 'cvxpy/reductions/solvers/conic_solvers/xpress_conif.py' | |
| adding 'cvxpy/reductions/solvers/lp_solvers/__init__.py' | |
| adding 'cvxpy/reductions/solvers/qp_solvers/__init__.py' | |
| adding 'cvxpy/reductions/solvers/qp_solvers/copt_qpif.py' | |
| adding 'cvxpy/reductions/solvers/qp_solvers/cplex_qpif.py' | |
| adding 'cvxpy/reductions/solvers/qp_solvers/gurobi_qpif.py' | |
| adding 'cvxpy/reductions/solvers/qp_solvers/osqp_qpif.py' | |
| adding 'cvxpy/reductions/solvers/qp_solvers/proxqp_qpif.py' | |
| adding 'cvxpy/reductions/solvers/qp_solvers/qp_solver.py' | |
| adding 'cvxpy/reductions/solvers/qp_solvers/xpress_qpif.py' | |
| adding 'cvxpy/tests/__init__.py' | |
| adding 'cvxpy/tests/base_test.py' | |
| adding 'cvxpy/tests/ram_limited.py' | |
| adding 'cvxpy/tests/solver_test_helpers.py' | |
| adding 'cvxpy/tests/test_atoms.py' | |
| adding 'cvxpy/tests/test_benchmarks.py' | |
| adding 'cvxpy/tests/test_complex.py' | |
| adding 'cvxpy/tests/test_cone2cone.py' | |
| adding 'cvxpy/tests/test_conic_solvers.py' | |
| adding 'cvxpy/tests/test_constant_atoms.py' | |
| adding 'cvxpy/tests/test_constraints.py' | |
| adding 'cvxpy/tests/test_convolution.py' | |
| adding 'cvxpy/tests/test_curvature.py' | |
| adding 'cvxpy/tests/test_custom_solver.py' | |
| adding 'cvxpy/tests/test_derivative.py' | |
| adding 'cvxpy/tests/test_dgp.py' | |
| adding 'cvxpy/tests/test_dgp2dcp.py' | |
| adding 'cvxpy/tests/test_domain.py' | |
| adding 'cvxpy/tests/test_dpp.py' | |
| adding 'cvxpy/tests/test_dqcp.py' | |
| adding 'cvxpy/tests/test_examples.py' | |
| adding 'cvxpy/tests/test_expressions.py' | |
| adding 'cvxpy/tests/test_grad.py' | |
| adding 'cvxpy/tests/test_gurobi_write.py' | |
| adding 'cvxpy/tests/test_interfaces.py' | |
| adding 'cvxpy/tests/test_kron_canon.py' | |
| adding 'cvxpy/tests/test_lin_ops.py' | |
| adding 'cvxpy/tests/test_linear_cone.py' | |
| adding 'cvxpy/tests/test_matrices.py' | |
| adding 'cvxpy/tests/test_mip_vars.py' | |
| adding 'cvxpy/tests/test_monotonicity.py' | |
| adding 'cvxpy/tests/test_nonlinear_atoms.py' | |
| adding 'cvxpy/tests/test_numpy.py' | |
| adding 'cvxpy/tests/test_objectives.py' | |
| adding 'cvxpy/tests/test_param_cone_prog.py' | |
| adding 'cvxpy/tests/test_param_quad_prog.py' | |
| adding 'cvxpy/tests/test_perspective.py' | |
| adding 'cvxpy/tests/test_power_tools.py' | |
| adding 'cvxpy/tests/test_problem.py' | |
| adding 'cvxpy/tests/test_python_backends.py' | |
| adding 'cvxpy/tests/test_qp_solvers.py' | |
| adding 'cvxpy/tests/test_quad_form.py' | |
| adding 'cvxpy/tests/test_quadratic.py' | |
| adding 'cvxpy/tests/test_semidefinite_vars.py' | |
| adding 'cvxpy/tests/test_shape.py' | |
| adding 'cvxpy/tests/test_sign.py' | |
| adding 'cvxpy/tests/test_suppfunc.py' | |
| adding 'cvxpy/tests/test_valinvec2mixedint.py' | |
| adding 'cvxpy/tests/test_versioning.py' | |
| adding 'cvxpy/tests/test_von_neumann_entr.py' | |
| adding 'cvxpy/transforms/__init__.py' | |
| adding 'cvxpy/transforms/indicator.py' | |
| adding 'cvxpy/transforms/linearize.py' | |
| adding 'cvxpy/transforms/partial_optimize.py' | |
| adding 'cvxpy/transforms/scalarize.py' | |
| adding 'cvxpy/transforms/suppfunc.py' | |
| adding 'cvxpy/utilities/__init__.py' | |
| adding 'cvxpy/utilities/canonical.py' | |
| adding 'cvxpy/utilities/coeff_extractor.py' | |
| adding 'cvxpy/utilities/cvxpy_upgrade.py' | |
| adding 'cvxpy/utilities/debug_tools.py' | |
| adding 'cvxpy/utilities/deterministic.py' | |
| adding 'cvxpy/utilities/grad.py' | |
| adding 'cvxpy/utilities/key_utils.py' | |
| adding 'cvxpy/utilities/linalg.py' | |
| adding 'cvxpy/utilities/performance_utils.py' | |
| adding 'cvxpy/utilities/perspective_utils.py' | |
| adding 'cvxpy/utilities/power_tools.py' | |
| adding 'cvxpy/utilities/replace_quad_forms.py' | |
| adding 'cvxpy/utilities/scopes.py' | |
| adding 'cvxpy/utilities/shape.py' | |
| adding 'cvxpy/utilities/sign.py' | |
| adding 'cvxpy/utilities/versioning.py' | |
| adding 'cvxpy-1.3.0.dist-info/LICENSE' | |
| adding 'cvxpy-1.3.0.dist-info/METADATA' | |
| adding 'cvxpy-1.3.0.dist-info/WHEEL' | |
| adding 'cvxpy-1.3.0.dist-info/top_level.txt' | |
| adding 'cvxpy-1.3.0.dist-info/RECORD' | |
| removing build/bdist.linux-x86_64/wheel | |
| Building wheel for cvxpy (pyproject.toml) ... [?25l[?25hdone | |
| Created wheel for cvxpy: filename=cvxpy-1.3.0-cp310-cp310-linux_x86_64.whl size=3758565 sha256=af2aa00f454584042053402de4b71936417875f5a01681885cbd849cddf674f6 | |
| Stored in directory: /build/pip-ephem-wheel-cache-lkp2rwv1/wheels/7e/0f/2c/c365ce508bfeeb7950624a9de486544a6c1385e07f3d47d6e7 | |
| Successfully built cvxpy | |
| Finished creating a wheel... | |
| Finished executing pipBuildPhase | |
| @nix { "action": "setPhase", "phase": "installPhase" } | |
| installing | |
| Executing pipInstallPhase | |
| /build/cvxpy-1.3.0/dist /build/cvxpy-1.3.0 | |
| Processing ./cvxpy-1.3.0-cp310-cp310-linux_x86_64.whl | |
| Requirement already satisfied: setuptools in /nix/store/8zx4h7r5mn1b913hgi8rwjfynwg1wgdi-python3.10-setuptools-67.4.0/lib/python3.10/site-packages (from cvxpy==1.3.0) (67.4.0.post0) | |
| Requirement already satisfied: numpy>=1.15 in /nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages (from cvxpy==1.3.0) (1.24.2) | |
| Requirement already satisfied: ecos>=2 in /nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages (from cvxpy==1.3.0) (2.0.10) | |
| Requirement already satisfied: scipy>=1.1.0 in /nix/store/hvs05k932v31cfckv49nx1pin0qjd20v-python3.10-scipy-1.10.1/lib/python3.10/site-packages (from cvxpy==1.3.0) (1.10.1) | |
| Requirement already satisfied: osqp>=0.4.1 in /nix/store/rjz2xpbvcghm0h2yiw5dfms3x0wmrl7h-python3.10-osqp-0.6.2.post8/lib/python3.10/site-packages (from cvxpy==1.3.0) (0.6.2.post8) | |
| Requirement already satisfied: scs>=1.1.6 in /nix/store/5h0hvjxghcbmz2fhkw2pcraagbl2khds-python3.10-scs-3.0.0/lib/python3.10/site-packages (from cvxpy==1.3.0) (3.0.0) | |
| Requirement already satisfied: qdldl in /nix/store/cbzbxmm53l218bc4wp2l4n2nn1wbnpxl-python3.10-qdldl-0.1.5.post3/lib/python3.10/site-packages (from osqp>=0.4.1->cvxpy==1.3.0) (0.1.5.post3) | |
| Installing collected packages: cvxpy | |
| Successfully installed cvxpy-1.3.0 | |
| /build/cvxpy-1.3.0 | |
| Finished executing pipInstallPhase | |
| @nix { "action": "setPhase", "phase": "pythonOutputDistPhase" } | |
| pythonOutputDistPhase | |
| Executing pythonOutputDistPhase | |
| Finished executing pythonOutputDistPhase | |
| @nix { "action": "setPhase", "phase": "fixupPhase" } | |
| post-installation fixup | |
| shrinking RPATHs of ELF executables and libraries in /nix/store/6pw8zjlmxwjh0zxbsdpq4jpmqpfvbya0-python3.10-cvxpy-1.3.0 | |
| shrinking /nix/store/6pw8zjlmxwjh0zxbsdpq4jpmqpfvbya0-python3.10-cvxpy-1.3.0/lib/python3.10/site-packages/_cvxcore.cpython-310-x86_64-linux-gnu.so | |
| checking for references to /build/ in /nix/store/6pw8zjlmxwjh0zxbsdpq4jpmqpfvbya0-python3.10-cvxpy-1.3.0... | |
| patching script interpreter paths in /nix/store/6pw8zjlmxwjh0zxbsdpq4jpmqpfvbya0-python3.10-cvxpy-1.3.0 | |
| stripping (with command strip and flags -S) in /nix/store/6pw8zjlmxwjh0zxbsdpq4jpmqpfvbya0-python3.10-cvxpy-1.3.0/lib | |
| shrinking RPATHs of ELF executables and libraries in /nix/store/z8g5vjlhcjdx7jn4q725ijgdbcv2qbyd-python3.10-cvxpy-1.3.0-dist | |
| checking for references to /build/ in /nix/store/z8g5vjlhcjdx7jn4q725ijgdbcv2qbyd-python3.10-cvxpy-1.3.0-dist... | |
| patching script interpreter paths in /nix/store/z8g5vjlhcjdx7jn4q725ijgdbcv2qbyd-python3.10-cvxpy-1.3.0-dist | |
| Executing pythonRemoveTestsDir | |
| Finished executing pythonRemoveTestsDir | |
| @nix { "action": "setPhase", "phase": "installCheckPhase" } | |
| running install tests | |
| no Makefile or custom installCheckPhase, doing nothing | |
| @nix { "action": "setPhase", "phase": "pythonCatchConflictsPhase" } | |
| pythonCatchConflictsPhase | |
| @nix { "action": "setPhase", "phase": "pythonRemoveBinBytecodePhase" } | |
| pythonRemoveBinBytecodePhase | |
| @nix { "action": "setPhase", "phase": "pythonImportsCheckPhase" } | |
| pythonImportsCheckPhase | |
| Executing pythonImportsCheckPhase | |
| Check whether the following modules can be imported: cvxpy | |
| @nix { "action": "setPhase", "phase": "pytestCheckPhase" } | |
| pytestCheckPhase | |
| Executing pytestCheckPhase | |
| [1m============================= test session starts ==============================[0m | |
| platform linux -- Python 3.10.10, pytest-7.2.1, pluggy-1.0.0 | |
| rootdir: /build/cvxpy-1.3.0, configfile: pyproject.toml | |
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| cvxpy/tests/test_derivative.py [33ms[0m[33ms[0m[33ms[0m[33ms[0m[33ms[0m[33ms[0m[33ms[0m[33ms[0m[33ms[0m[33ms[0m[33ms[0m[33ms[0m[33ms[0m[33ms[0m[33ms[0m[33ms[0m[33ms[0m[33ms[0m[33ms[0m[33ms[0m[33ms[0m[33ms[0m[33ms[0m[33ms[0m[33ms[0m[33ms[0m[33ms[0m[33ms[0m[33ms[0m[33ms[0m[31m [ 54%][0m | |
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| cvxpy/tests/test_domain.py [32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[31m [ 59%][0m | |
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| cvxpy/tests/test_examples.py [32m.[0m[32m.[0m[32m.[0m[32m.[0m[31mF[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[31m [ 69%][0m | |
| cvxpy/tests/test_expressions.py [32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[31m [ 72%][0m | |
| cvxpy/tests/test_grad.py [32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[31m [ 74%][0m | |
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| cvxpy/tests/test_lin_ops.py [32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[31m [ 76%][0m | |
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| cvxpy/tests/test_matrices.py [32m.[0m[32m.[0m[32m.[0m[32m.[0m[31m [ 77%][0m | |
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| cvxpy/tests/test_nonlinear_atoms.py [32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[31m [ 78%][0m | |
| cvxpy/tests/test_numpy.py [32m.[0m[32m.[0m[32m.[0m[32m.[0m[31m [ 78%][0m | |
| cvxpy/tests/test_objectives.py [32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[31m [ 78%][0m | |
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| cvxpy/tests/test_perspective.py [32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[31m [ 82%][0m | |
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| cvxpy/tests/test_problem.py [32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[31mF[0m[32m.[0m[32m.[0m[32m.[0m[31mF[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[31mF[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[31m [ 86%] | |
| [0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[31mF[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[31m [ 89%][0m | |
| cvxpy/tests/test_python_backends.py [32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[31m [ 92%][0m | |
| cvxpy/tests/test_qp_solvers.py [32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[31m [ 92%][0m | |
| cvxpy/tests/test_quad_form.py [32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[31m [ 93%][0m | |
| cvxpy/tests/test_quadratic.py [32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[31m [ 94%][0m | |
| cvxpy/tests/test_semidefinite_vars.py [32m.[0m[32m.[0m[31m [ 94%][0m | |
| cvxpy/tests/test_shape.py [32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[31m [ 95%][0m | |
| cvxpy/tests/test_sign.py [32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[31m [ 95%][0m | |
| cvxpy/tests/test_suppfunc.py [32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[31m [ 96%][0m | |
| cvxpy/tests/test_valinvec2mixedint.py [32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[31m [ 99%][0m | |
| cvxpy/tests/test_versioning.py [32m.[0m[32m.[0m[32m.[0m[31m [ 99%][0m | |
| cvxpy/tests/test_von_neumann_entr.py [32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[32m.[0m[31m [100%][0m | |
| =================================== FAILURES =================================== | |
| [31m[1m____________________________ TestAtoms.test_flatten ____________________________[0m | |
| self = <cvxpy.tests.test_atoms.TestAtoms testMethod=test_flatten> | |
| def test_flatten(self) -> None: | |
| """Test flatten and vec.""" | |
| # Constant argument. | |
| A = np.arange(10) | |
| reshaped = np.reshape(A, (2, 5), order='F') | |
| expr = cp.vec(reshaped, order='F') | |
| self.assertItemsAlmostEqual(expr.value, A) | |
| expr = cp.Constant(reshaped).flatten(order='F') | |
| self.assertItemsAlmostEqual(expr.value, A) | |
| reshaped = np.reshape(A, (2, 5), order='C') | |
| expr = cp.vec(reshaped, order='C') | |
| self.assertItemsAlmostEqual(expr.value, A) | |
| expr = cp.Constant(reshaped).flatten(order='C') | |
| self.assertItemsAlmostEqual(expr.value, A) | |
| reshaped = np.reshape(A, (2, 5), order='F') | |
| expr = cp.vec(reshaped, order='F') | |
| self.assertItemsAlmostEqual(expr.value, A) | |
| expr = cp.Constant(reshaped).flatten() | |
| self.assertItemsAlmostEqual(expr.value, A) | |
| # Variable argument. | |
| x = Variable((2, 5)) | |
| reshaped = np.reshape(A, (2, 5), order='F') | |
| expr = cp.vec(x, order='F') | |
| > cp.Problem(cp.Minimize(0), [expr == A]).solve() | |
| [1m[31mcvxpy/tests/test_atoms.py[0m:1385: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| [31m[1m________________________ TestComplex.test_partial_trace ________________________[0m | |
| self = <cvxpy.tests.test_complex.TestComplex testMethod=test_partial_trace> | |
| def test_partial_trace(self) -> None: | |
| """ | |
| Test a problem with partial_trace. | |
| rho_ABC = rho_A \\otimes rho_B \\otimes rho_C. | |
| Here \\otimes signifies Kronecker product. | |
| Each rho_i is normalized, i.e. Tr(rho_i) = 1. | |
| """ | |
| # Set random state. | |
| np.random.seed(1) | |
| # Generate test case. | |
| rho_A = np.random.random((4, 4)) + 1j*np.random.random((4, 4)) | |
| rho_A /= np.trace(rho_A) | |
| rho_B = np.random.random((3, 3)) + 1j*np.random.random((3, 3)) | |
| rho_B /= np.trace(rho_B) | |
| rho_C = np.random.random((2, 2)) + 1j*np.random.random((2, 2)) | |
| rho_C /= np.trace(rho_C) | |
| rho_AB = np.kron(rho_A, rho_B) | |
| rho_AC = np.kron(rho_A, rho_C) | |
| # Construct a cvxpy Variable with value equal to rho_A \otimes rho_B \otimes rho_C. | |
| rho_ABC_val = np.kron(rho_AB, rho_C) | |
| rho_ABC = cp.Variable(shape=rho_ABC_val.shape, complex=True) | |
| cons = [ | |
| rho_ABC_val == rho_ABC, | |
| rho_AB == cp.partial_trace(rho_ABC, [4, 3, 2], axis=2), | |
| rho_AC == cp.partial_trace(rho_ABC, [4, 3, 2], axis=1), | |
| ] | |
| prob = cp.Problem(cp.Minimize(0), cons) | |
| > prob.solve() | |
| [1m[31mcvxpy/tests/test_complex.py[0m:674: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| [31m[1m______________________ TestComplex.test_partial_transpose ______________________[0m | |
| self = <cvxpy.tests.test_complex.TestComplex testMethod=test_partial_transpose> | |
| def test_partial_transpose(self) -> None: | |
| """ | |
| Test a problem with partial_transpose. | |
| rho_ABC = rho_A \\otimes rho_B \\otimes rho_C. | |
| Here \\otimes signifies Kronecker product. | |
| Each rho_i is normalized, i.e. Tr(rho_i) = 1. | |
| """ | |
| # Set random state. | |
| np.random.seed(1) | |
| # Generate three test cases | |
| rho_A = np.random.random((8, 8)) + 1j*np.random.random((8, 8)) | |
| rho_A /= np.trace(rho_A) | |
| rho_B = np.random.random((6, 6)) + 1j*np.random.random((6, 6)) | |
| rho_B /= np.trace(rho_B) | |
| rho_C = np.random.random((4, 4)) + 1j*np.random.random((4, 4)) | |
| rho_C /= np.trace(rho_C) | |
| rho_TC = np.kron(np.kron(rho_A, rho_B), rho_C.T) | |
| rho_TB = np.kron(np.kron(rho_A, rho_B.T), rho_C) | |
| # Construct a cvxpy Variable with value equal to rho_A \otimes rho_B \otimes rho_C. | |
| rho_ABC_val = np.kron(np.kron(rho_A, rho_B), rho_C) | |
| rho_ABC = cp.Variable(shape=rho_ABC_val.shape, complex=True) | |
| cons = [ | |
| rho_ABC_val == rho_ABC, | |
| rho_TC == cp.partial_transpose(rho_ABC, [8, 6, 4], axis=2), | |
| rho_TB == cp.partial_transpose(rho_ABC, [8, 6, 4], axis=1), | |
| ] | |
| prob = cp.Problem(cp.Minimize(0), cons) | |
| > prob.solve() | |
| [1m[31mcvxpy/tests/test_complex.py[0m:709: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| [31m[1m___________________ test_constant_atoms[atom_info1-Minimize] ___________________[0m | |
| atom_info = (<function <lambda> at 0x7ffe69ad5fc0>, (2, 2), [[[-5, 2], [-3, 1]]], Constant(CONSTANT, UNKNOWN, (2, 2))) | |
| objective_type = <class 'cvxpy.problems.objective.Minimize'> | |
| @pytest.mark.parametrize("atom_info, objective_type", atoms_minimize + atoms_maximize) | |
| def test_constant_atoms(atom_info, objective_type) -> None: | |
| atom, size, args, obj_val = atom_info | |
| for indexer in get_indices(size): | |
| for solver in SOLVERS_TO_TRY: | |
| # Atoms with Constant arguments. | |
| prob_val = obj_val[indexer].value | |
| const_args = [Constant(arg) for arg in args] | |
| if len(size) != 0: | |
| objective = objective_type(atom(*const_args)[indexer]) | |
| else: | |
| objective = objective_type(atom(*const_args)) | |
| problem = Problem(objective) | |
| run_atom(atom, problem, prob_val, solver) | |
| # Atoms with Variable arguments. | |
| variables = [] | |
| constraints = [] | |
| for idx, expr in enumerate(args): | |
| variables.append(Variable(intf.shape(expr))) | |
| constraints.append(variables[-1] == expr) | |
| if len(size) != 0: | |
| objective = objective_type(atom(*variables)[indexer]) | |
| else: | |
| objective = objective_type(atom(*variables)) | |
| problem = Problem(objective, constraints) | |
| > run_atom(atom, problem, prob_val, solver) | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:396: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:341: in run_atom | |
| result = problem.solve(solver=solver, verbose=verbose) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| minimize cumsum([[-5. -3.] | |
| [ 2. 1.]], 1)[0, 0] | |
| minimize cumsum(var54707, 1)[0, 0] | |
| subject to var54707 == [[-5. -3.] | |
| [ 2. 1.]] | |
| [31m[1m___________________ test_constant_atoms[atom_info2-Minimize] ___________________[0m | |
| atom_info = (<function <lambda> at 0x7ffe69ad6050>, (2, 2), [[[-5, 2], [-3, 1]]], Constant(CONSTANT, NONPOSITIVE, (2, 2))) | |
| objective_type = <class 'cvxpy.problems.objective.Minimize'> | |
| @pytest.mark.parametrize("atom_info, objective_type", atoms_minimize + atoms_maximize) | |
| def test_constant_atoms(atom_info, objective_type) -> None: | |
| atom, size, args, obj_val = atom_info | |
| for indexer in get_indices(size): | |
| for solver in SOLVERS_TO_TRY: | |
| # Atoms with Constant arguments. | |
| prob_val = obj_val[indexer].value | |
| const_args = [Constant(arg) for arg in args] | |
| if len(size) != 0: | |
| objective = objective_type(atom(*const_args)[indexer]) | |
| else: | |
| objective = objective_type(atom(*const_args)) | |
| problem = Problem(objective) | |
| run_atom(atom, problem, prob_val, solver) | |
| # Atoms with Variable arguments. | |
| variables = [] | |
| constraints = [] | |
| for idx, expr in enumerate(args): | |
| variables.append(Variable(intf.shape(expr))) | |
| constraints.append(variables[-1] == expr) | |
| if len(size) != 0: | |
| objective = objective_type(atom(*variables)[indexer]) | |
| else: | |
| objective = objective_type(atom(*variables)) | |
| problem = Problem(objective, constraints) | |
| > run_atom(atom, problem, prob_val, solver) | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:396: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:341: in run_atom | |
| result = problem.solve(solver=solver, verbose=verbose) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| minimize cumsum([[-5. -3.] | |
| [ 2. 1.]], 0)[0, 0] | |
| minimize cumsum(var54747, 0)[0, 0] | |
| subject to var54747 == [[-5. -3.] | |
| [ 2. 1.]] | |
| [31m[1m___________________ test_constant_atoms[atom_info5-Minimize] ___________________[0m | |
| atom_info = (<function diag at 0x7ffe6be73d90>, (2,), [[[-5, 2], [-3, 1]]], Constant(CONSTANT, UNKNOWN, (2,))) | |
| objective_type = <class 'cvxpy.problems.objective.Minimize'> | |
| @pytest.mark.parametrize("atom_info, objective_type", atoms_minimize + atoms_maximize) | |
| def test_constant_atoms(atom_info, objective_type) -> None: | |
| atom, size, args, obj_val = atom_info | |
| for indexer in get_indices(size): | |
| for solver in SOLVERS_TO_TRY: | |
| # Atoms with Constant arguments. | |
| prob_val = obj_val[indexer].value | |
| const_args = [Constant(arg) for arg in args] | |
| if len(size) != 0: | |
| objective = objective_type(atom(*const_args)[indexer]) | |
| else: | |
| objective = objective_type(atom(*const_args)) | |
| problem = Problem(objective) | |
| run_atom(atom, problem, prob_val, solver) | |
| # Atoms with Variable arguments. | |
| variables = [] | |
| constraints = [] | |
| for idx, expr in enumerate(args): | |
| variables.append(Variable(intf.shape(expr))) | |
| constraints.append(variables[-1] == expr) | |
| if len(size) != 0: | |
| objective = objective_type(atom(*variables)[indexer]) | |
| else: | |
| objective = objective_type(atom(*variables)) | |
| problem = Problem(objective, constraints) | |
| > run_atom(atom, problem, prob_val, solver) | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:396: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:341: in run_atom | |
| result = problem.solve(solver=solver, verbose=verbose) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| minimize diag_mat([[-5. -3.] | |
| [ 2. 1.]])[0] | |
| minimize diag_mat(var56107)[0] | |
| subject to var56107 == [[-5. -3.] | |
| [ 2. 1.]] | |
| [31m[1m___________________ test_constant_atoms[atom_info6-Minimize] ___________________[0m | |
| atom_info = (<function diag at 0x7ffe6be73d90>, (2, 2), [[-5, 1]], Constant(CONSTANT, UNKNOWN, (2, 2))) | |
| objective_type = <class 'cvxpy.problems.objective.Minimize'> | |
| @pytest.mark.parametrize("atom_info, objective_type", atoms_minimize + atoms_maximize) | |
| def test_constant_atoms(atom_info, objective_type) -> None: | |
| atom, size, args, obj_val = atom_info | |
| for indexer in get_indices(size): | |
| for solver in SOLVERS_TO_TRY: | |
| # Atoms with Constant arguments. | |
| prob_val = obj_val[indexer].value | |
| const_args = [Constant(arg) for arg in args] | |
| if len(size) != 0: | |
| objective = objective_type(atom(*const_args)[indexer]) | |
| else: | |
| objective = objective_type(atom(*const_args)) | |
| problem = Problem(objective) | |
| run_atom(atom, problem, prob_val, solver) | |
| # Atoms with Variable arguments. | |
| variables = [] | |
| constraints = [] | |
| for idx, expr in enumerate(args): | |
| variables.append(Variable(intf.shape(expr))) | |
| constraints.append(variables[-1] == expr) | |
| if len(size) != 0: | |
| objective = objective_type(atom(*variables)[indexer]) | |
| else: | |
| objective = objective_type(atom(*variables)) | |
| problem = Problem(objective, constraints) | |
| > run_atom(atom, problem, prob_val, solver) | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:396: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:341: in run_atom | |
| result = problem.solve(solver=solver, verbose=verbose) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| minimize diag_vec(reshape([-5. 1.], (2,), F))[0, 0] | |
| minimize diag_vec(reshape(var56127, (2,), F))[0, 0] | |
| subject to var56127 == [-5. 1.] | |
| [31m[1m__________________ test_constant_atoms[atom_info19-Minimize] ___________________[0m | |
| atom_info = (<function <lambda> at 0x7ffe69ad63b0>, (4, 4), [array([[5, 6], | |
| [7, 8]])], Constant(CONSTANT, NONNEGATIVE, (4, 4))) | |
| objective_type = <class 'cvxpy.problems.objective.Minimize'> | |
| @pytest.mark.parametrize("atom_info, objective_type", atoms_minimize + atoms_maximize) | |
| def test_constant_atoms(atom_info, objective_type) -> None: | |
| atom, size, args, obj_val = atom_info | |
| for indexer in get_indices(size): | |
| for solver in SOLVERS_TO_TRY: | |
| # Atoms with Constant arguments. | |
| prob_val = obj_val[indexer].value | |
| const_args = [Constant(arg) for arg in args] | |
| if len(size) != 0: | |
| objective = objective_type(atom(*const_args)[indexer]) | |
| else: | |
| objective = objective_type(atom(*const_args)) | |
| problem = Problem(objective) | |
| run_atom(atom, problem, prob_val, solver) | |
| # Atoms with Variable arguments. | |
| variables = [] | |
| constraints = [] | |
| for idx, expr in enumerate(args): | |
| variables.append(Variable(intf.shape(expr))) | |
| constraints.append(variables[-1] == expr) | |
| if len(size) != 0: | |
| objective = objective_type(atom(*variables)[indexer]) | |
| else: | |
| objective = objective_type(atom(*variables)) | |
| problem = Problem(objective, constraints) | |
| > run_atom(atom, problem, prob_val, solver) | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:396: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:341: in run_atom | |
| result = problem.solve(solver=solver, verbose=verbose) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| minimize kron([[1. 2.] | |
| [3. 4.]], [[5. 6.] | |
| [7. 8.]])[0, 0] | |
| minimize kron([[1. 2.] | |
| [3. 4.]], var62516)[0, 0] | |
| subject to var62516 == [[5. 6.] | |
| [7. 8.]] | |
| [31m[1m__________________ test_constant_atoms[atom_info20-Minimize] ___________________[0m | |
| atom_info = (<function <lambda> at 0x7ffe69ad6440>, (6, 4), [array([[5, 6], | |
| [7, 8]])], Constant(CONSTANT, NONNEGATIVE, (6, 4))) | |
| objective_type = <class 'cvxpy.problems.objective.Minimize'> | |
| @pytest.mark.parametrize("atom_info, objective_type", atoms_minimize + atoms_maximize) | |
| def test_constant_atoms(atom_info, objective_type) -> None: | |
| atom, size, args, obj_val = atom_info | |
| for indexer in get_indices(size): | |
| for solver in SOLVERS_TO_TRY: | |
| # Atoms with Constant arguments. | |
| prob_val = obj_val[indexer].value | |
| const_args = [Constant(arg) for arg in args] | |
| if len(size) != 0: | |
| objective = objective_type(atom(*const_args)[indexer]) | |
| else: | |
| objective = objective_type(atom(*const_args)) | |
| problem = Problem(objective) | |
| run_atom(atom, problem, prob_val, solver) | |
| # Atoms with Variable arguments. | |
| variables = [] | |
| constraints = [] | |
| for idx, expr in enumerate(args): | |
| variables.append(Variable(intf.shape(expr))) | |
| constraints.append(variables[-1] == expr) | |
| if len(size) != 0: | |
| objective = objective_type(atom(*variables)[indexer]) | |
| else: | |
| objective = objective_type(atom(*variables)) | |
| problem = Problem(objective, constraints) | |
| > run_atom(atom, problem, prob_val, solver) | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:396: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:341: in run_atom | |
| result = problem.solve(solver=solver, verbose=verbose) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| minimize kron([[1. 2.] | |
| [3. 4.] | |
| [5. 6.]], [[5. 6.] | |
| [7. 8.]])[0, 0] | |
| minimize kron([[1. 2.] | |
| [3. 4.] | |
| [5. 6.]], var62535)[0, 0] | |
| subject to var62535 == [[5. 6.] | |
| [7. 8.]] | |
| [31m[1m__________________ test_constant_atoms[atom_info21-Minimize] ___________________[0m | |
| atom_info = (<function <lambda> at 0x7ffe69ad64d0>, (6, 4), [array([[ 5, 6], | |
| [ 7, 8], | |
| [ 9, 10]])], Constant(CONSTANT, NONNEGATIVE, (6, 4))) | |
| objective_type = <class 'cvxpy.problems.objective.Minimize'> | |
| @pytest.mark.parametrize("atom_info, objective_type", atoms_minimize + atoms_maximize) | |
| def test_constant_atoms(atom_info, objective_type) -> None: | |
| atom, size, args, obj_val = atom_info | |
| for indexer in get_indices(size): | |
| for solver in SOLVERS_TO_TRY: | |
| # Atoms with Constant arguments. | |
| prob_val = obj_val[indexer].value | |
| const_args = [Constant(arg) for arg in args] | |
| if len(size) != 0: | |
| objective = objective_type(atom(*const_args)[indexer]) | |
| else: | |
| objective = objective_type(atom(*const_args)) | |
| problem = Problem(objective) | |
| run_atom(atom, problem, prob_val, solver) | |
| # Atoms with Variable arguments. | |
| variables = [] | |
| constraints = [] | |
| for idx, expr in enumerate(args): | |
| variables.append(Variable(intf.shape(expr))) | |
| constraints.append(variables[-1] == expr) | |
| if len(size) != 0: | |
| objective = objective_type(atom(*variables)[indexer]) | |
| else: | |
| objective = objective_type(atom(*variables)) | |
| problem = Problem(objective, constraints) | |
| > run_atom(atom, problem, prob_val, solver) | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:396: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:341: in run_atom | |
| result = problem.solve(solver=solver, verbose=verbose) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| minimize kron([[1. 2.] | |
| [3. 4.]], [[ 5. 6.] | |
| [ 7. 8.] | |
| [ 9. 10.]])[0, 0] | |
| minimize kron([[1. 2.] | |
| [3. 4.]], var62554)[0, 0] | |
| subject to var62554 == [[ 5. 6.] | |
| [ 7. 8.] | |
| [ 9. 10.]] | |
| [31m[1m__________________ test_constant_atoms[atom_info22-Minimize] ___________________[0m | |
| atom_info = (<function <lambda> at 0x7ffe69ad6560>, (4, 4), [array([[5, 6], | |
| [7, 8]])], Constant(CONSTANT, NONNEGATIVE, (4, 4))) | |
| objective_type = <class 'cvxpy.problems.objective.Minimize'> | |
| @pytest.mark.parametrize("atom_info, objective_type", atoms_minimize + atoms_maximize) | |
| def test_constant_atoms(atom_info, objective_type) -> None: | |
| atom, size, args, obj_val = atom_info | |
| for indexer in get_indices(size): | |
| for solver in SOLVERS_TO_TRY: | |
| # Atoms with Constant arguments. | |
| prob_val = obj_val[indexer].value | |
| const_args = [Constant(arg) for arg in args] | |
| if len(size) != 0: | |
| objective = objective_type(atom(*const_args)[indexer]) | |
| else: | |
| objective = objective_type(atom(*const_args)) | |
| problem = Problem(objective) | |
| run_atom(atom, problem, prob_val, solver) | |
| # Atoms with Variable arguments. | |
| variables = [] | |
| constraints = [] | |
| for idx, expr in enumerate(args): | |
| variables.append(Variable(intf.shape(expr))) | |
| constraints.append(variables[-1] == expr) | |
| if len(size) != 0: | |
| objective = objective_type(atom(*variables)[indexer]) | |
| else: | |
| objective = objective_type(atom(*variables)) | |
| problem = Problem(objective, constraints) | |
| > run_atom(atom, problem, prob_val, solver) | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:396: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:341: in run_atom | |
| result = problem.solve(solver=solver, verbose=verbose) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| minimize kron([[5. 6.] | |
| [7. 8.]], [[1. 2.] | |
| [3. 4.]])[0, 0] | |
| minimize kron(var62573, [[1. 2.] | |
| [3. 4.]])[0, 0] | |
| subject to var62573 == [[5. 6.] | |
| [7. 8.]] | |
| [31m[1m__________________ test_constant_atoms[atom_info23-Minimize] ___________________[0m | |
| atom_info = (<function <lambda> at 0x7ffe69ad65f0>, (6, 4), [array([[5, 6], | |
| [7, 8]])], Constant(CONSTANT, NONNEGATIVE, (6, 4))) | |
| objective_type = <class 'cvxpy.problems.objective.Minimize'> | |
| @pytest.mark.parametrize("atom_info, objective_type", atoms_minimize + atoms_maximize) | |
| def test_constant_atoms(atom_info, objective_type) -> None: | |
| atom, size, args, obj_val = atom_info | |
| for indexer in get_indices(size): | |
| for solver in SOLVERS_TO_TRY: | |
| # Atoms with Constant arguments. | |
| prob_val = obj_val[indexer].value | |
| const_args = [Constant(arg) for arg in args] | |
| if len(size) != 0: | |
| objective = objective_type(atom(*const_args)[indexer]) | |
| else: | |
| objective = objective_type(atom(*const_args)) | |
| problem = Problem(objective) | |
| run_atom(atom, problem, prob_val, solver) | |
| # Atoms with Variable arguments. | |
| variables = [] | |
| constraints = [] | |
| for idx, expr in enumerate(args): | |
| variables.append(Variable(intf.shape(expr))) | |
| constraints.append(variables[-1] == expr) | |
| if len(size) != 0: | |
| objective = objective_type(atom(*variables)[indexer]) | |
| else: | |
| objective = objective_type(atom(*variables)) | |
| problem = Problem(objective, constraints) | |
| > run_atom(atom, problem, prob_val, solver) | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:396: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:341: in run_atom | |
| result = problem.solve(solver=solver, verbose=verbose) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| minimize kron([[5. 6.] | |
| [7. 8.]], [[1. 2.] | |
| [3. 4.] | |
| [5. 6.]])[0, 0] | |
| minimize kron(var62592, [[1. 2.] | |
| [3. 4.] | |
| [5. 6.]])[0, 0] | |
| subject to var62592 == [[5. 6.] | |
| [7. 8.]] | |
| [31m[1m__________________ test_constant_atoms[atom_info24-Minimize] ___________________[0m | |
| atom_info = (<function <lambda> at 0x7ffe69ad6680>, (6, 4), [array([[ 5, 6], | |
| [ 7, 8], | |
| [ 9, 10]])], Constant(CONSTANT, NONNEGATIVE, (6, 4))) | |
| objective_type = <class 'cvxpy.problems.objective.Minimize'> | |
| @pytest.mark.parametrize("atom_info, objective_type", atoms_minimize + atoms_maximize) | |
| def test_constant_atoms(atom_info, objective_type) -> None: | |
| atom, size, args, obj_val = atom_info | |
| for indexer in get_indices(size): | |
| for solver in SOLVERS_TO_TRY: | |
| # Atoms with Constant arguments. | |
| prob_val = obj_val[indexer].value | |
| const_args = [Constant(arg) for arg in args] | |
| if len(size) != 0: | |
| objective = objective_type(atom(*const_args)[indexer]) | |
| else: | |
| objective = objective_type(atom(*const_args)) | |
| problem = Problem(objective) | |
| run_atom(atom, problem, prob_val, solver) | |
| # Atoms with Variable arguments. | |
| variables = [] | |
| constraints = [] | |
| for idx, expr in enumerate(args): | |
| variables.append(Variable(intf.shape(expr))) | |
| constraints.append(variables[-1] == expr) | |
| if len(size) != 0: | |
| objective = objective_type(atom(*variables)[indexer]) | |
| else: | |
| objective = objective_type(atom(*variables)) | |
| problem = Problem(objective, constraints) | |
| > run_atom(atom, problem, prob_val, solver) | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:396: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:341: in run_atom | |
| result = problem.solve(solver=solver, verbose=verbose) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| minimize kron([[ 5. 6.] | |
| [ 7. 8.] | |
| [ 9. 10.]], [[1. 2.] | |
| [3. 4.]])[0, 0] | |
| minimize kron(var62611, [[1. 2.] | |
| [3. 4.]])[0, 0] | |
| subject to var62611 == [[ 5. 6.] | |
| [ 7. 8.] | |
| [ 9. 10.]] | |
| [31m[1m__________________ test_constant_atoms[atom_info68-Minimize] ___________________[0m | |
| atom_info = (<function <lambda> at 0x7ffe69ad7520>, (), [7.45], Constant(CONSTANT, NONNEGATIVE, (1,))) | |
| objective_type = <class 'cvxpy.problems.objective.Minimize'> | |
| @pytest.mark.parametrize("atom_info, objective_type", atoms_minimize + atoms_maximize) | |
| def test_constant_atoms(atom_info, objective_type) -> None: | |
| atom, size, args, obj_val = atom_info | |
| for indexer in get_indices(size): | |
| for solver in SOLVERS_TO_TRY: | |
| # Atoms with Constant arguments. | |
| prob_val = obj_val[indexer].value | |
| const_args = [Constant(arg) for arg in args] | |
| if len(size) != 0: | |
| objective = objective_type(atom(*const_args)[indexer]) | |
| else: | |
| objective = objective_type(atom(*const_args)) | |
| problem = Problem(objective) | |
| run_atom(atom, problem, prob_val, solver) | |
| # Atoms with Variable arguments. | |
| variables = [] | |
| constraints = [] | |
| for idx, expr in enumerate(args): | |
| variables.append(Variable(intf.shape(expr))) | |
| constraints.append(variables[-1] == expr) | |
| if len(size) != 0: | |
| objective = objective_type(atom(*variables)[indexer]) | |
| else: | |
| objective = objective_type(atom(*variables)) | |
| problem = Problem(objective, constraints) | |
| > run_atom(atom, problem, prob_val, solver) | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:396: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:341: in run_atom | |
| result = problem.solve(solver=solver, verbose=verbose) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| minimize power(7.45, 1.0) | |
| minimize power(var74641, 1.0) | |
| subject to var74641 == 7.45 | |
| [31m[1m__________________ test_constant_atoms[atom_info80-Minimize] ___________________[0m | |
| atom_info = (<function Sum at 0x7ffe6be713f0>, (), [[[-5, 2], [-3, 1]]], Constant(CONSTANT, NONPOSITIVE, (1,))) | |
| objective_type = <class 'cvxpy.problems.objective.Minimize'> | |
| @pytest.mark.parametrize("atom_info, objective_type", atoms_minimize + atoms_maximize) | |
| def test_constant_atoms(atom_info, objective_type) -> None: | |
| atom, size, args, obj_val = atom_info | |
| for indexer in get_indices(size): | |
| for solver in SOLVERS_TO_TRY: | |
| # Atoms with Constant arguments. | |
| prob_val = obj_val[indexer].value | |
| const_args = [Constant(arg) for arg in args] | |
| if len(size) != 0: | |
| objective = objective_type(atom(*const_args)[indexer]) | |
| else: | |
| objective = objective_type(atom(*const_args)) | |
| problem = Problem(objective) | |
| run_atom(atom, problem, prob_val, solver) | |
| # Atoms with Variable arguments. | |
| variables = [] | |
| constraints = [] | |
| for idx, expr in enumerate(args): | |
| variables.append(Variable(intf.shape(expr))) | |
| constraints.append(variables[-1] == expr) | |
| if len(size) != 0: | |
| objective = objective_type(atom(*variables)[indexer]) | |
| else: | |
| objective = objective_type(atom(*variables)) | |
| problem = Problem(objective, constraints) | |
| > run_atom(atom, problem, prob_val, solver) | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:396: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:341: in run_atom | |
| result = problem.solve(solver=solver, verbose=verbose) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| minimize Sum([[-5. -3.] | |
| [ 2. 1.]], None, False) | |
| minimize Sum(var79137, None, False) | |
| subject to var79137 == [[-5. -3.] | |
| [ 2. 1.]] | |
| [31m[1m__________________ test_constant_atoms[atom_info81-Minimize] ___________________[0m | |
| atom_info = (<function <lambda> at 0x7ffe69ad7a30>, (2,), [[[-5, 2], [-3, 1]]], Constant(CONSTANT, NONPOSITIVE, (2,))) | |
| objective_type = <class 'cvxpy.problems.objective.Minimize'> | |
| @pytest.mark.parametrize("atom_info, objective_type", atoms_minimize + atoms_maximize) | |
| def test_constant_atoms(atom_info, objective_type) -> None: | |
| atom, size, args, obj_val = atom_info | |
| for indexer in get_indices(size): | |
| for solver in SOLVERS_TO_TRY: | |
| # Atoms with Constant arguments. | |
| prob_val = obj_val[indexer].value | |
| const_args = [Constant(arg) for arg in args] | |
| if len(size) != 0: | |
| objective = objective_type(atom(*const_args)[indexer]) | |
| else: | |
| objective = objective_type(atom(*const_args)) | |
| problem = Problem(objective) | |
| run_atom(atom, problem, prob_val, solver) | |
| # Atoms with Variable arguments. | |
| variables = [] | |
| constraints = [] | |
| for idx, expr in enumerate(args): | |
| variables.append(Variable(intf.shape(expr))) | |
| constraints.append(variables[-1] == expr) | |
| if len(size) != 0: | |
| objective = objective_type(atom(*variables)[indexer]) | |
| else: | |
| objective = objective_type(atom(*variables)) | |
| problem = Problem(objective, constraints) | |
| > run_atom(atom, problem, prob_val, solver) | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:396: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:341: in run_atom | |
| result = problem.solve(solver=solver, verbose=verbose) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| minimize Sum([[-5. -3.] | |
| [ 2. 1.]], 0, False)[0] | |
| minimize Sum(var79154, 0, False)[0] | |
| subject to var79154 == [[-5. -3.] | |
| [ 2. 1.]] | |
| [31m[1m__________________ test_constant_atoms[atom_info82-Minimize] ___________________[0m | |
| atom_info = (<function <lambda> at 0x7ffe69ad7ac0>, (2,), [[[-5, 2], [-3, 1]]], Constant(CONSTANT, UNKNOWN, (2,))) | |
| objective_type = <class 'cvxpy.problems.objective.Minimize'> | |
| @pytest.mark.parametrize("atom_info, objective_type", atoms_minimize + atoms_maximize) | |
| def test_constant_atoms(atom_info, objective_type) -> None: | |
| atom, size, args, obj_val = atom_info | |
| for indexer in get_indices(size): | |
| for solver in SOLVERS_TO_TRY: | |
| # Atoms with Constant arguments. | |
| prob_val = obj_val[indexer].value | |
| const_args = [Constant(arg) for arg in args] | |
| if len(size) != 0: | |
| objective = objective_type(atom(*const_args)[indexer]) | |
| else: | |
| objective = objective_type(atom(*const_args)) | |
| problem = Problem(objective) | |
| run_atom(atom, problem, prob_val, solver) | |
| # Atoms with Variable arguments. | |
| variables = [] | |
| constraints = [] | |
| for idx, expr in enumerate(args): | |
| variables.append(Variable(intf.shape(expr))) | |
| constraints.append(variables[-1] == expr) | |
| if len(size) != 0: | |
| objective = objective_type(atom(*variables)[indexer]) | |
| else: | |
| objective = objective_type(atom(*variables)) | |
| problem = Problem(objective, constraints) | |
| > run_atom(atom, problem, prob_val, solver) | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:396: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:341: in run_atom | |
| result = problem.solve(solver=solver, verbose=verbose) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| minimize Sum([[-5. -3.] | |
| [ 2. 1.]], 1, False)[0] | |
| minimize Sum(var79173, 1, False)[0] | |
| subject to var79173 == [[-5. -3.] | |
| [ 2. 1.]] | |
| [31m[1m__________________ test_constant_atoms[atom_info87-Minimize] ___________________[0m | |
| atom_info = (<class 'cvxpy.atoms.affine.trace.trace'>, (), [[[3, 4, 5], [6, 7, 8], [9, 10, 11]]], Constant(CONSTANT, NONNEGATIVE, (1,))) | |
| objective_type = <class 'cvxpy.problems.objective.Minimize'> | |
| @pytest.mark.parametrize("atom_info, objective_type", atoms_minimize + atoms_maximize) | |
| def test_constant_atoms(atom_info, objective_type) -> None: | |
| atom, size, args, obj_val = atom_info | |
| for indexer in get_indices(size): | |
| for solver in SOLVERS_TO_TRY: | |
| # Atoms with Constant arguments. | |
| prob_val = obj_val[indexer].value | |
| const_args = [Constant(arg) for arg in args] | |
| if len(size) != 0: | |
| objective = objective_type(atom(*const_args)[indexer]) | |
| else: | |
| objective = objective_type(atom(*const_args)) | |
| problem = Problem(objective) | |
| run_atom(atom, problem, prob_val, solver) | |
| # Atoms with Variable arguments. | |
| variables = [] | |
| constraints = [] | |
| for idx, expr in enumerate(args): | |
| variables.append(Variable(intf.shape(expr))) | |
| constraints.append(variables[-1] == expr) | |
| if len(size) != 0: | |
| objective = objective_type(atom(*variables)[indexer]) | |
| else: | |
| objective = objective_type(atom(*variables)) | |
| problem = Problem(objective, constraints) | |
| > run_atom(atom, problem, prob_val, solver) | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:396: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:341: in run_atom | |
| result = problem.solve(solver=solver, verbose=verbose) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| minimize trace([[ 3. 6. 9.] | |
| [ 4. 7. 10.] | |
| [ 5. 8. 11.]]) | |
| minimize trace(var80248) | |
| subject to var80248 == [[ 3. 6. 9.] | |
| [ 4. 7. 10.] | |
| [ 5. 8. 11.]] | |
| [31m[1m__________________ test_constant_atoms[atom_info88-Minimize] ___________________[0m | |
| atom_info = (<class 'cvxpy.atoms.affine.trace.trace'>, (), [[[-5, 2], [-3, 1]]], Constant(CONSTANT, NONPOSITIVE, (1,))) | |
| objective_type = <class 'cvxpy.problems.objective.Minimize'> | |
| @pytest.mark.parametrize("atom_info, objective_type", atoms_minimize + atoms_maximize) | |
| def test_constant_atoms(atom_info, objective_type) -> None: | |
| atom, size, args, obj_val = atom_info | |
| for indexer in get_indices(size): | |
| for solver in SOLVERS_TO_TRY: | |
| # Atoms with Constant arguments. | |
| prob_val = obj_val[indexer].value | |
| const_args = [Constant(arg) for arg in args] | |
| if len(size) != 0: | |
| objective = objective_type(atom(*const_args)[indexer]) | |
| else: | |
| objective = objective_type(atom(*const_args)) | |
| problem = Problem(objective) | |
| run_atom(atom, problem, prob_val, solver) | |
| # Atoms with Variable arguments. | |
| variables = [] | |
| constraints = [] | |
| for idx, expr in enumerate(args): | |
| variables.append(Variable(intf.shape(expr))) | |
| constraints.append(variables[-1] == expr) | |
| if len(size) != 0: | |
| objective = objective_type(atom(*variables)[indexer]) | |
| else: | |
| objective = objective_type(atom(*variables)) | |
| problem = Problem(objective, constraints) | |
| > run_atom(atom, problem, prob_val, solver) | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:396: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:341: in run_atom | |
| result = problem.solve(solver=solver, verbose=verbose) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| minimize trace([[-5. -3.] | |
| [ 2. 1.]]) | |
| minimize trace(var80264) | |
| subject to var80264 == [[-5. -3.] | |
| [ 2. 1.]] | |
| [31m[1m__________________ test_constant_atoms[atom_info94-Minimize] ___________________[0m | |
| atom_info = (<class 'cvxpy.atoms.affine.upper_tri.upper_tri'>, (3,), [[[3, 4, 5], [6, 7, 8], [9, 10, 11]]], Constant(CONSTANT, NONNEGATIVE, (3,))) | |
| objective_type = <class 'cvxpy.problems.objective.Minimize'> | |
| @pytest.mark.parametrize("atom_info, objective_type", atoms_minimize + atoms_maximize) | |
| def test_constant_atoms(atom_info, objective_type) -> None: | |
| atom, size, args, obj_val = atom_info | |
| for indexer in get_indices(size): | |
| for solver in SOLVERS_TO_TRY: | |
| # Atoms with Constant arguments. | |
| prob_val = obj_val[indexer].value | |
| const_args = [Constant(arg) for arg in args] | |
| if len(size) != 0: | |
| objective = objective_type(atom(*const_args)[indexer]) | |
| else: | |
| objective = objective_type(atom(*const_args)) | |
| problem = Problem(objective) | |
| run_atom(atom, problem, prob_val, solver) | |
| # Atoms with Variable arguments. | |
| variables = [] | |
| constraints = [] | |
| for idx, expr in enumerate(args): | |
| variables.append(Variable(intf.shape(expr))) | |
| constraints.append(variables[-1] == expr) | |
| if len(size) != 0: | |
| objective = objective_type(atom(*variables)[indexer]) | |
| else: | |
| objective = objective_type(atom(*variables)) | |
| problem = Problem(objective, constraints) | |
| > run_atom(atom, problem, prob_val, solver) | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:396: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:341: in run_atom | |
| result = problem.solve(solver=solver, verbose=verbose) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| minimize upper_tri([[ 3. 6. 9.] | |
| [ 4. 7. 10.] | |
| [ 5. 8. 11.]])[0, 0] | |
| minimize upper_tri(var82259)[0, 0] | |
| subject to var82259 == [[ 3. 6. 9.] | |
| [ 4. 7. 10.] | |
| [ 5. 8. 11.]] | |
| [31m[1m__________________ test_constant_atoms[atom_info95-Minimize] ___________________[0m | |
| atom_info = (<function <lambda> at 0x7ffe69ad7d00>, (2,), [[[3, 4, 5], [6, 7, 8], [9, 10, 11]]], Constant(CONSTANT, NONNEGATIVE, (2,))) | |
| objective_type = <class 'cvxpy.problems.objective.Minimize'> | |
| @pytest.mark.parametrize("atom_info, objective_type", atoms_minimize + atoms_maximize) | |
| def test_constant_atoms(atom_info, objective_type) -> None: | |
| atom, size, args, obj_val = atom_info | |
| for indexer in get_indices(size): | |
| for solver in SOLVERS_TO_TRY: | |
| # Atoms with Constant arguments. | |
| prob_val = obj_val[indexer].value | |
| const_args = [Constant(arg) for arg in args] | |
| if len(size) != 0: | |
| objective = objective_type(atom(*const_args)[indexer]) | |
| else: | |
| objective = objective_type(atom(*const_args)) | |
| problem = Problem(objective) | |
| run_atom(atom, problem, prob_val, solver) | |
| # Atoms with Variable arguments. | |
| variables = [] | |
| constraints = [] | |
| for idx, expr in enumerate(args): | |
| variables.append(Variable(intf.shape(expr))) | |
| constraints.append(variables[-1] == expr) | |
| if len(size) != 0: | |
| objective = objective_type(atom(*variables)[indexer]) | |
| else: | |
| objective = objective_type(atom(*variables)) | |
| problem = Problem(objective, constraints) | |
| > run_atom(atom, problem, prob_val, solver) | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:396: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:341: in run_atom | |
| result = problem.solve(solver=solver, verbose=verbose) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| minimize [[ 3. 6. 9.] | |
| [ 4. 7. 10.] | |
| [ 5. 8. 11.]]([1, 2], [0, 2])[0] | |
| minimize var82278([1, 2], [0, 2])[0] | |
| subject to var82278 == [[ 3. 6. 9.] | |
| [ 4. 7. 10.] | |
| [ 5. 8. 11.]] | |
| [31m[1m__________________ test_constant_atoms[atom_info96-Minimize] ___________________[0m | |
| atom_info = (<function <lambda> at 0x7ffe69ad7d90>, (2, 2), [[[3, 4, 5], [6, 7, 8]]], Constant(CONSTANT, NONNEGATIVE, (2, 2))) | |
| objective_type = <class 'cvxpy.problems.objective.Minimize'> | |
| @pytest.mark.parametrize("atom_info, objective_type", atoms_minimize + atoms_maximize) | |
| def test_constant_atoms(atom_info, objective_type) -> None: | |
| atom, size, args, obj_val = atom_info | |
| for indexer in get_indices(size): | |
| for solver in SOLVERS_TO_TRY: | |
| # Atoms with Constant arguments. | |
| prob_val = obj_val[indexer].value | |
| const_args = [Constant(arg) for arg in args] | |
| if len(size) != 0: | |
| objective = objective_type(atom(*const_args)[indexer]) | |
| else: | |
| objective = objective_type(atom(*const_args)) | |
| problem = Problem(objective) | |
| run_atom(atom, problem, prob_val, solver) | |
| # Atoms with Variable arguments. | |
| variables = [] | |
| constraints = [] | |
| for idx, expr in enumerate(args): | |
| variables.append(Variable(intf.shape(expr))) | |
| constraints.append(variables[-1] == expr) | |
| if len(size) != 0: | |
| objective = objective_type(atom(*variables)[indexer]) | |
| else: | |
| objective = objective_type(atom(*variables)) | |
| problem = Problem(objective, constraints) | |
| > run_atom(atom, problem, prob_val, solver) | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:396: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:341: in run_atom | |
| result = problem.solve(solver=solver, verbose=verbose) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| minimize [[3. 6.] | |
| [4. 7.] | |
| [5. 8.]][1, 2][0, 0] | |
| minimize var82299[1, 2][0, 0] | |
| subject to var82299 == [[3. 6.] | |
| [4. 7.] | |
| [5. 8.]] | |
| [31m[1m__________________ test_constant_atoms[atom_info97-Minimize] ___________________[0m | |
| atom_info = (<function <lambda> at 0x7ffe69ad7e20>, (2,), [[[3, 4, 5], [6, 7, 8]]], Constant(CONSTANT, NONNEGATIVE, (3,))) | |
| objective_type = <class 'cvxpy.problems.objective.Minimize'> | |
| @pytest.mark.parametrize("atom_info, objective_type", atoms_minimize + atoms_maximize) | |
| def test_constant_atoms(atom_info, objective_type) -> None: | |
| atom, size, args, obj_val = atom_info | |
| for indexer in get_indices(size): | |
| for solver in SOLVERS_TO_TRY: | |
| # Atoms with Constant arguments. | |
| prob_val = obj_val[indexer].value | |
| const_args = [Constant(arg) for arg in args] | |
| if len(size) != 0: | |
| objective = objective_type(atom(*const_args)[indexer]) | |
| else: | |
| objective = objective_type(atom(*const_args)) | |
| problem = Problem(objective) | |
| run_atom(atom, problem, prob_val, solver) | |
| # Atoms with Variable arguments. | |
| variables = [] | |
| constraints = [] | |
| for idx, expr in enumerate(args): | |
| variables.append(Variable(intf.shape(expr))) | |
| constraints.append(variables[-1] == expr) | |
| if len(size) != 0: | |
| objective = objective_type(atom(*variables)[indexer]) | |
| else: | |
| objective = objective_type(atom(*variables)) | |
| problem = Problem(objective, constraints) | |
| > run_atom(atom, problem, prob_val, solver) | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:396: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:341: in run_atom | |
| result = problem.solve(solver=solver, verbose=verbose) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| minimize [[3. 6.] | |
| [4. 7.] | |
| [5. 8.]][[False True] | |
| [ True False] | |
| [False True]][0] | |
| minimize var82320[[False True] | |
| [ True False] | |
| [False True]][0] | |
| subject to var82320 == [[3. 6.] | |
| [4. 7.] | |
| [5. 8.]] | |
| [31m[1m__________________ test_constant_atoms[atom_info98-Minimize] ___________________[0m | |
| atom_info = (<function <lambda> at 0x7ffe69ad7eb0>, (2,), [[3, 4, 5]], Constant(CONSTANT, NONNEGATIVE, (2,))) | |
| objective_type = <class 'cvxpy.problems.objective.Minimize'> | |
| @pytest.mark.parametrize("atom_info, objective_type", atoms_minimize + atoms_maximize) | |
| def test_constant_atoms(atom_info, objective_type) -> None: | |
| atom, size, args, obj_val = atom_info | |
| for indexer in get_indices(size): | |
| for solver in SOLVERS_TO_TRY: | |
| # Atoms with Constant arguments. | |
| prob_val = obj_val[indexer].value | |
| const_args = [Constant(arg) for arg in args] | |
| if len(size) != 0: | |
| objective = objective_type(atom(*const_args)[indexer]) | |
| else: | |
| objective = objective_type(atom(*const_args)) | |
| problem = Problem(objective) | |
| run_atom(atom, problem, prob_val, solver) | |
| # Atoms with Variable arguments. | |
| variables = [] | |
| constraints = [] | |
| for idx, expr in enumerate(args): | |
| variables.append(Variable(intf.shape(expr))) | |
| constraints.append(variables[-1] == expr) | |
| if len(size) != 0: | |
| objective = objective_type(atom(*variables)[indexer]) | |
| else: | |
| objective = objective_type(atom(*variables)) | |
| problem = Problem(objective, constraints) | |
| > run_atom(atom, problem, prob_val, solver) | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:396: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:341: in run_atom | |
| result = problem.solve(solver=solver, verbose=verbose) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| minimize [3. 4. 5.][2][0] | |
| minimize var82341[2][0] | |
| subject to var82341 == [3. 4. 5.] | |
| [31m[1m__________________ test_constant_atoms[atom_info99-Minimize] ___________________[0m | |
| atom_info = (<function <lambda> at 0x7ffe69ad7f40>, (3,), [[3, 4, 5]], Constant(CONSTANT, NONNEGATIVE, (3,))) | |
| objective_type = <class 'cvxpy.problems.objective.Minimize'> | |
| @pytest.mark.parametrize("atom_info, objective_type", atoms_minimize + atoms_maximize) | |
| def test_constant_atoms(atom_info, objective_type) -> None: | |
| atom, size, args, obj_val = atom_info | |
| for indexer in get_indices(size): | |
| for solver in SOLVERS_TO_TRY: | |
| # Atoms with Constant arguments. | |
| prob_val = obj_val[indexer].value | |
| const_args = [Constant(arg) for arg in args] | |
| if len(size) != 0: | |
| objective = objective_type(atom(*const_args)[indexer]) | |
| else: | |
| objective = objective_type(atom(*const_args)) | |
| problem = Problem(objective) | |
| run_atom(atom, problem, prob_val, solver) | |
| # Atoms with Variable arguments. | |
| variables = [] | |
| constraints = [] | |
| for idx, expr in enumerate(args): | |
| variables.append(Variable(intf.shape(expr))) | |
| constraints.append(variables[-1] == expr) | |
| if len(size) != 0: | |
| objective = objective_type(atom(*variables)[indexer]) | |
| else: | |
| objective = objective_type(atom(*variables)) | |
| problem = Problem(objective, constraints) | |
| > run_atom(atom, problem, prob_val, solver) | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:396: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:341: in run_atom | |
| result = problem.solve(solver=solver, verbose=verbose) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| minimize [3. 4. 5.][2][0] | |
| minimize var82360[2][0] | |
| subject to var82360 == [3. 4. 5.] | |
| [31m[1m__________________ test_constant_atoms[atom_info100-Minimize] __________________[0m | |
| atom_info = (<function <lambda> at 0x7ffe69918040>, (2,), [[3, 4, 5]], Constant(CONSTANT, NONNEGATIVE, (2,))) | |
| objective_type = <class 'cvxpy.problems.objective.Minimize'> | |
| @pytest.mark.parametrize("atom_info, objective_type", atoms_minimize + atoms_maximize) | |
| def test_constant_atoms(atom_info, objective_type) -> None: | |
| atom, size, args, obj_val = atom_info | |
| for indexer in get_indices(size): | |
| for solver in SOLVERS_TO_TRY: | |
| # Atoms with Constant arguments. | |
| prob_val = obj_val[indexer].value | |
| const_args = [Constant(arg) for arg in args] | |
| if len(size) != 0: | |
| objective = objective_type(atom(*const_args)[indexer]) | |
| else: | |
| objective = objective_type(atom(*const_args)) | |
| problem = Problem(objective) | |
| run_atom(atom, problem, prob_val, solver) | |
| # Atoms with Variable arguments. | |
| variables = [] | |
| constraints = [] | |
| for idx, expr in enumerate(args): | |
| variables.append(Variable(intf.shape(expr))) | |
| constraints.append(variables[-1] == expr) | |
| if len(size) != 0: | |
| objective = objective_type(atom(*variables)[indexer]) | |
| else: | |
| objective = objective_type(atom(*variables)) | |
| problem = Problem(objective, constraints) | |
| > run_atom(atom, problem, prob_val, solver) | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:396: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:341: in run_atom | |
| result = problem.solve(solver=solver, verbose=verbose) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| minimize [3. 4. 5.][2][0] | |
| minimize var82379[2][0] | |
| subject to var82379 == [3. 4. 5.] | |
| [31m[1m__________________ test_constant_atoms[atom_info101-Minimize] __________________[0m | |
| atom_info = (<function <lambda> at 0x7ffe699180d0>, (3,), [[3, 4, 5]], Constant(CONSTANT, NONNEGATIVE, (3,))) | |
| objective_type = <class 'cvxpy.problems.objective.Minimize'> | |
| @pytest.mark.parametrize("atom_info, objective_type", atoms_minimize + atoms_maximize) | |
| def test_constant_atoms(atom_info, objective_type) -> None: | |
| atom, size, args, obj_val = atom_info | |
| for indexer in get_indices(size): | |
| for solver in SOLVERS_TO_TRY: | |
| # Atoms with Constant arguments. | |
| prob_val = obj_val[indexer].value | |
| const_args = [Constant(arg) for arg in args] | |
| if len(size) != 0: | |
| objective = objective_type(atom(*const_args)[indexer]) | |
| else: | |
| objective = objective_type(atom(*const_args)) | |
| problem = Problem(objective) | |
| run_atom(atom, problem, prob_val, solver) | |
| # Atoms with Variable arguments. | |
| variables = [] | |
| constraints = [] | |
| for idx, expr in enumerate(args): | |
| variables.append(Variable(intf.shape(expr))) | |
| constraints.append(variables[-1] == expr) | |
| if len(size) != 0: | |
| objective = objective_type(atom(*variables)[indexer]) | |
| else: | |
| objective = objective_type(atom(*variables)) | |
| problem = Problem(objective, constraints) | |
| > run_atom(atom, problem, prob_val, solver) | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:396: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:341: in run_atom | |
| result = problem.solve(solver=solver, verbose=verbose) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| minimize [3. 4. 5.][2][0] | |
| minimize var82398[2][0] | |
| subject to var82398 == [3. 4. 5.] | |
| [31m[1m__________________ test_constant_atoms[atom_info113-Maximize] __________________[0m | |
| atom_info = (<function <lambda> at 0x7ffe69918280>, (3,), [[1, 2, 3]], Constant(CONSTANT, NONNEGATIVE, (3,))) | |
| objective_type = <class 'cvxpy.problems.objective.Maximize'> | |
| @pytest.mark.parametrize("atom_info, objective_type", atoms_minimize + atoms_maximize) | |
| def test_constant_atoms(atom_info, objective_type) -> None: | |
| atom, size, args, obj_val = atom_info | |
| for indexer in get_indices(size): | |
| for solver in SOLVERS_TO_TRY: | |
| # Atoms with Constant arguments. | |
| prob_val = obj_val[indexer].value | |
| const_args = [Constant(arg) for arg in args] | |
| if len(size) != 0: | |
| objective = objective_type(atom(*const_args)[indexer]) | |
| else: | |
| objective = objective_type(atom(*const_args)) | |
| problem = Problem(objective) | |
| run_atom(atom, problem, prob_val, solver) | |
| # Atoms with Variable arguments. | |
| variables = [] | |
| constraints = [] | |
| for idx, expr in enumerate(args): | |
| variables.append(Variable(intf.shape(expr))) | |
| constraints.append(variables[-1] == expr) | |
| if len(size) != 0: | |
| objective = objective_type(atom(*variables)[indexer]) | |
| else: | |
| objective = objective_type(atom(*variables)) | |
| problem = Problem(objective, constraints) | |
| > run_atom(atom, problem, prob_val, solver) | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:396: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:341: in run_atom | |
| result = problem.solve(solver=solver, verbose=verbose) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| maximize [1. 2. 3.][0] | |
| maximize var84675[0] | |
| subject to var84675 == [1. 2. 3.] | |
| [31m[1m__________________ test_constant_atoms[atom_info114-Maximize] __________________[0m | |
| atom_info = (<function diff at 0x7ffe6be8c8b0>, (2,), [[1, 2, 3]], Constant(CONSTANT, NONNEGATIVE, (2,))) | |
| objective_type = <class 'cvxpy.problems.objective.Maximize'> | |
| @pytest.mark.parametrize("atom_info, objective_type", atoms_minimize + atoms_maximize) | |
| def test_constant_atoms(atom_info, objective_type) -> None: | |
| atom, size, args, obj_val = atom_info | |
| for indexer in get_indices(size): | |
| for solver in SOLVERS_TO_TRY: | |
| # Atoms with Constant arguments. | |
| prob_val = obj_val[indexer].value | |
| const_args = [Constant(arg) for arg in args] | |
| if len(size) != 0: | |
| objective = objective_type(atom(*const_args)[indexer]) | |
| else: | |
| objective = objective_type(atom(*const_args)) | |
| problem = Problem(objective) | |
| run_atom(atom, problem, prob_val, solver) | |
| # Atoms with Variable arguments. | |
| variables = [] | |
| constraints = [] | |
| for idx, expr in enumerate(args): | |
| variables.append(Variable(intf.shape(expr))) | |
| constraints.append(variables[-1] == expr) | |
| if len(size) != 0: | |
| objective = objective_type(atom(*variables)[indexer]) | |
| else: | |
| objective = objective_type(atom(*variables)) | |
| problem = Problem(objective, constraints) | |
| > run_atom(atom, problem, prob_val, solver) | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:396: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:341: in run_atom | |
| result = problem.solve(solver=solver, verbose=verbose) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| maximize [1. 2. 3.][1:3] + -[1. 2. 3.][0:2][0] | |
| maximize var84697[1:3] + -var84697[0:2][0] | |
| subject to var84697 == [1. 2. 3.] | |
| [31m[1m__________________ test_constant_atoms[atom_info115-Maximize] __________________[0m | |
| atom_info = (<function diff at 0x7ffe6be8c8b0>, (), [[1.1, 2.3]], Constant(CONSTANT, NONNEGATIVE, (1,))) | |
| objective_type = <class 'cvxpy.problems.objective.Maximize'> | |
| @pytest.mark.parametrize("atom_info, objective_type", atoms_minimize + atoms_maximize) | |
| def test_constant_atoms(atom_info, objective_type) -> None: | |
| atom, size, args, obj_val = atom_info | |
| for indexer in get_indices(size): | |
| for solver in SOLVERS_TO_TRY: | |
| # Atoms with Constant arguments. | |
| prob_val = obj_val[indexer].value | |
| const_args = [Constant(arg) for arg in args] | |
| if len(size) != 0: | |
| objective = objective_type(atom(*const_args)[indexer]) | |
| else: | |
| objective = objective_type(atom(*const_args)) | |
| problem = Problem(objective) | |
| run_atom(atom, problem, prob_val, solver) | |
| # Atoms with Variable arguments. | |
| variables = [] | |
| constraints = [] | |
| for idx, expr in enumerate(args): | |
| variables.append(Variable(intf.shape(expr))) | |
| constraints.append(variables[-1] == expr) | |
| if len(size) != 0: | |
| objective = objective_type(atom(*variables)[indexer]) | |
| else: | |
| objective = objective_type(atom(*variables)) | |
| problem = Problem(objective, constraints) | |
| > run_atom(atom, problem, prob_val, solver) | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:396: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:341: in run_atom | |
| result = problem.solve(solver=solver, verbose=verbose) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| maximize [1.1 2.3][1] + -[1.1 2.3][0] | |
| maximize var84726[1] + -var84726[0] | |
| subject to var84726 == [1.1 2.3] | |
| [31m[1m__________________ test_constant_atoms[atom_info116-Maximize] __________________[0m | |
| atom_info = (<function <lambda> at 0x7ffe69918310>, (), [[1, 2, 3]], Constant(CONSTANT, ZERO, (1,))) | |
| objective_type = <class 'cvxpy.problems.objective.Maximize'> | |
| @pytest.mark.parametrize("atom_info, objective_type", atoms_minimize + atoms_maximize) | |
| def test_constant_atoms(atom_info, objective_type) -> None: | |
| atom, size, args, obj_val = atom_info | |
| for indexer in get_indices(size): | |
| for solver in SOLVERS_TO_TRY: | |
| # Atoms with Constant arguments. | |
| prob_val = obj_val[indexer].value | |
| const_args = [Constant(arg) for arg in args] | |
| if len(size) != 0: | |
| objective = objective_type(atom(*const_args)[indexer]) | |
| else: | |
| objective = objective_type(atom(*const_args)) | |
| problem = Problem(objective) | |
| run_atom(atom, problem, prob_val, solver) | |
| # Atoms with Variable arguments. | |
| variables = [] | |
| constraints = [] | |
| for idx, expr in enumerate(args): | |
| variables.append(Variable(intf.shape(expr))) | |
| constraints.append(variables[-1] == expr) | |
| if len(size) != 0: | |
| objective = objective_type(atom(*variables)[indexer]) | |
| else: | |
| objective = objective_type(atom(*variables)) | |
| problem = Problem(objective, constraints) | |
| > run_atom(atom, problem, prob_val, solver) | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:396: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:341: in run_atom | |
| result = problem.solve(solver=solver, verbose=verbose) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| maximize [1. 2. 3.][1:3] + -[1. 2. 3.][0:2][1] + -[1. 2. 3.][1:3] + -[1. 2. 3.][0:2][0] | |
| maximize var84757[1:3] + -var84757[0:2][1] + -var84757[1:3] + -var84757[0:2][0] | |
| subject to var84757 == [1. 2. 3.] | |
| [31m[1m__________________ test_constant_atoms[atom_info117-Maximize] __________________[0m | |
| atom_info = (<function diff at 0x7ffe6be8c8b0>, (3,), [[2.1, 1, 4.5, -0.1]], Constant(CONSTANT, UNKNOWN, (3,))) | |
| objective_type = <class 'cvxpy.problems.objective.Maximize'> | |
| @pytest.mark.parametrize("atom_info, objective_type", atoms_minimize + atoms_maximize) | |
| def test_constant_atoms(atom_info, objective_type) -> None: | |
| atom, size, args, obj_val = atom_info | |
| for indexer in get_indices(size): | |
| for solver in SOLVERS_TO_TRY: | |
| # Atoms with Constant arguments. | |
| prob_val = obj_val[indexer].value | |
| const_args = [Constant(arg) for arg in args] | |
| if len(size) != 0: | |
| objective = objective_type(atom(*const_args)[indexer]) | |
| else: | |
| objective = objective_type(atom(*const_args)) | |
| problem = Problem(objective) | |
| run_atom(atom, problem, prob_val, solver) | |
| # Atoms with Variable arguments. | |
| variables = [] | |
| constraints = [] | |
| for idx, expr in enumerate(args): | |
| variables.append(Variable(intf.shape(expr))) | |
| constraints.append(variables[-1] == expr) | |
| if len(size) != 0: | |
| objective = objective_type(atom(*variables)[indexer]) | |
| else: | |
| objective = objective_type(atom(*variables)) | |
| problem = Problem(objective, constraints) | |
| > run_atom(atom, problem, prob_val, solver) | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:396: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:341: in run_atom | |
| result = problem.solve(solver=solver, verbose=verbose) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| maximize [ 2.1 1. 4.5 -0.1][1:4] + -[ 2.1 1. 4.5 -0.1][0:3][0] | |
| maximize var84797[1:4] + -var84797[0:3][0] | |
| subject to var84797 == [ 2.1 1. 4.5 -0.1] | |
| [31m[1m__________________ test_constant_atoms[atom_info118-Maximize] __________________[0m | |
| atom_info = (<function <lambda> at 0x7ffe699183a0>, (2,), [[2.1, 1, 4.5, -0.1]], Constant(CONSTANT, UNKNOWN, (2,))) | |
| objective_type = <class 'cvxpy.problems.objective.Maximize'> | |
| @pytest.mark.parametrize("atom_info, objective_type", atoms_minimize + atoms_maximize) | |
| def test_constant_atoms(atom_info, objective_type) -> None: | |
| atom, size, args, obj_val = atom_info | |
| for indexer in get_indices(size): | |
| for solver in SOLVERS_TO_TRY: | |
| # Atoms with Constant arguments. | |
| prob_val = obj_val[indexer].value | |
| const_args = [Constant(arg) for arg in args] | |
| if len(size) != 0: | |
| objective = objective_type(atom(*const_args)[indexer]) | |
| else: | |
| objective = objective_type(atom(*const_args)) | |
| problem = Problem(objective) | |
| run_atom(atom, problem, prob_val, solver) | |
| # Atoms with Variable arguments. | |
| variables = [] | |
| constraints = [] | |
| for idx, expr in enumerate(args): | |
| variables.append(Variable(intf.shape(expr))) | |
| constraints.append(variables[-1] == expr) | |
| if len(size) != 0: | |
| objective = objective_type(atom(*variables)[indexer]) | |
| else: | |
| objective = objective_type(atom(*variables)) | |
| problem = Problem(objective, constraints) | |
| > run_atom(atom, problem, prob_val, solver) | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:396: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:341: in run_atom | |
| result = problem.solve(solver=solver, verbose=verbose) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| maximize [ 2.1 1. 4.5 -0.1][1:4] + -[ 2.1 1. 4.5 -0.1][0:3][1:3] + -[ 2.1 1. 4.5 -0.1][1:4] + -[ 2.1 1. 4.5 -0.1][0:3][0:2][0] | |
| maximize var84831[1:4] + -var84831[0:3][1:3] + -var84831[1:4] + -var84831[0:3][0:2][0] | |
| subject to var84831 == [ 2.1 1. 4.5 -0.1] | |
| [31m[1m__________________ test_constant_atoms[atom_info119-Maximize] __________________[0m | |
| atom_info = (<function <lambda> at 0x7ffe69918430>, (1, 2), [array([[-5, -3], | |
| [ 2, 1]])], Constant(CONSTANT, NONNEGATIVE, (1, 2))) | |
| objective_type = <class 'cvxpy.problems.objective.Maximize'> | |
| @pytest.mark.parametrize("atom_info, objective_type", atoms_minimize + atoms_maximize) | |
| def test_constant_atoms(atom_info, objective_type) -> None: | |
| atom, size, args, obj_val = atom_info | |
| for indexer in get_indices(size): | |
| for solver in SOLVERS_TO_TRY: | |
| # Atoms with Constant arguments. | |
| prob_val = obj_val[indexer].value | |
| const_args = [Constant(arg) for arg in args] | |
| if len(size) != 0: | |
| objective = objective_type(atom(*const_args)[indexer]) | |
| else: | |
| objective = objective_type(atom(*const_args)) | |
| problem = Problem(objective) | |
| run_atom(atom, problem, prob_val, solver) | |
| # Atoms with Variable arguments. | |
| variables = [] | |
| constraints = [] | |
| for idx, expr in enumerate(args): | |
| variables.append(Variable(intf.shape(expr))) | |
| constraints.append(variables[-1] == expr) | |
| if len(size) != 0: | |
| objective = objective_type(atom(*variables)[indexer]) | |
| else: | |
| objective = objective_type(atom(*variables)) | |
| problem = Problem(objective, constraints) | |
| > run_atom(atom, problem, prob_val, solver) | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:396: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:341: in run_atom | |
| result = problem.solve(solver=solver, verbose=verbose) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| maximize [[-5. -3.] | |
| [ 2. 1.]][1, 0:2] + -[[-5. -3.] | |
| [ 2. 1.]][0, 0:2][0, 0] | |
| maximize var84873[1, 0:2] + -var84873[0, 0:2][0, 0] | |
| subject to var84873 == [[-5. -3.] | |
| [ 2. 1.]] | |
| [31m[1m__________________ test_constant_atoms[atom_info120-Maximize] __________________[0m | |
| atom_info = (<function <lambda> at 0x7ffe699184c0>, (2, 1), [array([[-5, -3], | |
| [ 2, 1]])], Constant(CONSTANT, UNKNOWN, (2, 1))) | |
| objective_type = <class 'cvxpy.problems.objective.Maximize'> | |
| @pytest.mark.parametrize("atom_info, objective_type", atoms_minimize + atoms_maximize) | |
| def test_constant_atoms(atom_info, objective_type) -> None: | |
| atom, size, args, obj_val = atom_info | |
| for indexer in get_indices(size): | |
| for solver in SOLVERS_TO_TRY: | |
| # Atoms with Constant arguments. | |
| prob_val = obj_val[indexer].value | |
| const_args = [Constant(arg) for arg in args] | |
| if len(size) != 0: | |
| objective = objective_type(atom(*const_args)[indexer]) | |
| else: | |
| objective = objective_type(atom(*const_args)) | |
| problem = Problem(objective) | |
| run_atom(atom, problem, prob_val, solver) | |
| # Atoms with Variable arguments. | |
| variables = [] | |
| constraints = [] | |
| for idx, expr in enumerate(args): | |
| variables.append(Variable(intf.shape(expr))) | |
| constraints.append(variables[-1] == expr) | |
| if len(size) != 0: | |
| objective = objective_type(atom(*variables)[indexer]) | |
| else: | |
| objective = objective_type(atom(*variables)) | |
| problem = Problem(objective, constraints) | |
| > run_atom(atom, problem, prob_val, solver) | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:396: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/tests/test_constant_atoms.py[0m:341: in run_atom | |
| result = problem.solve(solver=solver, verbose=verbose) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| maximize [[-5. -3.] | |
| [ 2. 1.]].T[1, 0:2] + -[[-5. -3.] | |
| [ 2. 1.]].T[0, 0:2].T[0, 0] | |
| maximize var84905.T[1, 0:2] + -var84905.T[0, 0:2].T[0, 0] | |
| subject to var84905 == [[-5. -3.] | |
| [ 2. 1.]] | |
| [31m[1m________________________ TestConvolution.test_conv_prob ________________________[0m | |
| self = <cvxpy.tests.test_convolution.TestConvolution testMethod=test_conv_prob> | |
| def test_conv_prob(self) -> None: | |
| """Test a problem with convolution. | |
| """ | |
| import numpy as np | |
| N = 5 | |
| y = np.random.randn(N, 1) | |
| h = np.random.randn(2, 1) | |
| x = cvx.Variable(N) | |
| v = cvx.conv(h, x) | |
| obj = cvx.Minimize(cvx.sum(cvx.multiply(y, v[0:N]))) | |
| > print(cvx.Problem(obj, []).solve(solver=cvx.ECOS)) | |
| [1m[31mcvxpy/tests/test_convolution.py[0m:111: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| [31m[1m__________________ TestDgp2Dcp.test_basic_equality_constraint __________________[0m | |
| self = <cvxpy.tests.test_dgp2dcp.TestDgp2Dcp testMethod=test_basic_equality_constraint> | |
| def test_basic_equality_constraint(self) -> None: | |
| x = cvxpy.Variable(pos=True) | |
| dgp = cvxpy.Problem(cvxpy.Minimize(x), [x == 1.0]) | |
| dgp2dcp = cvxpy.reductions.Dgp2Dcp(dgp) | |
| dcp = dgp2dcp.reduce() | |
| self.assertIsInstance(dcp.objective.expr, cvxpy.Variable) | |
| > opt = dcp.solve(SOLVER) | |
| [1m[31mcvxpy/tests/test_dgp2dcp.py[0m:63: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| [31m[1m__________________________ TestDgp2Dcp.test_geo_mean ___________________________[0m | |
| self = <cvxpy.tests.test_dgp2dcp.TestDgp2Dcp testMethod=test_geo_mean> | |
| def test_geo_mean(self) -> None: | |
| x = cvxpy.Variable(3, pos=True) | |
| p = [1, 2, 0.5] | |
| geo_mean = cvxpy.geo_mean(x, p) | |
| dgp = cvxpy.Problem(cvxpy.Minimize(geo_mean), []) | |
| dgp2dcp = cvxpy.reductions.Dgp2Dcp(dgp) | |
| dcp = dgp2dcp.reduce() | |
| > dcp.solve(SOLVER) | |
| [1m[31mcvxpy/tests/test_dgp2dcp.py[0m:308: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| [31m[1m___________________________ TestDgp2Dcp.test_gmatmul ___________________________[0m | |
| self = <cvxpy.tests.test_dgp2dcp.TestDgp2Dcp testMethod=test_gmatmul> | |
| def test_gmatmul(self) -> None: | |
| x = cvxpy.Variable(2, pos=True) | |
| A = np.array([[-5., 2.], [1., -3.]]) | |
| b = np.array([3, 2]) | |
| expr = cvxpy.gmatmul(A, x) | |
| x.value = b | |
| self.assertItemsAlmostEqual(expr.value, [3**-5*2**2, 3./8]) | |
| A_par = cvxpy.Parameter((2, 2), value=A) | |
| self.assertItemsAlmostEqual(cvxpy.gmatmul(A_par, x).value, | |
| [3**-5*2**2, 3./8]) | |
| x.value = None | |
| prob = cvxpy.Problem(cvxpy.Minimize(1.0), [expr == b]) | |
| > prob.solve(solver=SOLVER, gp=True) | |
| [1m[31mcvxpy/tests/test_dgp2dcp.py[0m:609: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| [31m[1m__________________________ TestDgp2Dcp.test_parameter __________________________[0m | |
| self = <cvxpy.tests.test_dgp2dcp.TestDgp2Dcp testMethod=test_parameter> | |
| def test_parameter(self) -> None: | |
| param = cvxpy.Parameter(pos=True) | |
| param.value = 1.0 | |
| dgp = cvxpy.Problem(cvxpy.Minimize(param), []) | |
| dgp2dcp = cvxpy.reductions.Dgp2Dcp(dgp) | |
| dcp = dgp2dcp.reduce() | |
| self.assertAlmostEqual(dcp.parameters()[0].value, np.log(param.value)) | |
| x = cvxpy.Variable(pos=True) | |
| problem = cvxpy.Problem(cvxpy.Minimize(x), [x == param]) | |
| > problem.solve(SOLVER, gp=True) | |
| [1m[31mcvxpy/tests/test_dgp2dcp.py[0m:581: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| [31m[1m____________ TestDgp2Dcp.test_solving_non_dcp_problem_raises_error _____________[0m | |
| self = <cvxpy.tests.test_dgp2dcp.TestDgp2Dcp testMethod=test_solving_non_dcp_problem_raises_error> | |
| def test_solving_non_dcp_problem_raises_error(self) -> None: | |
| problem = cvxpy.Problem( | |
| cvxpy.Minimize(cvxpy.Variable(pos=True) * cvxpy.Variable(pos=True)), | |
| ) | |
| with pytest.raises(error.DCPError, match='However, the problem does follow DGP rules'): | |
| > problem.solve(SOLVER, gp=True) | |
| [1m[31mcvxpy/tests/test_dgp2dcp.py[0m:331: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| [31m[1m____________ TestDgp2Dcp.test_solving_non_dgp_problem_raises_error _____________[0m | |
| self = <cvxpy.tests.test_dgp2dcp.TestDgp2Dcp testMethod=test_solving_non_dgp_problem_raises_error> | |
| def test_solving_non_dgp_problem_raises_error(self) -> None: | |
| problem = cvxpy.Problem(cvxpy.Minimize(-1.0 * cvxpy.Variable()), []) | |
| with pytest.raises(error.DGPError, match='However, the problem does follow DCP rules'): | |
| problem.solve(SOLVER, gp=True) | |
| > problem.solve(SOLVER) | |
| [1m[31mcvxpy/tests/test_dgp2dcp.py[0m:322: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| [31m[1m___________________ TestDgp2Dcp.test_unconstrained_monomial ____________________[0m | |
| self = <cvxpy.tests.test_dgp2dcp.TestDgp2Dcp testMethod=test_unconstrained_monomial> | |
| def test_unconstrained_monomial(self) -> None: | |
| x = cvxpy.Variable(pos=True) | |
| y = cvxpy.Variable(pos=True) | |
| prod = x * y | |
| dgp = cvxpy.Problem(cvxpy.Minimize(prod), []) | |
| dgp2dcp = cvxpy.reductions.Dgp2Dcp(dgp) | |
| dcp = dgp2dcp.reduce() | |
| self.assertIsInstance(dcp.objective.expr, AddExpression) | |
| self.assertEqual(len(dcp.objective.expr.args), 2) | |
| self.assertIsInstance(dcp.objective.expr.args[0], cvxpy.Variable) | |
| self.assertIsInstance(dcp.objective.expr.args[1], cvxpy.Variable) | |
| > opt = dcp.solve(SOLVER) | |
| [1m[31mcvxpy/tests/test_dgp2dcp.py[0m:28: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| [31m[1m_____________________________ TestDqcp.test_length _____________________________[0m | |
| self = <cvxpy.tests.test_dqcp.TestDqcp testMethod=test_length> | |
| def test_length(self) -> None: | |
| x = cp.Variable(5) | |
| expr = cp.length(x) | |
| self.assertTrue(expr.is_dqcp()) | |
| self.assertTrue(expr.is_quasiconvex()) | |
| self.assertFalse(expr.is_quasiconcave()) | |
| problem = cp.Problem(cp.Minimize(expr), [x[0] == 2.0, x[1] == 1.0]) | |
| > problem.solve(SOLVER, qcp=True) | |
| [1m[31mcvxpy/tests/test_dqcp.py[0m:382: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1049: in _solve | |
| soln = bisection.bisect( | |
| [1m[31mcvxpy/reductions/solvers/bisection.py[0m:174: in bisect | |
| _solve(lowered_feas, solver) | |
| [1m[31mcvxpy/reductions/solvers/bisection.py[0m:36: in _solve | |
| problem.solve(solver=solver) | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| [31m[1m___________________________ TestExamples.test_intro ____________________________[0m | |
| self = <cvxpy.tests.test_examples.TestExamples testMethod=test_intro> | |
| def test_intro(self) -> None: | |
| """Test examples from cvxpy.org introduction. | |
| """ | |
| import numpy | |
| # cvx.Problem data. | |
| m = 30 | |
| n = 20 | |
| numpy.random.seed(1) | |
| A = numpy.random.randn(m, n) | |
| b = numpy.random.randn(m) | |
| # Construct the problem. | |
| x = cvx.Variable(n) | |
| objective = cvx.Minimize(cvx.sum_squares(A @ x - b)) | |
| constraints = [0 <= x, x <= 1] | |
| prob = cvx.Problem(objective, constraints) | |
| # The optimal objective is returned by p.solve(). | |
| prob.solve(solver=cvx.SCS, eps=1e-6) | |
| # The optimal value for x is stored in x.value. | |
| print(x.value) | |
| # The optimal Lagrange multiplier for a constraint | |
| # is stored in constraint.dual_value. | |
| print(constraints[0].dual_value) | |
| ######################################## | |
| # Create two scalar variables. | |
| x = cvx.Variable() | |
| y = cvx.Variable() | |
| # Create two constraints. | |
| constraints = [x + y == 1, | |
| x - y >= 1] | |
| # Form objective. | |
| obj = cvx.Minimize(cvx.square(x - y)) | |
| # Form and solve problem. | |
| prob = cvx.Problem(obj, constraints) | |
| prob.solve(solver=cvx.SCS, eps=1e-6) # Returns the optimal value. | |
| print("status:", prob.status) | |
| print("optimal value", prob.value) | |
| print("optimal var", x.value, y.value) | |
| ######################################## | |
| # Create two scalar variables. | |
| x = cvx.Variable() | |
| y = cvx.Variable() | |
| # Create two constraints. | |
| constraints = [x + y == 1, | |
| x - y >= 1] | |
| # Form objective. | |
| obj = cvx.Minimize(cvx.square(x - y)) | |
| # Form and solve problem. | |
| prob = cvx.Problem(obj, constraints) | |
| prob.solve(solver=cvx.SCS, eps=1e-6) # Returns the optimal value. | |
| print("status:", prob.status) | |
| print("optimal value", prob.value) | |
| print("optimal var", x.value, y.value) | |
| self.assertEqual(prob.status, cvx.OPTIMAL) | |
| self.assertAlmostEqual(prob.value, 1.0) | |
| self.assertAlmostEqual(x.value, 1.0) | |
| self.assertAlmostEqual(y.value, 0) | |
| ######################################## | |
| # Replace the objective. | |
| prob = cvx.Problem(cvx.Maximize(x + y), prob.constraints) | |
| print("optimal value", prob.solve(solver=cvx.SCS, eps=1e-6)) | |
| self.assertAlmostEqual(prob.value, 1.0, places=3) | |
| # Replace the constraint (x + y == 1). | |
| constraints = prob.constraints | |
| constraints[0] = (x + y <= 3) | |
| prob = cvx.Problem(prob.objective, constraints) | |
| print("optimal value", prob.solve(solver=cvx.SCS, eps=1e-6)) | |
| self.assertAlmostEqual(prob.value, 3.0, places=2) | |
| ######################################## | |
| x = cvx.Variable() | |
| # An infeasible problem. | |
| prob = cvx.Problem(cvx.Minimize(x), [x >= 1, x <= 0]) | |
| prob.solve(solver=cvx.SCS, eps=1e-6) | |
| print("status:", prob.status) | |
| print("optimal value", prob.value) | |
| self.assertEqual(prob.status, cvx.INFEASIBLE) | |
| self.assertAlmostEqual(prob.value, np.inf) | |
| # An unbounded problem. | |
| prob = cvx.Problem(cvx.Minimize(x)) | |
| > prob.solve(solver=cvx.ECOS) | |
| [1m[31mcvxpy/tests/test_examples.py[0m:477: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| ----------------------------- Captured stdout call ----------------------------- | |
| [-3.83658887e-07 2.85110062e-02 4.62204680e-07 3.13604185e-07 | |
| -3.46205933e-07 1.49285317e-01 -7.55028388e-08 1.92974047e-07 | |
| 2.46718579e-01 5.78223657e-01 -3.46212344e-07 1.01209588e-03 | |
| 1.34842162e-07 2.26766991e-01 -2.00139443e-07 -1.91646838e-07 | |
| -1.22392761e-07 1.09604377e-07 2.88204259e-07 -6.33753633e-08] | |
| [ 2.50935647 0. 2.78357747 1.79428842 13.08575121 0. | |
| 0.73715604 3.35347392 0. 0. 8.93822025 0. | |
| 7.02956927 0. 4.71065605 3.18871929 2.06089042 10.08167813 | |
| 3.04814968 8.53267501] | |
| status: optimal | |
| optimal value 0.9999996287454611 | |
| optimal var 0.9999999071863565 9.281364315132923e-08 | |
| status: optimal | |
| optimal value 0.9999996287454611 | |
| optimal var 0.9999999071863565 9.281364315132923e-08 | |
| optimal value 0.9999999305159345 | |
| optimal value 3.000000000002148 | |
| status: infeasible | |
| optimal value inf | |
| [31m[1m_________________________ TestProblem.test_cumsum_axis _________________________[0m | |
| self = <cvxpy.tests.test_problem.TestProblem testMethod=test_cumsum_axis> | |
| def test_cumsum_axis(self) -> None: | |
| """Test the cumsum axis bug with row or column matrix | |
| See issue #1678 | |
| """ | |
| n = 5 | |
| # Solve for axis = 0 | |
| x1 = cp.Variable((1, n)) | |
| expr1 = cp.cumsum(x1, axis=0) | |
| prob1 = cp.Problem(cp.Minimize(0), [expr1 == 1]) | |
| > prob1.solve() | |
| [1m[31mcvxpy/tests/test_problem.py[0m:2004: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| [31m[1m_________________________ TestProblem.test_ecos_noineq _________________________[0m | |
| self = <cvxpy.tests.test_problem.TestProblem testMethod=test_ecos_noineq> | |
| def test_ecos_noineq(self) -> None: | |
| """Test ECOS with no inequality constraints. | |
| """ | |
| T = Constant(numpy.ones((2, 2))).value | |
| p = Problem(cp.Minimize(1), [self.A == T]) | |
| > result = p.solve(solver=s.ECOS) | |
| [1m[31mcvxpy/tests/test_problem.py[0m:627: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| [31m[1m________________________ TestProblem.test_mult_by_zero _________________________[0m | |
| self = <cvxpy.tests.test_problem.TestProblem testMethod=test_mult_by_zero> | |
| def test_mult_by_zero(self) -> None: | |
| """Test multiplication by zero. | |
| """ | |
| self.a.value = 1 | |
| exp = 0*self.a | |
| self.assertEqual(exp.value, 0) | |
| obj = cp.Minimize(exp) | |
| p = Problem(obj) | |
| > result = p.solve(solver=cp.ECOS) | |
| [1m[31mcvxpy/tests/test_problem.py[0m:1234: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| [31m[1m_________________________ TestProblem.test_rmul_param __________________________[0m | |
| self = <cvxpy.tests.test_problem.TestProblem testMethod=test_rmul_param> | |
| def test_rmul_param(self) -> None: | |
| """Test a complex rmul expression with a parameter. | |
| See issue #1555. | |
| """ | |
| b = cp.Variable((1,)) | |
| param = cp.Parameter(1) | |
| constraints = [] | |
| objective = cp.Minimize((2 * b) @ param) | |
| prob = cp.Problem(objective, constraints) | |
| param.value = np.array([1]) | |
| > prob.solve() | |
| [1m[31mcvxpy/tests/test_problem.py[0m:1991: | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| [1m[31mcvxpy/problems/problem.py[0m:493: in solve | |
| return solve_func(self, *args, **kwargs) | |
| [1m[31mcvxpy/problems/problem.py[0m:1064: in _solve | |
| solution = solving_chain.solve_via_data( | |
| [1m[31mcvxpy/reductions/solvers/solving_chain.py[0m:410: in solve_via_data | |
| return self.solver.solve_via_data(data, warm_start, verbose, | |
| [1m[31mcvxpy/reductions/solvers/conic_solvers/ecos_conif.py[0m:138: in solve_via_data | |
| solution = ecos.solve(data[s.C], data[s.G], data[s.H], | |
| [1m[31m/nix/store/g3dxwwl2b7k5vw62rv19c16p6xd7w451-python3.10-ecos-2.0.10/lib/python3.10/site-packages/ecos/ecos.py[0m:53: in solve | |
| indices = np.zeros((0,),dtype=np.int) | |
| _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ | |
| attr = 'int' | |
| def __getattr__(attr): | |
| # Warn for expired attributes, and return a dummy function | |
| # that always raises an exception. | |
| import warnings | |
| try: | |
| msg = __expired_functions__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| def _expired(*args, **kwds): | |
| raise RuntimeError(msg) | |
| return _expired | |
| # Emit warnings for deprecated attributes | |
| try: | |
| val, msg = __deprecated_attrs__[attr] | |
| except KeyError: | |
| pass | |
| else: | |
| warnings.warn(msg, DeprecationWarning, stacklevel=2) | |
| return val | |
| if attr in __future_scalars__: | |
| # And future warnings for those that will change, but also give | |
| # the AttributeError | |
| warnings.warn( | |
| f"In the future `np.{attr}` will be defined as the " | |
| "corresponding NumPy scalar.", FutureWarning, stacklevel=2) | |
| if attr in __former_attrs__: | |
| > raise AttributeError(__former_attrs__[attr]) | |
| [1m[31mE AttributeError: module 'numpy' has no attribute 'int'.[0m | |
| [1m[31mE `np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.[0m | |
| [1m[31mE The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:[0m | |
| [1m[31mE https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations. Did you mean: 'inf'?[0m | |
| [1m[31m/nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/__init__.py[0m:305: AttributeError | |
| [33m=============================== warnings summary ===============================[0m | |
| cvxpy/tests/test_atoms.py: 1 warning | |
| cvxpy/tests/test_complex.py: 1 warning | |
| cvxpy/tests/test_conic_solvers.py: 1 warning | |
| cvxpy/tests/test_dqcp.py: 44 warnings | |
| cvxpy/tests/test_examples.py: 1 warning | |
| cvxpy/tests/test_mip_vars.py: 1 warning | |
| cvxpy/tests/test_power_tools.py: 1 warning | |
| /build/cvxpy-1.3.0/cvxpy/problems/problem.py:1385: UserWarning: Solution may be inaccurate. Try another solver, adjusting the solver settings, or solve with verbose=True for more information. | |
| warnings.warn( | |
| cvxpy/tests/test_benchmarks.py::TestBenchmarks::test_parameterized_qp | |
| /build/cvxpy-1.3.0/cvxpy/reductions/solvers/solving_chain.py:209: UserWarning: Your problem has too many parameters for efficient DPP compilation. We suggest setting 'ignore_dpp = True'. | |
| warnings.warn( | |
| cvxpy/tests/test_complex.py: 4 warnings | |
| cvxpy/tests/test_conic_solvers.py: 8 warnings | |
| cvxpy/tests/test_constant_atoms.py: 115 warnings | |
| cvxpy/tests/test_constraints.py: 8 warnings | |
| cvxpy/tests/test_dqcp.py: 2 warnings | |
| cvxpy/tests/test_problem.py: 1 warning | |
| cvxpy/tests/test_von_neumann_entr.py: 1 warning | |
| /nix/store/hvs05k932v31cfckv49nx1pin0qjd20v-python3.10-scipy-1.10.1/lib/python3.10/site-packages/scipy/linalg/_decomp.py:1023: DeprecationWarning: Keyword argument 'eigvals' is deprecated in favour of 'subset_by_index' keyword instead and will be removed in SciPy 1.12.0. | |
| return eigh(a, b=b, lower=lower, eigvals_only=True, | |
| cvxpy/tests/test_complex.py::TestComplex::test_matrix_frac | |
| /nix/store/0n4y44dnaxafqs7cg625aldrb152x7bx-python3-3.10.10/lib/python3.10/logging/__init__.py:368: ComplexWarning: Casting complex values to real discards the imaginary part | |
| msg = msg % self.args | |
| cvxpy/tests/test_complex.py::TestComplex::test_quad_psd | |
| /nix/store/hvs05k932v31cfckv49nx1pin0qjd20v-python3.10-scipy-1.10.1/lib/python3.10/site-packages/scipy/sparse/linalg/_eigen/arpack/arpack.py:1272: RuntimeWarning: k >= N - 1 for N * N square matrix. Attempting to use scipy.linalg.eig instead. | |
| warnings.warn("k >= N - 1 for N * N square matrix. " | |
| cvxpy/tests/test_cone2cone.py::TestPowND::test_pcp_3a | |
| cvxpy/tests/test_cone2cone.py::TestPowND::test_pcp_3b | |
| cvxpy/tests/test_cone2cone.py::TestPowND::test_pcp_4a | |
| cvxpy/tests/test_cone2cone.py::TestPowND::test_pcp_4b | |
| /build/cvxpy-1.3.0/cvxpy/tests/solver_test_helpers.py:130: UserWarning: | |
| PowConeND dual variables not implemented; | |
| Skipping complementarity check. | |
| warnings.warn(msg) | |
| cvxpy/tests/test_cone2cone.py::TestOpRelConeQuad::test_oprelcone_2 | |
| /build/cvxpy-1.3.0/cvxpy/constraints/exponential.py:317: UserWarning: One of the input matrices has not explicitly been declared as symmetric orHermitian. If the inputs are Variable objects, try declaring them with thesymmetric=True or Hermitian=True properties. If the inputs are general Expression objects that are known to be symmetric or Hermitian, then youcan wrap them with the symmetric_wrap and hermitian_wrap atoms. Failure todo one of these things will cause this function to impose a symmetry orconjugate-symmetry constraint internally, in a way that is veryinefficient. | |
| warnings.warn(msg) | |
| cvxpy/tests/test_dqcp.py::TestDqcp::test_gen_lambda_max_matrix_completion | |
| /build/cvxpy-1.3.0/cvxpy/atoms/gen_lambda_max.py:37: DeprecationWarning: Keyword argument 'eigvals' is deprecated in favour of 'subset_by_index' keyword instead and will be removed in SciPy 1.12.0. | |
| return LA.eigh(a=values[0], | |
| cvxpy/tests/test_interfaces.py: 42 warnings | |
| /nix/store/0xhlg0vi0y8m5lxsm8khcqqma8rmy2jr-python3.10-numpy-1.24.2/lib/python3.10/site-packages/numpy/matrixlib/defmatrix.py:69: PendingDeprecationWarning: the matrix subclass is not the recommended way to represent matrices or deal with linear algebra (see https://docs.scipy.org/doc/numpy/user/numpy-for-matlab-users.html). Please adjust your code to use regular ndarray. | |
| return matrix(data, dtype=dtype, copy=False) | |
| cvxpy/tests/test_kron_canon.py::TestKronRightVar::test_gen_kronr_param | |
| cvxpy/tests/test_kron_canon.py::TestKronLeftVar::test_gen_kronl_param | |
| cvxpy/tests/test_kron_canon.py::TestKronLeftVar::test_scalar_kronl_param | |
| cvxpy/tests/test_kron_canon.py::TestKronLeftVar::test_symvar_kronl_param | |
| cvxpy/tests/test_perspective.py::test_parameter | |
| /build/cvxpy-1.3.0/cvxpy/reductions/solvers/solving_chain.py:200: UserWarning: You are solving a parameterized problem that is not DPP. Because the problem is not DPP, subsequent solves will not be faster than the first one. For more information, see the documentation on Discplined Parametrized Programming, at | |
| https://www.cvxpy.org/tutorial/advanced/index.html#disciplined-parametrized-programming | |
| warnings.warn(dpp_error_msg) | |
| cvxpy/tests/test_numpy.py::TestNumpy::test_broken_numpy_functions | |
| /build/cvxpy-1.3.0/cvxpy/expressions/expression.py:612: UserWarning: | |
| This use of ``*`` has resulted in matrix multiplication. | |
| Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1. | |
| Use ``*`` for matrix-scalar and vector-scalar multiplication. | |
| Use ``@`` for matrix-matrix and matrix-vector multiplication. | |
| Use ``multiply`` for elementwise multiplication. | |
| This code path has been hit 5 times so far. | |
| warnings.warn(msg, UserWarning) | |
| cvxpy/tests/test_numpy.py::TestNumpy::test_broken_numpy_functions | |
| /build/cvxpy-1.3.0/cvxpy/expressions/expression.py:613: DeprecationWarning: | |
| This use of ``*`` has resulted in matrix multiplication. | |
| Using ``*`` for matrix multiplication has been deprecated since CVXPY 1.1. | |
| Use ``*`` for matrix-scalar and vector-scalar multiplication. | |
| Use ``@`` for matrix-matrix and matrix-vector multiplication. | |
| Use ``multiply`` for elementwise multiplication. | |
| This code path has been hit 5 times so far. | |
| warnings.warn(msg, DeprecationWarning) | |
| -- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html | |
| [36m[1m=========================== short test summary info ============================[0m | |
| [31mFAILED[0m cvxpy/tests/test_atoms.py::[1mTestAtoms::test_flatten[0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_complex.py::[1mTestComplex::test_partial_trace[0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_complex.py::[1mTestComplex::test_partial_transpose[0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_constant_atoms.py::[1mtest_constant_atoms[atom_info1-Minimize][0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_constant_atoms.py::[1mtest_constant_atoms[atom_info2-Minimize][0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_constant_atoms.py::[1mtest_constant_atoms[atom_info5-Minimize][0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_constant_atoms.py::[1mtest_constant_atoms[atom_info6-Minimize][0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_constant_atoms.py::[1mtest_constant_atoms[atom_info19-Minimize][0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_constant_atoms.py::[1mtest_constant_atoms[atom_info20-Minimize][0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_constant_atoms.py::[1mtest_constant_atoms[atom_info21-Minimize][0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_constant_atoms.py::[1mtest_constant_atoms[atom_info22-Minimize][0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_constant_atoms.py::[1mtest_constant_atoms[atom_info23-Minimize][0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_constant_atoms.py::[1mtest_constant_atoms[atom_info24-Minimize][0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_constant_atoms.py::[1mtest_constant_atoms[atom_info68-Minimize][0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_constant_atoms.py::[1mtest_constant_atoms[atom_info80-Minimize][0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_constant_atoms.py::[1mtest_constant_atoms[atom_info81-Minimize][0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_constant_atoms.py::[1mtest_constant_atoms[atom_info82-Minimize][0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_constant_atoms.py::[1mtest_constant_atoms[atom_info87-Minimize][0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_constant_atoms.py::[1mtest_constant_atoms[atom_info88-Minimize][0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_constant_atoms.py::[1mtest_constant_atoms[atom_info94-Minimize][0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_constant_atoms.py::[1mtest_constant_atoms[atom_info95-Minimize][0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_constant_atoms.py::[1mtest_constant_atoms[atom_info96-Minimize][0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_constant_atoms.py::[1mtest_constant_atoms[atom_info97-Minimize][0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_constant_atoms.py::[1mtest_constant_atoms[atom_info98-Minimize][0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_constant_atoms.py::[1mtest_constant_atoms[atom_info99-Minimize][0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_constant_atoms.py::[1mtest_constant_atoms[atom_info100-Minimize][0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_constant_atoms.py::[1mtest_constant_atoms[atom_info101-Minimize][0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_constant_atoms.py::[1mtest_constant_atoms[atom_info113-Maximize][0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_constant_atoms.py::[1mtest_constant_atoms[atom_info114-Maximize][0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_constant_atoms.py::[1mtest_constant_atoms[atom_info115-Maximize][0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_constant_atoms.py::[1mtest_constant_atoms[atom_info116-Maximize][0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_constant_atoms.py::[1mtest_constant_atoms[atom_info117-Maximize][0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_constant_atoms.py::[1mtest_constant_atoms[atom_info118-Maximize][0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_constant_atoms.py::[1mtest_constant_atoms[atom_info119-Maximize][0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_constant_atoms.py::[1mtest_constant_atoms[atom_info120-Maximize][0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_convolution.py::[1mTestConvolution::test_conv_prob[0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_dgp2dcp.py::[1mTestDgp2Dcp::test_basic_equality_constraint[0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_dgp2dcp.py::[1mTestDgp2Dcp::test_geo_mean[0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_dgp2dcp.py::[1mTestDgp2Dcp::test_gmatmul[0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_dgp2dcp.py::[1mTestDgp2Dcp::test_parameter[0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_dgp2dcp.py::[1mTestDgp2Dcp::test_solving_non_dcp_problem_raises_error[0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_dgp2dcp.py::[1mTestDgp2Dcp::test_solving_non_dgp_problem_raises_error[0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_dgp2dcp.py::[1mTestDgp2Dcp::test_unconstrained_monomial[0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_dqcp.py::[1mTestDqcp::test_length[0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_examples.py::[1mTestExamples::test_intro[0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_problem.py::[1mTestProblem::test_cumsum_axis[0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_problem.py::[1mTestProblem::test_ecos_noineq[0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_problem.py::[1mTestProblem::test_mult_by_zero[0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31mFAILED[0m cvxpy/tests/test_problem.py::[1mTestProblem::test_rmul_param[0m - AttributeError: module 'numpy' has no attribute 'int'. | |
| [31m= [31m[1m49 failed[0m, [32m899 passed[0m, [33m236 skipped[0m, [33m7 deselected[0m, [33m247 warnings[0m[31m in 11332.40s (3:08:52)[0m[31m =[0m | |
| +00 +2e-01 2e-01 5e-02 1e+00 5e-02 0.7833 5e-02 1 1 1 | 2 1 | |
| 3 +5.146e+00 +6.202e+00 +4e-02 1e-01 2e-02 1e+00 1e-02 0.7833 5e-02 1 1 1 | 2 1 | |
| 4 +6.500e+00 +6.962e+00 +9e-03 4e-02 8e-03 4e-01 3e-03 0.7833 5e-02 1 1 1 | 2 1 | |
| 5 +7.109e+00 +7.251e+00 +3e-03 2e-02 3e-03 1e-01 8e-04 0.9791 3e-01 2 1 1 | 5 0 | |
| 6 +7.314e+00 +7.349e+00 +7e-04 5e-03 8e-04 3e-02 2e-04 0.7833 1e-02 1 1 1 | 1 1 | |
| 7 +7.373e+00 +7.383e+00 +1e-04 1e-03 2e-04 9e-03 4e-05 0.7833 9e-03 2 1 1 | 1 1 | |
| 8 +7.385e+00 +7.387e+00 +4e-05 2e-04 4e-05 2e-03 1e-05 0.7777 1e-02 1 0 1 | 1 1 | |
| 9 +7.388e+00 +7.389e+00 +7e-06 6e-05 1e-05 5e-04 2e-06 0.7833 9e-03 2 0 0 | 1 1 | |
| 10 +7.389e+00 +7.389e+00 +2e-06 1e-05 2e-06 1e-04 5e-07 0.7729 1e-02 1 0 0 | 1 1 | |
| 11 +7.389e+00 +7.389e+00 +4e-07 3e-06 6e-07 2e-05 1e-07 0.7833 9e-03 1 0 0 | 1 1 | |
| 12 +7.389e+00 +7.389e+00 +1e-07 7e-07 1e-07 5e-06 3e-08 0.7814 1e-02 1 0 0 | 1 1 | |
| 13 +7.389e+00 +7.389e+00 +2e-08 2e-07 3e-08 1e-06 6e-09 0.7833 5e-02 1 0 0 | 2 1 | |
| 14 +7.389e+00 +7.389e+00 +6e-09 4e-08 7e-09 3e-07 1e-09 0.7833 1e-04 0 0 0 | 0 1 | |
| 15 +7.389e+00 +7.389e+00 +1e-09 9e-09 2e-09 6e-08 3e-10 0.7833 9e-03 1 0 0 | 1 1 | |
| OPTIMAL (within feastol=8.9e-09, reltol=1.7e-10, abstol=1.2e-09). | |
| Runtime: 0.000067 seconds. | |
| /nix/store/pw17yc3mwmsci4jygwalj8ppg0drz31v-stdenv-linux/setup: line 1593: pop_var_context: head of shell_variables not a function context |
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