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January 19, 2020 14:49
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| (tensorflow-env) [ghoshk1@x86_64-conda_cos6-linux-gnu]/scratch/work/ghoshk1/SWAVI_tfp/Linear_Regression_QMC% python plot_K_hat_vs_D_fr_swa.py | |
| 2020-01-17 17:18:42.228790: I tensorflow/core/platform/profile_utils/cpu_utils.cc:101] CPU Frequency: 2793045000 Hz | |
| 2020-01-17 17:18:42.229921: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x561889248eb0 initialized for platform Host (this does not guarantee that XLA will be used). Devices: | |
| 2020-01-17 17:18:42.229970: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version | |
| Traceback (most recent call last): | |
| File "plot_K_hat_vs_D_fr_swa.py", line 148, in <module> | |
| init, max_iterations=1000) | |
| File "/home/ghoshk1/.local/lib/python3.6/site-packages/tensorflow_probability/python/optimizer/lbfgs.py", line 260, in minimize | |
| parallel_iterations=parallel_iterations)[0] | |
| File "/home/ghoshk1/.local/lib/python3.6/site-packages/tensorflow_core/python/util/deprecation.py", line 574, in new_func | |
| return func(*args, **kwargs) | |
| File "/home/ghoshk1/.local/lib/python3.6/site-packages/tensorflow_core/python/ops/control_flow_ops.py", line 2491, in while_loop_v2 | |
| return_same_structure=True) | |
| File "/home/ghoshk1/.local/lib/python3.6/site-packages/tensorflow_core/python/ops/control_flow_ops.py", line 2727, in while_loop | |
| loop_vars = body(*loop_vars) | |
| File "/home/ghoshk1/.local/lib/python3.6/site-packages/tensorflow_probability/python/optimizer/lbfgs.py", line 238, in _body | |
| tolerance, f_relative_tolerance, x_tolerance, stopping_condition) | |
| File "/home/ghoshk1/.local/lib/python3.6/site-packages/tensorflow_probability/python/optimizer/bfgs_utils.py", line 153, in line_search_step | |
| converged=inactive) # No search needed for these. | |
| File "/home/ghoshk1/.local/lib/python3.6/site-packages/tensorflow_probability/python/optimizer/linesearch/hager_zhang.py", line 255, in hager_zhang | |
| threshold_use_approximate_wolfe_condition) | |
| File "/home/ghoshk1/.local/lib/python3.6/site-packages/tensorflow_probability/python/optimizer/linesearch/hager_zhang.py", line 636, in _prepare_args | |
| val_initial = value_and_gradients_function(initial_step_size) | |
| File "/home/ghoshk1/.local/lib/python3.6/site-packages/tensorflow_probability/python/optimizer/bfgs_utils.py", line 248, in _restricted_func | |
| objective_value, gradient = value_and_gradients_function(pt) | |
| File "plot_K_hat_vs_D_fr_swa.py", line 147, in <lambda> | |
| lambda par: qmc_loss.loss_and_gradient(par), | |
| File "/home/ghoshk1/.local/lib/python3.6/site-packages/tensorflow_core/python/eager/def_function.py", line 558, in __call__ | |
| return self._python_function(*args, **kwds) | |
| File "/home/ghoshk1/.local/lib/python3.6/site-packages/tensorflow_core/python/eager/function.py", line 3277, in bound_method_wrapper | |
| return wrapped_fn(weak_instance(), *args, **kwargs) | |
| File "/scratch/work/ghoshk1/SWAVI_tfp/Linear_Regression_QMC/qmcLoss.py", line 75, in loss_and_gradient | |
| return tfp.math.value_and_gradient(lambda par: self.loss(par), par) | |
| File "/home/ghoshk1/.local/lib/python3.6/site-packages/tensorflow_probability/python/math/gradient.py", line 79, in value_and_gradient | |
| y = f(*xs) | |
| File "/scratch/work/ghoshk1/SWAVI_tfp/Linear_Regression_QMC/qmcLoss.py", line 75, in <lambda> | |
| return tfp.math.value_and_gradient(lambda par: self.loss(par), par) | |
| File "/home/ghoshk1/.local/lib/python3.6/site-packages/tensorflow_core/python/eager/def_function.py", line 558, in __call__ | |
| return self._python_function(*args, **kwds) | |
| File "/home/ghoshk1/.local/lib/python3.6/site-packages/tensorflow_core/python/eager/function.py", line 3277, in bound_method_wrapper | |
| return wrapped_fn(weak_instance(), *args, **kwargs) | |
| File "/scratch/work/ghoshk1/SWAVI_tfp/Linear_Regression_QMC/qmcLoss.py", line 69, in loss | |
| discrepancy = discrepancy_fn(target_log_prob - tf.reshape(surrogate.log_prob(q_samples),(-1, 1))) | |
| File "/home/ghoshk1/.local/lib/python3.6/site-packages/tensorflow_probability/python/distributions/distribution.py", line 883, in log_prob | |
| return self._call_log_prob(value, name, **kwargs) | |
| File "/home/ghoshk1/.local/lib/python3.6/site-packages/tensorflow_probability/python/distributions/distribution.py", line 865, in _call_log_prob | |
| return self._log_prob(value, **kwargs) | |
| File "/home/ghoshk1/.local/lib/python3.6/site-packages/tensorflow_probability/python/internal/distribution_util.py", line 1388, in _fn | |
| return fn(*args, **kwargs) | |
| File "/home/ghoshk1/.local/lib/python3.6/site-packages/tensorflow_probability/python/distributions/mvn_linear_operator.py", line 222, in _log_prob | |
| return super(MultivariateNormalLinearOperator, self)._log_prob(x) | |
| File "/home/ghoshk1/.local/lib/python3.6/site-packages/tensorflow_probability/python/distributions/transformed_distribution.py", line 432, in _log_prob | |
| x = self.bijector.inverse(y, **bijector_kwargs) | |
| File "/home/ghoshk1/.local/lib/python3.6/site-packages/tensorflow_probability/python/bijectors/bijector.py", line 1073, in inverse | |
| return self._call_inverse(y, name, **kwargs) | |
| File "/home/ghoshk1/.local/lib/python3.6/site-packages/tensorflow_probability/python/bijectors/bijector.py", line 1045, in _call_inverse | |
| mapping = mapping.merge(x=self._inverse(y, **kwargs)) | |
| File "/home/ghoshk1/.local/lib/python3.6/site-packages/tensorflow_probability/python/bijectors/chain.py", line 236, in _inverse | |
| y = b.inverse(y, **kwargs.get(b.name, {})) | |
| File "/home/ghoshk1/.local/lib/python3.6/site-packages/tensorflow_probability/python/bijectors/bijector.py", line 1073, in inverse | |
| return self._call_inverse(y, name, **kwargs) | |
| File "/home/ghoshk1/.local/lib/python3.6/site-packages/tensorflow_probability/python/bijectors/bijector.py", line 1045, in _call_inverse | |
| mapping = mapping.merge(x=self._inverse(y, **kwargs)) | |
| File "/home/ghoshk1/.local/lib/python3.6/site-packages/tensorflow_probability/python/bijectors/scale_matvec_linear_operator.py", line 115, in _inverse | |
| return self.scale.solvevec(y, adjoint=self.adjoint) | |
| File "/home/ghoshk1/.local/lib/python3.6/site-packages/tensorflow_core/python/ops/linalg/linear_operator.py", line 896, in solvevec | |
| return self._solvevec(rhs, adjoint=adjoint) | |
| File "/home/ghoshk1/.local/lib/python3.6/site-packages/tensorflow_core/python/ops/linalg/linear_operator.py", line 847, in _solvevec | |
| solution_mat = self.solve(rhs_mat, adjoint=adjoint) | |
| File "/home/ghoshk1/.local/lib/python3.6/site-packages/tensorflow_core/python/ops/linalg/linear_operator.py", line 842, in solve | |
| return self._solve(rhs, adjoint=adjoint, adjoint_arg=adjoint_arg) | |
| File "/home/ghoshk1/.local/lib/python3.6/site-packages/tensorflow_core/python/ops/linalg/linear_operator_lower_triangular.py", line 202, in _solve | |
| self._get_tril(), rhs, lower=True, adjoint=adjoint) | |
| File "/home/ghoshk1/.local/lib/python3.6/site-packages/tensorflow_core/python/ops/linalg/linear_operator_util.py", line 429, in matrix_triangular_solve_with_broadcast | |
| adjoint=adjoint and still_need_to_transpose) | |
| File "/home/ghoshk1/.local/lib/python3.6/site-packages/tensorflow_core/python/ops/gen_linalg_ops.py", line 1896, in matrix_triangular_solve | |
| _ops.raise_from_not_ok_status(e, name) | |
| File "/home/ghoshk1/.local/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py", line 6625, in raise_from_not_ok_status | |
| six.raise_from(core._status_to_exception(e.code, message), None) | |
| File "<string>", line 3, in raise_from | |
| tensorflow.python.framework.errors_impl.InvalidArgumentError: Input matrix is not invertible. [Op:MatrixTriangularSolve] | |
| (tensorflow-env) [ghoshk1@x86_64-conda_cos6-linux-gnu]/scratch/work/ghoshk1/SWAVI_tfp/Linear_Regression_QMC% |
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