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from cvxpy import * | |
import numpy | |
# 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 = Variable(n) | |
objective = Minimize(sum_squares(A*x - b)) | |
constraints = [0 <= x, x <= 1] | |
prob = Problem(objective, constraints) | |
# The optimal objective is returned by prob.solve(). | |
result = prob.solve("SCS", gpu=True, verbose=True) | |
# 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) |
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