def test_matrix_inverse_solve():
if not imported_scipy:
pytest.skip("Scipy needed for the Solve op.")
A = theano.tensor.dmatrix("A")
b = theano.tensor.dmatrix("b")
node = matrix_inverse(A).dot(b).owner
[out] = inv_as_solve.transform(node)
assert isinstance(out.owner.op, Solve)
def test_matrix_inverse_solve():
if not imported_scipy:
raise SkipTest("Scipy needed for the Solve op.")
A = theano.tensor.dmatrix('A')
b = theano.tensor.dmatrix('b')
node = matrix_inverse(A).dot(b).owner
[out] = inv_as_solve.transform(node)
assert isinstance(out.owner.op, Solve)
def test_matrix_inverse_as_solve_right():
if not imported_scipy:
raise SkipTest("Scipy needed for the Solve op.")
A = theano.tensor.dmatrix('A')
B = theano.tensor.dmatrix('B')
node = B.dot(matrix_inverse(A)).owner
[out] = inv_as_solve.transform(node)
# take into account the transpose after the solve operation, so go up one
# in expression tree
assert isinstance(out.owner.inputs[0].owner.op, Solve)
def test_matrix_inverse_solve():
A = theano.tensor.dmatrix('A')
b = theano.tensor.dmatrix('b')
node = matrix_inverse(A).dot(b).owner
[out] = inv_as_solve.transform(node)
assert isinstance(out.owner.op, Solve)
def test_matrix_inverse_solve():
A = theano.tensor.dmatrix('A')
b = theano.tensor.dmatrix('b')
node = matrix_inverse(A).dot(b).owner
[out] = inv_as_solve.transform(node)
assert isinstance(out.owner.op, Solve)
