def test_incompatible_dimensions_raise(self):
with self.test_session():
x = ops.convert_to_tensor(rng.rand(2, 4, 4))
operator = DomainDimensionStubOperator(3)
with self.assertRaisesOpError("Incompatible matrix dimensions"):
linear_operator_util.assert_compatible_matrix_dimensions(
operator, x).run()
def test_incompatible_dimensions_raise(self):
with self.test_session():
x = ops.convert_to_tensor(rng.rand(2, 4, 4))
operator = DomainDimensionStubOperator(3)
with self.assertRaisesOpError("Incompatible matrix dimensions"):
linear_operator_util.assert_compatible_matrix_dimensions(
operator, x).run()
def test_compatible_dimensions_do_not_raise(self):
with self.test_session():
x = ops.convert_to_tensor(rng.rand(2, 3, 4))
operator = DomainDimensionStubOperator(3)
# Should not raise
linear_operator_util.assert_compatible_matrix_dimensions(
operator, x).run()
def test_compatible_dimensions_do_not_raise(self):
with self.test_session():
x = ops.convert_to_tensor(rng.rand(2, 3, 4))
operator = DomainDimensionStubOperator(3)
# Should not raise
linear_operator_util.assert_compatible_matrix_dimensions(
operator, x).run()
def _apply(self, x, adjoint=False):
# Note that adjoint has no effect since this matrix is self-adjoint.
if self._assert_proper_shapes:
aps = linear_operator_util.assert_compatible_matrix_dimensions(
self, x)
x = control_flow_ops.with_dependencies([aps], x)
return self._possibly_broadcast_batch_shape(x)
def _apply(self, x, adjoint=False):
# Note that adjoint has no effect since this matrix is self-adjoint.
if self._assert_proper_shapes:
aps = linear_operator_util.assert_compatible_matrix_dimensions(
self, x)
x = control_flow_ops.with_dependencies([aps], x)
return self._possibly_broadcast_batch_shape(x)
def _solve(self, rhs, adjoint=False):
if adjoint:
matrix = self._multiplier_matrix_conj
else:
matrix = self._multiplier_matrix
if self._assert_proper_shapes:
aps = linear_operator_util.assert_compatible_matrix_dimensions(
self, rhs)
rhs = control_flow_ops.with_dependencies([aps], rhs)
return rhs / matrix
def _matmul(self, x, adjoint=False, adjoint_arg=False):
x = linear_operator_util.matrix_adjoint(x) if adjoint_arg else x
if adjoint:
matrix = self._multiplier_matrix_conj
else:
matrix = self._multiplier_matrix
if self._assert_proper_shapes:
aps = linear_operator_util.assert_compatible_matrix_dimensions(self, x)
x = control_flow_ops.with_dependencies([aps], x)
return x * matrix
def _solve(self, rhs, adjoint=False):
if adjoint:
matrix = self._multiplier_matrix_conj
else:
matrix = self._multiplier_matrix
if self._assert_proper_shapes:
aps = linear_operator_util.assert_compatible_matrix_dimensions(
self, rhs)
rhs = control_flow_ops.with_dependencies([aps], rhs)
return rhs / matrix
def _matmul(self, x, adjoint=False, adjoint_arg=False):
x = linear_operator_util.matrix_adjoint(x) if adjoint_arg else x
if adjoint:
matrix = self._multiplier_matrix_conj
else:
matrix = self._multiplier_matrix
if self._assert_proper_shapes:
aps = linear_operator_util.assert_compatible_matrix_dimensions(
self, x)
x = control_flow_ops.with_dependencies([aps], x)
return x * matrix
