def _assert_with_shape(self, tensor, expected_value, expected_shape,
unexpected_shapes):
for unexpected_shape in unexpected_shapes:
self.assertRaises(ValueError, tensor_util.with_shape,
unexpected_shape, tensor)
pattern = (
r"\[Wrong shape for %s \[expected\] \[actual\].\] \[%s\] \[%s\]"
%
(tensor.name, " ".join([str(dim) for dim in unexpected_shape]),
" ".join([str(dim) for dim in expected_shape])))
self.assertRaisesRegexp(
errors_impl.OpError, re.compile(pattern),
tensor_util.with_shape(constant_op.constant(unexpected_shape),
tensor).eval)
expected_placeholder = array_ops.placeholder(dtypes.float32)
self.assertRaisesRegexp(
errors_impl.OpError, re.compile(pattern),
tensor_util.with_same_shape(expected_placeholder, tensor).eval,
{expected_placeholder: np.ones(unexpected_shape)})
self.assertIs(tensor, tensor_util.with_shape(expected_shape, tensor))
self.assertIs(
tensor,
tensor_util.with_same_shape(
constant_op.constant(1, shape=expected_shape), tensor))
tensor_with_shape = tensor_util.with_shape(
constant_op.constant(expected_shape), tensor)
np.testing.assert_array_equal(expected_value, tensor_with_shape.eval())
tensor_with_same_shape = tensor_util.with_same_shape(
expected_placeholder, tensor)
np.testing.assert_array_equal(
expected_value,
tensor_with_same_shape.eval(
{expected_placeholder: np.ones(expected_shape)}))
def test_with_shape_partial(self):
with self.test_session():
tensor_partial_shape = array_ops.placeholder(dtypes.float32)
tensor_partial_shape.set_shape([None, 2])
for incompatible_shape in [[0], [1]]:
self.assertRaisesRegexp(
ValueError, r"Shapes \(\?, 2\) and \([01],\) are not compatible",
tensor_util.with_shape, incompatible_shape, tensor_partial_shape)
for incompatible_shape in [[1, 2, 1]]:
self.assertRaisesRegexp(ValueError, "Dimensions must be equal",
tensor_util.with_shape, incompatible_shape,
tensor_partial_shape)
for incompatible_shape in [[2, 1]]:
self.assertRaisesRegexp(
ValueError, r"Shapes \(\?, 2\) and \(2, 1\) are not compatible",
tensor_util.with_shape, incompatible_shape, tensor_partial_shape)
compatible_shape = [2, 2]
with_present_2x2 = tensor_util.with_shape(compatible_shape,
tensor_partial_shape)
self.assertEquals(compatible_shape, with_present_2x2.get_shape().dims)
with_future_2x2 = tensor_util.with_shape(
constant_op.constant(compatible_shape), tensor_partial_shape)
array_2x2 = [[42.0, 43.0], [44.0, 45.0]]
for tensor_2x2 in [with_present_2x2, with_future_2x2]:
np.testing.assert_array_equal(array_2x2,
tensor_2x2.eval({
tensor_partial_shape: array_2x2
}))
self.assertRaises(ValueError, tensor_2x2.eval,
{tensor_partial_shape: [42.0, 43.0]})
self.assertRaises(ValueError, tensor_2x2.eval,
{tensor_partial_shape: [42.0]})
def test_with_shape_partial(self):
with self.test_session():
tensor_partial_shape = array_ops.placeholder(dtypes.float32)
tensor_partial_shape.set_shape([None, 2])
for incompatible_shape in [[0], [1]]:
if ops._USE_C_API:
error_message = "Shapes must be equal rank, but are 2 and 1"
else:
error_message = r"Shapes \(\?, 2\) and \([01],\) are not compatible"
self.assertRaisesRegexp(ValueError, error_message,
tensor_util.with_shape,
incompatible_shape,
tensor_partial_shape)
for incompatible_shape in [[1, 2, 1]]:
self.assertRaisesRegexp(ValueError, "Dimensions must be equal",
tensor_util.with_shape,
incompatible_shape,
tensor_partial_shape)
for incompatible_shape in [[2, 1]]:
if ops._USE_C_API:
error_message = (
r"Dimension 1 in both shapes must be equal, but are "
r"2 and 1. Shapes are \[\?,2\] and \[2,1\].")
else:
error_message = r"Shapes \(\?, 2\) and \(2, 1\) are not compatible"
self.assertRaisesRegexp(ValueError, error_message,
tensor_util.with_shape,
incompatible_shape,
tensor_partial_shape)
compatible_shape = [2, 2]
with_present_2x2 = tensor_util.with_shape(compatible_shape,
tensor_partial_shape)
self.assertEquals(compatible_shape,
with_present_2x2.get_shape().dims)
with_future_2x2 = tensor_util.with_shape(
constant_op.constant(compatible_shape), tensor_partial_shape)
array_2x2 = [[42.0, 43.0], [44.0, 45.0]]
for tensor_2x2 in [with_present_2x2, with_future_2x2]:
np.testing.assert_array_equal(
array_2x2,
tensor_2x2.eval({tensor_partial_shape: array_2x2}))
self.assertRaises(ValueError, tensor_2x2.eval,
{tensor_partial_shape: [42.0, 43.0]})
self.assertRaises(ValueError, tensor_2x2.eval,
{tensor_partial_shape: [42.0]})
def test_with_shape_2x2_with_partial_expected_shape(self):
with self.cached_session():
value = [[42, 43], [44, 45]]
actual_shape = [2, 2]
tensor = constant_op.constant(value, shape=actual_shape)
partial_expected_shape = tensor_shape.TensorShape([None, 2])
# Won't raise any exception here:
tensor_with_shape = tensor_util.with_shape(partial_expected_shape, tensor)
np.testing.assert_array_equal(value, tensor_with_shape.eval())
def test_with_shape_2x2_with_partial_expected_shape(self):
with self.test_session():
value = [[42, 43], [44, 45]]
actual_shape = [2, 2]
tensor = constant_op.constant(value, shape=actual_shape)
partial_expected_shape = tensor_shape.TensorShape([None, 2])
# Won't raise any exception here:
tensor_with_shape = tensor_util.with_shape(partial_expected_shape, tensor)
np.testing.assert_array_equal(value, tensor_with_shape.eval())
def test_with_shape_none(self):
with self.test_session():
tensor_no_shape = array_ops.placeholder(dtypes.float32)
compatible_shape = [2, 2]
with_present_2x2 = tensor_util.with_shape(compatible_shape,
tensor_no_shape)
self.assertEquals(compatible_shape, with_present_2x2.get_shape().dims)
with_future_2x2 = tensor_util.with_shape(
constant_op.constant(compatible_shape), tensor_no_shape)
array_2x2 = [[42.0, 43.0], [44.0, 45.0]]
for tensor_2x2 in [with_present_2x2, with_future_2x2]:
np.testing.assert_array_equal(array_2x2,
tensor_2x2.eval({
tensor_no_shape: array_2x2
}))
self.assertRaisesRegexp(errors_impl.OpError, "Wrong shape",
tensor_2x2.eval,
{tensor_no_shape: [42.0, 43.0]})
self.assertRaisesRegexp(errors_impl.OpError, "Wrong shape",
tensor_2x2.eval, {tensor_no_shape: [42.0]})
def _assert_with_shape(self, tensor, expected_value, expected_shape,
unexpected_shapes):
for unexpected_shape in unexpected_shapes:
self.assertRaises(ValueError, tensor_util.with_shape, unexpected_shape,
tensor)
pattern = (
r"\[Wrong shape for %s \[expected\] \[actual\].\] \[%s\] \[%s\]" %
(tensor.name, " ".join([str(dim) for dim in unexpected_shape]),
" ".join([str(dim) for dim in expected_shape])))
self.assertRaisesRegexp(errors_impl.OpError,
re.compile(pattern),
tensor_util.with_shape(
constant_op.constant(unexpected_shape),
tensor).eval)
expected_placeholder = array_ops.placeholder(dtypes.float32)
self.assertRaisesRegexp(errors_impl.OpError,
re.compile(pattern),
tensor_util.with_same_shape(expected_placeholder,
tensor).eval,
{expected_placeholder: np.ones(unexpected_shape)})
self.assertIs(tensor, tensor_util.with_shape(expected_shape, tensor))
self.assertIs(
tensor,
tensor_util.with_same_shape(
constant_op.constant(
1, shape=expected_shape), tensor))
tensor_with_shape = tensor_util.with_shape(
constant_op.constant(expected_shape), tensor)
np.testing.assert_array_equal(expected_value, tensor_with_shape.eval())
tensor_with_same_shape = tensor_util.with_same_shape(expected_placeholder,
tensor)
np.testing.assert_array_equal(expected_value,
tensor_with_same_shape.eval({
expected_placeholder:
np.ones(expected_shape)
}))
