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 with_same_shape(old, new):
"""Check and set new tensor's shape."""
xla_compile = (os.environ["xla_compile"] == "true")
if not xla_compile:
if isinstance(old, tf.Tensor) and isinstance(new, tf.Tensor):
return tensor_util.with_same_shape(old, new)
return new
def with_same_shape(old, new):
"""Check and set new tensor's shape."""
if isinstance(old, tf.Tensor) and isinstance(new, tf.Tensor):
return tensor_util.with_same_shape(old, new)
return new
def assert_state_is_compatible(expected_state, state):
"""Asserts that states are compatible.
Args:
expected_state: The reference state.
state: The state that must be compatible with :obj:`expected_state`.
Raises:
ValueError: if the states are incompatible.
"""
# Check structure compatibility.
nest.assert_same_structure(expected_state, state)
# Check shape compatibility.
expected_state_flat = nest.flatten(expected_state)
state_flat = nest.flatten(state)
for x, y in zip(expected_state_flat, state_flat):
if tensor_util.is_tensor(x):
with_same_shape(x, y)
def with_same_shape(old, new):
"""Check and set new tensor's shape."""
if isinstance(old, ops.Tensor) and isinstance(new, ops.Tensor):
if not context.executing_eagerly():
return tensor_util.with_same_shape(old, new)
else:
if old.shape.as_list() != new.shape.as_list():
raise ValueError(
"The shape of the AttentionWrapperState is "
"expected to be same as the one to clone. "
"self.shape: %s, input.shape: %s" %
(old.shape, new.shape))
return new
return new
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 with_same_shape(old, new):
"""Check and set new tensor's shape."""
if isinstance(old, tf.Tensor) and isinstance(new, tf.Tensor):
return tensor_util.with_same_shape(old, new)
return new
