def _create_none_optionals(func_graph, template_tensors):
"""Creates none optionals in func_graph to represent template_tensors.
Args:
func_graph: FuncGraph.
template_tensors: a list of tensors in func_graph.
Returns:
A list of tensors in func_graph.
"""
with func_graph.as_default():
return [gen_dataset_ops.optional_none() for _ in template_tensors]
def _create_none_optionals(func_graph, n):
"""Creates `n` `None` optionals in func_graph.
Args:
func_graph: FuncGraph.
n: `int` the number of `None` optionals to make.
Returns:
A list of tensors in func_graph.
"""
with func_graph.as_default():
return [gen_dataset_ops.optional_none() for _ in range(n)]
def _create_none_optionals(func_graph, template_tensors):
"""Creates none optionals in func_graph to represent template_tensors.
Args:
func_graph: FuncGraph.
template_tensors: a list of tensors in func_graph.
Returns:
A list of tensors in func_graph.
"""
with func_graph.as_default():
return [gen_dataset_ops.optional_none() for _ in template_tensors]
def none_from_structure(value_structure):
"""Returns an `Optional` that has no value.
NOTE: This method takes an argument that defines the structure of the value
that would be contained in the returned `Optional` if it had a value.
Args:
value_structure: A `Structure` object representing the structure of the
components of this optional.
Returns:
An `Optional` that has no value.
"""
return _OptionalImpl(gen_dataset_ops.optional_none(), value_structure)
def none_from_structure(value_structure):
"""Returns an `Optional` that has no value.
NOTE: This method takes an argument that defines the structure of the value
that would be contained in the returned `Optional` if it had a value.
Args:
value_structure: A `Structure` object representing the structure of the
components of this optional.
Returns:
An `Optional` that has no value.
"""
return _OptionalImpl(gen_dataset_ops.optional_none(), value_structure)
def none_from_structure(output_shapes, output_types, output_classes):
"""Returns an `Optional` that has no value.
NOTE: This method takes arguments that define the structure of the value
that would be contained in the returned `Optional` if it had a value.
Args:
output_shapes: A nested structure of `tf.TensorShape` objects
corresponding to each component of this optional.
output_types: A nested structure of `tf.DType` objects corresponding to
each component of this optional.
output_classes: A nested structure of Python `type` objects corresponding
to each component of this optional.
Returns:
An `Optional` that has no value.
"""
return _OptionalImpl(gen_dataset_ops.optional_none(), output_shapes,
output_types, output_classes)
def empty(element_spec):
"""Returns an `Optional` that has no value.
NOTE: This method takes an argument that defines the structure of the value
that would be contained in the returned `Optional` if it had a value.
>>> optional = tf.experimental.Optional.empty(
... tf.TensorSpec(shape=(), dtype=tf.int32, name=None))
>>> print(optional.has_value())
tf.Tensor(False, shape=(), dtype=bool)
Args:
element_spec: A (nested) structure of `tf.TypeSpec` objects matching the
structure of an element of this optional.
Returns:
A `tf.experimental.Optional` with no value.
"""
return _OptionalImpl(gen_dataset_ops.optional_none(), element_spec)
def none_from_structure(output_shapes, output_types, output_classes):
"""Returns an `Optional` that has no value.
NOTE: This method takes arguments that define the structure of the value
that would be contained in the returned `Optional` if it had a value.
Args:
output_shapes: A nested structure of `tf.TensorShape` objects
corresponding to each component of this optional.
output_types: A nested structure of `tf.DType` objects corresponding to
each component of this optional.
output_classes: A nested structure of Python `type` objects corresponding
to each component of this optional.
Returns:
An `Optional` that has no value.
"""
return _OptionalImpl(gen_dataset_ops.optional_none(), output_shapes,
output_types, output_classes)
