TensorSpec
Defined in tensorflow/python/framework/tensor_spec.py
.
Describes a tf.Tensor.
A TensorSpec allows an API to describe the Tensors that it accepts or returns, before that Tensor exists. This allows dynamic and flexible graph construction and configuration.
dtype
Returns the dtype
of elements in the tensor.
is_continuous
Whether spec is continuous.
is_discrete
Whether spec is discrete.
name
Returns the name of the described tensor.
shape
Returns the TensorShape
that represents the shape of the tensor.
__init__
__init__( shape, dtype, name=None )
Creates a TensorSpec.
shape
: Value convertible to tf.TensorShape
. The shape of the tensor.dtype
: Value convertible to tf.DType
. The type of the tensor values.name
: Optional name for the Tensor.TypeError
: If shape is not convertible to a tf.TensorShape
, or dtype is not convertible to a tf.DType
.__eq__
__eq__(other)
Return self==value.
__ne__
__ne__(other)
Return self!=value.
__reduce__
__reduce__()
helper for pickle
from_spec
@classmethod from_spec( cls, spec, name=None )
from_tensor
@classmethod from_tensor( cls, tensor, name=None )
is_bounded
@classmethod is_bounded(cls)
is_compatible_with
is_compatible_with(spec_or_tensor)
True if the shape and dtype of spec_or_tensor
are compatible.
© 2018 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/contrib/framework/TensorSpec