A TensorShape represents a possibly-partial shape specification for a
Tensor. It may be one of the following:
Fully-known shape: has a known number of dimensions and a known size
for each dimension. e.g. TensorShape([16, 256])
Partially-known shape: has a known number of dimensions, and an unknown
size for one or more dimension. e.g. TensorShape([None, 256])
Unknown shape: has an unknown number of dimensions, and an unknown
size in all dimensions. e.g. TensorShape(None)
If a tensor is produced by an operation of type "Foo", its shape
may be inferred if there is a registered shape function for
"Foo". See Shape
functions
for details of shape functions and how to register them. Alternatively,
the shape may be set explicitly using tf.Tensor.set_shape.
Args
dims
A list of Dimensions, or None if the shape is unspecified.
Raises
TypeError
If dims cannot be converted to a list of dimensions.
Attributes
dims
Deprecated. Returns list of dimensions for this shape.
Two possibly-partially-defined shapes are compatible if there
exists a fully-defined shape that both shapes can represent. Thus,
compatibility allows the shape inference code to reason about
partially-defined shapes. For example:
TensorShape(None) is compatible with all shapes.
TensorShape([None, None]) is compatible with all two-dimensional
shapes, such as TensorShape([32, 784]), and also TensorShape(None). It is
not compatible with, for example, TensorShape([None]) or
TensorShape([None, None, None]).
TensorShape([32, None]) is compatible with all two-dimensional shapes
with size 32 in the 0th dimension, and also TensorShape([None, None])
and TensorShape(None). It is not compatible with, for example,
TensorShape([32]), TensorShape([32, None, 1]) or TensorShape([64, None]).
TensorShape([32, 784]) is compatible with itself, and also
TensorShape([32, None]), TensorShape([None, 784]), TensorShape([None,
None]) and TensorShape(None). It is not compatible with, for example,
TensorShape([32, 1, 784]) or TensorShape([None]).
The compatibility relation is reflexive and symmetric, but not
transitive. For example, TensorShape([32, 784]) is compatible with
TensorShape(None), and TensorShape(None) is compatible with
TensorShape([4, 4]), but TensorShape([32, 784]) is not compatible with
TensorShape([4, 4]).
Returns the most specific TensorShape compatible with self and other.
TensorShape([None, 1]) is the most specific TensorShape compatible with
both TensorShape([2, 1]) and TensorShape([5, 1]). Note that
TensorShape(None) is also compatible with above mentioned TensorShapes.
TensorShape([1, 2, 3]) is the most specific TensorShape compatible with
both TensorShape([1, 2, 3]) and TensorShape([1, 2, 3]). There are more
less specific TensorShapes compatible with above mentioned TensorShapes,
e.g. TensorShape([1, 2, None]), TensorShape(None).
Args
other
Another TensorShape.
Returns
A TensorShape which is the most specific compatible shape of self
and other.
TensorFlow 1 version
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