Type IDType
Namespace tensorflow
Interfaces IPythonObjectContainer
Methods
Properties
Public instance methods
object is_compatible_with(object other)
Returns True iff `self` is compatible with `other`. 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]).
Parameters
-
object
other - Another TensorShape.
Returns
-
object
- True iff `self` is compatible with `other`.