tf.broadcast_dynamic_shape
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Computes the shape of a broadcast given symbolic shapes.
tf.broadcast_dynamic_shape( shape_x, shape_y )
When shape_x
and shape_y
are Tensors representing shapes (i.e. the result of calling tf.shape on another Tensor) this computes a Tensor which is the shape of the result of a broadcasting op applied in tensors of shapes shape_x
and shape_y
.
This is useful when validating the result of a broadcasting operation when the tensors do not have statically known shapes.
Example:
shape_x = (1, 2, 3) shape_y = (5, 1, 3) tf.broadcast_dynamic_shape(shape_x, shape_y) <tf.Tensor: shape=(3,), dtype=int32, numpy=array([5, 2, 3], ...>
Args | |
---|---|
shape_x | A rank 1 integer Tensor , representing the shape of x. |
shape_y | A rank 1 integer Tensor , representing the shape of y. |
Returns | |
---|---|
A rank 1 integer Tensor representing the broadcasted shape. |
Raises | |
---|---|
InvalidArgumentError | If the two shapes are incompatible for broadcasting. |
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/broadcast_dynamic_shape