W3cubDocs

/TensorFlow 2.4

tf.broadcast_dynamic_shape

Computes the shape of a broadcast given symbolic shapes.

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.

© 2020 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/versions/r2.4/api_docs/python/tf/broadcast_dynamic_shape