tf.broadcast_dynamic_shape
| View source on GitHub | 
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