tf.broadcast_dynamic

TensorFlow 1 version

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Computes the shape of a broadcast given symbolic shapes.

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See Migration guide for more details.

tf.compat.v1.broadcast_dynamic_shape

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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tf / broadcast_dynamic_shape

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Example:

Args

Returns

Raises