mindspore.ops.BroadcastTo

class mindspore.ops.BroadcastTo(shape)[source]

Broadcasts input tensor to a given shape.

Input shape can be broadcast to target shape if for each dimension pair they are either equal or input is one or the target dimension is -1. In case of -1 in target shape, it will be replaced by the input shape’s value in that dimension.

When input shape is broadcast to target shape, it starts with the trailing dimensions. If there is a -1 in the target shape, the -1 cannot be in a leading, non-existing dimension.

Parameters: shape (tuple) – The target shape to broadcast. Can be fully specified, or have -1 in one position where it will be substituted by the input tensor’s shape in that position, see example.

Inputs:

input_x (Tensor) - The input tensor. The data type should be one of the following types: float16, float32, int32, int8, uint8, bool. The shape is \((N,*)\) where \(*\) means,any number of additional dimensions.

Outputs:

Tensor, with the given shape and the same data type as input_x.

Raises

TypeError – If shape is not a tuple.
ValueError – if the target and input shapes are incompatible, or if a - 1 in the target shape is in an invalid location.

Supported Platforms:: Ascend GPU CPU

Examples

>>> shape = (2, 3)
>>> input_x = Tensor(np.array([1, 2, 3]).astype(np.float32))
>>> broadcast_to = ops.BroadcastTo(shape)
>>> output = broadcast_to(input_x)
>>> print(output)
[[1. 2. 3.]
 [1. 2. 3.]]

>>> shape = (-1, 2)
>>> input_x = Tensor(np.array([[1], [2]]).astype(np.float32))
>>> broadcast_to = ops.BroadcastTo(shape)
>>> output = broadcast_to(input_x)
>>> print(output)
[[1. 1.]
 [2. 2.]]