broadcast_to

paddle. broadcast_to ( x: Tensor, shape: ShapeLike, name: str | None = None ) → Tensor [source]

Broadcast the input tensor to a given shape.

Both the number of dimensions of x and the number of elements in shape should be less than or equal to 6. The dimension to broadcast to must have a value 0.

The following figure shows the process of broadcasting a one-dimensional tensor of shape [3] to a two-dimensional tensor of shape [2,3] based on the shape specified by ‘shape’.

broadcast_to API

Note

Alias Support: The parameter name input can be used as an alias for x, and size can be used as an alias for shape. For example, broadcast_to(input=tensor_x, size=[2, 3], ...) is equivalent to broadcast_to(x=tensor_x, shape=[2, 3], ...).

Parameters

  • x (Tensor) – The input tensor, its data type is bool, float16, float32, float64, int32, int64, uint8 or uint16. alias: input.

  • shape (list|tuple|Tensor) – The result shape after broadcasting. The data type is int32. If shape is a list or tuple, all its elements should be integers or 0-D or 1-D Tensors with the data type int32. If shape is a Tensor, it should be an 1-D Tensor with the data type int32. The value -1 in shape means keeping the corresponding dimension unchanged. alias: size.

  • name (str|None, optional) – Name for the operation (optional, default is None). For more information, please refer to api_guide_Name.

Returns

N-D Tensor, A Tensor with the given shape. The data type is the same as x.

Examples

>>> import paddle

>>> data = paddle.to_tensor([1, 2, 3], dtype='int32')
>>> out = paddle.broadcast_to(data, shape=[2, 3])
>>> print(out)
Tensor(shape=[2, 3], dtype=int32, place=Place(cpu), stop_gradient=True,
[[1, 2, 3],
 [1, 2, 3]])