expand¶

tripy.expand(input: Tensor, sizes: Sequence[int | DimensionSize]) → Tensor[source]¶

Returns a new tensor based on the input tensor with singleton dimensions expanded to a larger size.

Parameters:

input (Tensor) – [dtype=T1] The input tensor.
sizes (Sequence[int | DimensionSize]) – The desired expanded size. A value of \(-1\) indicates that the dimension should not be modified. If the length of this parameter exceeds the rank of the tensor, new dimensions are prepended.

Returns:

[dtype=T1] The new tensor.

Return type:

Tensor

TYPE CONSTRAINTS:

T1: bool, float8, bfloat16, float16, float32, int8, int32, int64

Example

Example¶

input = tp.iota((2, 1), dtype=tp.float32)
output = tp.expand(input, (-1, 4))

>>> input
tensor(
    [[0.0000],
     [1.0000]], 
    dtype=float32, loc=gpu:0, shape=(2, 1))
>>> output
tensor(
    [[0.0000, 0.0000, 0.0000, 0.0000],
     [1.0000, 1.0000, 1.0000, 1.0000]], 
    dtype=float32, loc=gpu:0, shape=(2, 4))

Example: Increasing Tensor Rank

Increasing Tensor Rank¶

input = tp.iota((1, 1), dtype=tp.float32)
output = tp.expand(input, (3, -1, -1))

>>> input
tensor([[0.0000]], dtype=float32, loc=gpu:0, shape=(1, 1))
>>> output
tensor(
    [[[0.0000]],

     [[0.0000]],

     [[0.0000]]], 
    dtype=float32, loc=gpu:0, shape=(3, 1, 1))