pad

nvtripy.pad(input: Tensor, pad: Sequence[Sequence[int | DimensionSize]], mode: str = 'constant', value: int | float = 0) → Tensor[source]

Pads the input tensor.

Parameters:

  • input (Tensor) – The input tensor.

  • pad (Sequence[Sequence[int | DimensionSize]]) – A sequence of padding sizes of each dimension. Its length must be equal to the rank of input. Each element of pad is a tuple of integers or DimensionSize s (low, high), which represents the padding sizes before the lowest index and after the highest index at the corresponding dimension.

  • mode (str) – The padding mode. Only “constant” is supported.

  • value (int | float) – The padding value for “constant” mode.

Returns:

The padded tensor.

Return type:

Tensor

Example: Constant padding.
1input = tp.reshape(tp.arange(6, dtype=tp.float32), (2, 3))
2output = tp.pad(input, ((1, 0), (0, 1)))
Local Variables
>>> input
tensor(
    [[0.0000, 1.0000, 2.0000],
     [3.0000, 4.0000, 5.0000]], 
    dtype=float32, loc=gpu:0, shape=(2, 3))

>>> output
tensor(
    [[0.0000, 0.0000, 0.0000, 0.0000],
     [0.0000, 1.0000, 2.0000, 0.0000],
     [3.0000, 4.0000, 5.0000, 0.0000]], 
    dtype=float32, loc=gpu:0, shape=(3, 4))