r"""Extracts sliding local blocks from a batched input tensor. Refer to :class:`~.module.sliding_window.SlidingWindow` for more information. Args: inp: input tensor. kernel_size: size of the window. padding: implicit zero padding added on both sides of input. Defaul
(
inp: Tensor,
kernel_size: Union[int, Tuple[int, int]],
padding: Union[int, Tuple[int, int]] = 0,
stride: Union[int, Tuple[int, int]] = 1,
dilation: Union[int, Tuple[int, int]] = 1,
)
| 1721 | |
| 1722 | |
| 1723 | def sliding_window( |
| 1724 | inp: Tensor, |
| 1725 | kernel_size: Union[int, Tuple[int, int]], |
| 1726 | padding: Union[int, Tuple[int, int]] = 0, |
| 1727 | stride: Union[int, Tuple[int, int]] = 1, |
| 1728 | dilation: Union[int, Tuple[int, int]] = 1, |
| 1729 | ) -> Tensor: |
| 1730 | r"""Extracts sliding local blocks from a batched input tensor. |
| 1731 | |
| 1732 | Refer to :class:`~.module.sliding_window.SlidingWindow` for more information. |
| 1733 | |
| 1734 | Args: |
| 1735 | inp: input tensor. |
| 1736 | kernel_size: size of the window. |
| 1737 | padding: implicit zero padding added on both sides of input. Default: 0 |
| 1738 | stride: stride of the window. Default: 1 |
| 1739 | dilation: dilation of the window. Default: 1 |
| 1740 | """ |
| 1741 | padding_h, padding_w = expand_hw(padding) |
| 1742 | stride_h, stride_w = expand_hw(stride) |
| 1743 | dilation_h, dilation_w = expand_hw(dilation) |
| 1744 | window_h, window_w = expand_hw(kernel_size) |
| 1745 | |
| 1746 | op = builtin.Images2Neibs( |
| 1747 | pad_h=padding_h, |
| 1748 | pad_w=padding_w, |
| 1749 | stride_h=stride_h, |
| 1750 | stride_w=stride_w, |
| 1751 | dilate_h=dilation_h, |
| 1752 | dilate_w=dilation_w, |
| 1753 | window_h=window_h, |
| 1754 | window_w=window_w, |
| 1755 | ) |
| 1756 | (output,) = apply(op, inp) |
| 1757 | return output |
| 1758 | |
| 1759 | |
| 1760 | def sliding_window_transpose( |