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- # -*- coding: utf-8 -*-
- # MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
- #
- # Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
- #
- # Unless required by applicable law or agreed to in writing,
- # software distributed under the License is distributed on an
- # "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- from typing import Tuple, Union
-
- from ..functional import sliding_window
- from .module import Module
-
-
- class SlidingWindow(Module):
- r"""
- Apply a sliding window to input tensor and copy content in the window to
- corresponding output location. Assume input shape is :math:`(N, C, IH, IW)`,
- then output shape would be :math:`(N, C, OH, OW, window_h, window_w)` where
- :math:`(OH, OW)` would be computed from padding, stride, window and
- :math:`(IH, IW)`, as in convolution. For each output location, we have;
-
- .. math::
-
- out_{n, c, oh, ow, wh, ww} &= src_{n, c, ih+wh, iw+ww} \\
- \text{where } & ih=-pad_h+oh \times stride_h + (wh-1) \times (dilation_h-1) \\
- & iw=-pad_w+ow \times stride_w + (ww-1) \times (dilation_w-1)
-
-
- :param kernel_size: the size of the window to take a max over.
- :param padding: implicit zero padding to be added on both sides. Default: 0
- :param stride: the stride of the window. Default: 1
- :param dilation: the dilation of the window. Default: 1
-
- Example:
-
- .. testcode::
-
- from megengine import tensor
- import megengine.module as M
- import numpy as np
-
- inp = tensor(np.arange(30).reshape(1,1,5,6))
- op = M.SlidingWindow(kernel_size=3, padding=1, stride=2, dilation=2)
- out = op(inp)
- print(out.numpy())
-
- Outputs:
-
- .. testoutput::
-
- [[[[[[ 0 0 0]
- [ 0 7 9]
- [ 0 19 21]]
-
- [[ 0 0 0]
- [ 7 9 11]
- [19 21 23]]]
-
-
- [[[ 0 7 9]
- [ 0 19 21]
- [ 0 0 0]]
-
- [[ 7 9 11]
- [19 21 23]
- [ 0 0 0]]]]]]
-
- """
-
- def __init__(
- self,
- 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,
- **kwargs
- ):
- super(SlidingWindow, self).__init__(**kwargs)
- self.kernel_size = kernel_size
- self.padding = padding
- self.stride = stride
- self.dilation = dilation
-
- def forward(self, inp):
- return sliding_window(
- inp, self.kernel_size, self.padding, self.stride, self.dilation
- )
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