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# Copyright (c) OpenMMLab. All rights reserved. | |
import torch.nn as nn | |
from mmcv.cnn import PLUGIN_LAYERS | |
class Maxpool2d(nn.Module): | |
"""A wrapper around nn.Maxpool2d(). | |
Args: | |
kernel_size (int or tuple(int)): Kernel size for max pooling layer | |
stride (int or tuple(int)): Stride for max pooling layer | |
padding (int or tuple(int)): Padding for pooling layer | |
""" | |
def __init__(self, kernel_size, stride, padding=0, **kwargs): | |
super(Maxpool2d, self).__init__() | |
self.model = nn.MaxPool2d(kernel_size, stride, padding) | |
def forward(self, x): | |
""" | |
Args: | |
x (Tensor): Input feature map | |
Returns: | |
Tensor: The tensor after Maxpooling layer. | |
""" | |
return self.model(x) | |