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pytorch-image-models/timm/models/layers/conv_bn_act.py

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1.1 KiB

""" Conv2d + BN + Act
Hacked together by Ross Wightman
"""
from torch import nn as nn
from timm.models.layers import get_padding
class ConvBnAct(nn.Module):
def __init__(self, in_channels, out_channels, kernel_size=1, stride=1, dilation=1, groups=1,
drop_block=None, act_layer=nn.ReLU, norm_layer=nn.BatchNorm2d):
super(ConvBnAct, self).__init__()
padding = get_padding(kernel_size, stride, dilation) # assuming PyTorch style padding for this block
self.conv = nn.Conv2d(
in_channels, out_channels=out_channels, kernel_size=kernel_size, stride=stride,
padding=padding, dilation=dilation, groups=groups, bias=False)
self.bn = norm_layer(out_channels)
self.drop_block = drop_block
if act_layer is not None:
self.act = act_layer(inplace=True)
else:
self.act = None
def forward(self, x):
x = self.conv(x)
x = self.bn(x)
if self.drop_block is not None:
x = self.drop_block(x)
if self.act is not None:
x = self.act(x)
return x