From 7c51070cdbf93157c8b03f6728165820f2ebf972 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Zheng=20Hui=20=28=E6=83=A0=E6=94=BF=29?= Date: Sun, 27 Sep 2020 17:24:13 +0800 Subject: [PATCH] Update block.py --- model/block.py | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/model/block.py b/model/block.py index 87993ec..86feb77 100644 --- a/model/block.py +++ b/model/block.py @@ -3,9 +3,9 @@ import torch -def conv_layer(in_channels, out_channels, kernel_size, stride=1, dilation=1, groups=1): +def conv_layer(in_channels, out_channels, kernel_size, stride=1, dilation=1, groups=1, bias=True): padding = int((kernel_size - 1) / 2) * dilation - return nn.Conv2d(in_channels, out_channels, kernel_size, stride, padding=padding, bias=True, dilation=dilation, + return nn.Conv2d(in_channels, out_channels, kernel_size, stride, padding=padding, bias=bias, dilation=dilation, groups=groups) @@ -175,14 +175,14 @@ def __init__(self, in_channels, distillation_rate=1/4): super(IMDModule_Large, self).__init__() self.distilled_channels = int(in_channels * distillation_rate) # 6 self.remaining_channels = int(in_channels - self.distilled_channels) # 18 - self.c1 = conv_layer(in_channels, in_channels, 3) # 24 --> 24 - self.c2 = conv_layer(self.remaining_channels, in_channels, 3) # 18 --> 24 - self.c3 = conv_layer(self.remaining_channels, in_channels, 3) # 18 --> 24 - self.c4 = conv_layer(self.remaining_channels, self.remaining_channels, 3) # 15 --> 15 - self.c5 = conv_layer(self.remaining_channels-self.distilled_channels, self.remaining_channels-self.distilled_channels, 3) # 10 --> 10 - self.c6 = conv_layer(self.distilled_channels, self.distilled_channels, 3) # 5 --> 5 + self.c1 = conv_layer(in_channels, in_channels, 3, bias=False) # 24 --> 24 + self.c2 = conv_layer(self.remaining_channels, in_channels, 3, bias=False) # 18 --> 24 + self.c3 = conv_layer(self.remaining_channels, in_channels, 3, bias=False) # 18 --> 24 + self.c4 = conv_layer(self.remaining_channels, self.remaining_channels, 3, bias=False) # 15 --> 15 + self.c5 = conv_layer(self.remaining_channels-self.distilled_channels, self.remaining_channels-self.distilled_channels, 3, bias=False) # 10 --> 10 + self.c6 = conv_layer(self.distilled_channels, self.distilled_channels, 3, bias=False) # 5 --> 5 self.act = activation('relu') - self.c7 = conv_layer(self.distilled_channels * 6, in_channels, 1) + self.c7 = conv_layer(self.distilled_channels * 6, in_channels, 1, bias=False) def forward(self, input): out_c1 = self.act(self.c1(input)) # 24 --> 24