b2074ddf9d8bc2069d66976fea58a52f40238496,pretrainedmodels/nasnet.py,ReductionCell0,__init__,#ReductionCell0#Any#Any#Any#Any#,278

Before Change

        self.comb_iter_3_left = nn.AvgPool2d(3, stride=1, padding=1)

        self.comb_iter_4_left = TwoSeparables(out_channels_right, out_channels_right, 3, 1, 1, bias=False)
        self.comb_iter_4_right = nn.MaxPool2d(3, stride=2, padding=1)

    def forward(self, x_left, x_right):
        x_left = F.relu(x_left)
        x_left = self.conv_left(x_left)

After Change

        self.conv_prev_1x1 = nn.Sequential()
        self.conv_prev_1x1.add_module("relu", nn.ReLU())
        self.conv_prev_1x1.add_module("conv", nn.Conv2d(in_channels_left, out_channels_left, 1, stride=1, bias=False))
        self.conv_prev_1x1.add_module("bn", nn.BatchNorm2d(out_channels_left, eps=0.001, momentum=0.1, affine=True))

        self.conv_1x1 = nn.Sequential()
        self.conv_1x1.add_module("relu", nn.ReLU())
        self.conv_1x1.add_module("conv", nn.Conv2d(in_channels_right, out_channels_right, 1, stride=1, bias=False))

Instances