395b1fc3df754c21a6b7aebc79a1d950bfdc1efc,pytorch/pytorchcv/models/senet.py,SENet,__init__,#SENet#Any#Any#Any#Any#Any#Any#,203

Before Change

            kernel_size=7,
            stride=1))

        self.output = nn.Sequential()
        self.output.add_module("dropout", nn.Dropout(p=0.2))
        self.output.add_module("fc", nn.Linear(
            in_features=in_channels,
            out_features=num_classes))

After Change

            in_channels=in_channels,
            out_channels=init_block_channels))
        in_channels = init_block_channels
        for i, channels_per_stage in enumerate(channels):
            stage = nn.Sequential()
            identity_conv3x3 = (i != 0)
            for j, out_channels in enumerate(channels_per_stage):
                stride = 2 if (j == 0) and (i != 0) else 1
                stage.add_module("unit{}".format(j + 1), SENetUnit(
                    in_channels=in_channels,
                    out_channels=out_channels,

Instances