88f5086454759b4e213013cb1bc177df183b43b2,gluoncv/model_zoo/resnetv1b.py,BottleneckV1b,__init__,#BottleneckV1b#Any#Any#Any#Any#Any#Any#Any#Any#,58

Before Change

            in_channels=planes, channels=planes, kernel_size=3, strides=strides,
            padding=dilation, dilation=dilation, use_bias=False)
        self.bn2 = norm_layer(in_channels=planes)
        self.conv3 = nn.Conv2D(
            in_channels=planes, channels=planes * 4, kernel_size=1, use_bias=False)
        if not last_gamma:
            self.bn3 = nn.BatchNorm(in_channels=planes * 4)
        else:
            self.bn3 = nn.BatchNorm(in_channels=planes * 4, gamma_initializer="zeros")
        self.relu = nn.Activation("relu")
        self.downsample = downsample
        self.dilation = dilation
        self.strides = strides

    def hybrid_forward(self, F, x):
        residual = x

After Change

                               padding=dilation, dilation=dilation, use_bias=False)
        self.bn1 = norm_layer(in_channels=planes, use_global_stats=use_global_stats)
        self.relu = nn.Activation("relu")
        self.conv2 = nn.Conv2D(in_channels=planes, channels=planes, kernel_size=3, strides=1,
                               padding=previous_dilation, dilation=previous_dilation,
                               use_bias=False)
        self.bn2 = norm_layer(in_channels=planes, use_global_stats=use_global_stats)
        self.downsample = downsample
        self.strides = strides

Instances