ResNet ResidualBlock AttributeError: 'expansion' - Fixing the Error

This error, 'AttributeError: type object 'ResidualBlock' has no attribute 'expansion'', arises when attempting to access the 'expansion' attribute within the ResidualBlock class, which is not defined in the current implementation. The 'expansion' attribute is commonly used in ResNet architectures to adjust the number of output channels in the residual block based on the stride value.

To resolve this, you need to add the 'expansion' attribute to your ResidualBlock class and assign it the desired value, typically 1 for stride=1 and 2 for stride=2. This attribute can then be used to adjust the output channels in the downsample convolutional layer, if required.

Here's an example of how to modify the ResidualBlock class:

class ResidualBlock(nn.Cell):
    def __init__(self, in_channels, out_channels, stride=1, downsample=None):
        super(ResidualBlock, self).__init__()
        self.conv1 = nn.Conv2d(in_channels, out_channels, kernel_size=3, stride=stride,   pad_mode='valid')
        self.bn1 = nn.BatchNorm2d(out_channels)
        self.relu = nn.ReLU()
        self.conv2 = nn.Conv2d(out_channels, out_channels, kernel_size=3, stride=1,   pad_mode='valid')
        self.bn2 = nn.BatchNorm2d(out_channels)
        self.downsample = downsample
        self.stride = stride
        # Add the 'expansion' attribute
        self.expansion = 1 if stride == 1 else 2

    # ... rest of the code remains the same

By incorporating the 'expansion' attribute, your ResidualBlock class will be compatible with ResNet architectures that expect this attribute. This simple modification will eliminate the 'AttributeError' and allow your code to run smoothly.