src/transformers/models/resnet/modeling_resnet.py/ResNetConvLayer/__init__
class ResNetConvLayer:    def __init__(
        self, in_channels: int, out_channels: int, kernel_size: int = 3, stride: int = 1, activation: str = "relu"
    ):
        super().__init__()
        self.convolution = nn.Conv2d(
            in_channels, out_channels, kernel_size=kernel_size, stride=stride, padding=kernel_size // 2, bias=False
        )
        self.normalization = nn.BatchNorm2d(out_channels)
        self.activation = ACT2FN[activation] if activation is not None else nn.Identity()