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