src/transformers/models/regnet/modeling_tf_regnet.py/TFRegNetShortCut/__init__
class TFRegNetShortCut:    def __init__(self, out_channels: int, stride: int = 2, **kwargs):
        super().__init__(**kwargs)
        self.convolution = tf.keras.layers.Conv2D(
            filters=out_channels, kernel_size=1, strides=stride, use_bias=False, name="convolution"
        )
        self.normalization = tf.keras.layers.BatchNormalization(epsilon=1e-5, momentum=0.9, name="normalization")