src/transformers/models/deberta_v2/modeling_tf_deberta_v2.py/TFDebertaV2ConvLayer/__init__
class TFDebertaV2ConvLayer:    def __init__(self, config: DebertaV2Config, **kwargs):
        super().__init__(**kwargs)

        self.kernel_size = getattr(config, "conv_kernel_size", 3)
        # groups = getattr(config, "conv_groups", 1)
        self.conv_act = get_tf_activation(getattr(config, "conv_act", "tanh"))
        self.padding = (self.kernel_size - 1) // 2
        self.LayerNorm = tf.keras.layers.LayerNormalization(epsilon=config.layer_norm_eps, name="LayerNorm")
        self.dropout = TFDebertaV2StableDropout(config.hidden_dropout_prob, name="dropout")
        self.config = config