src/transformers/models/led/modeling_tf_led.py/TFLEDDecoder/__init__
class TFLEDDecoder:    def __init__(self, config: LEDConfig, embed_tokens: Optional[TFSharedEmbeddings] = None, **kwargs):
        super().__init__(**kwargs)
        self.config = config
        self.padding_idx = config.pad_token_id
        self.embed_tokens = embed_tokens
        self.layerdrop = config.decoder_layerdrop
        self.embed_positions = TFLEDLearnedPositionalEmbedding(
            config.max_decoder_position_embeddings,
            config.d_model,
            name="embed_positions",
        )
        self.layers = [TFLEDDecoderLayer(config, name=f"layers.{i}") for i in range(config.decoder_layers)]
        self.layernorm_embedding = tf.keras.layers.LayerNormalization(epsilon=1e-5, name="layernorm_embedding")

        self.dropout = tf.keras.layers.Dropout(config.dropout)