src/transformers/models/speecht5/modeling_speecht5.py/SpeechT5Encoder/__init__
class SpeechT5Encoder:    def __init__(self, config: SpeechT5Config):
        super().__init__(config)
        self.layer_norm = nn.LayerNorm(config.hidden_size, eps=config.layer_norm_eps)
        self.dropout = nn.Dropout(config.hidden_dropout)
        self.layerdrop = config.encoder_layerdrop

        self.layers = nn.ModuleList([SpeechT5EncoderLayer(config) for _ in range(config.encoder_layers)])

        self.embed_positions = SpeechT5RelativePositionalEncoding(
            config.hidden_size // config.encoder_attention_heads, config.encoder_max_relative_position
        )

        self.gradient_checkpointing = False

        # Initialize weights and apply final processing
        self.post_init()