src/transformers/models/speecht5/modeling_speecht5.py/SpeechT5TextDecoderPrenet/__init__
class SpeechT5TextDecoderPrenet:    def __init__(self, config):
        super().__init__()
        self.config = config
        self.dropout = nn.Dropout(config.positional_dropout)
        self.embed_scale = math.sqrt(config.hidden_size) if config.scale_embedding else 1.0

        self.embed_tokens = nn.Embedding(config.vocab_size, config.hidden_size, config.pad_token_id)

        self.embed_positions = SpeechT5SinusoidalPositionalEmbedding(
            config.max_text_positions + config.pad_token_id + 1,
            config.hidden_size,
            config.pad_token_id,
        )