def __init__()

in parler_tts/modeling_parler_tts.py [0:0]

• 39 lines of code
• 3 McCabe index (conditional complexity)

    def __init__(self, config: ParlerTTSDecoderConfig, layer_idx: int = None):
        super().__init__()
        self.embed_dim = config.hidden_size

        self.self_attn = PARLERTTS_ATTENTION_CLASSES[config._attn_implementation](
            embed_dim=self.embed_dim,
            num_heads=config.num_attention_heads,
            num_key_value_heads=config.num_key_value_heads,
            dropout=config.attention_dropout,
            is_decoder=True,
            is_causal=True,
            bias=False,
            rope_embeddings=config.rope_embeddings,
            layer_idx=layer_idx,
            config=config,
        )
        self.dropout = config.dropout
        self.activation_fn = ACT2FN[config.activation_function]
        self.activation_dropout = config.activation_dropout

        self.self_attn_layer_norm = nn.LayerNorm(self.embed_dim)
        cross_attn_implementation = config._attn_implementation
        if config.cross_attention_implementation_strategy == "always_eager":
            cross_attn_implementation = "eager"
        elif config.cross_attention_implementation_strategy == "always_sdpa":
            cross_attn_implementation = "sdpa"
        self.encoder_attn = PARLERTTS_ATTENTION_CLASSES[cross_attn_implementation](
            self.embed_dim,
            config.num_attention_heads,
            num_key_value_heads=config.num_cross_attention_key_value_heads,
            dropout=config.attention_dropout,
            is_decoder=True,
            bias=False,
            rope_embeddings=config.rope_embeddings,
            layer_idx=layer_idx,
            config=config,
        )
        self.encoder_attn_layer_norm = nn.LayerNorm(self.embed_dim)
        self.fc1 = nn.Linear(self.embed_dim, config.ffn_dim, bias=False)
        self.fc2 = nn.Linear(config.ffn_dim, self.embed_dim, bias=False)
        self.final_layer_norm = nn.LayerNorm(self.embed_dim)