src/transformers/models/speech_to_text_2/configuration_speech_to_text_2.py/Speech2Text2Config/__init__
class Speech2Text2Config:    def __init__(
        self,
        vocab_size=10000,
        decoder_layers=6,
        decoder_ffn_dim=2048,
        decoder_attention_heads=4,
        decoder_layerdrop=0.0,
        use_cache=True,
        activation_function="relu",
        d_model=256,
        dropout=0.1,
        attention_dropout=0.0,
        activation_dropout=0.0,
        init_std=0.02,
        decoder_start_token_id=2,
        classifier_dropout=0.0,
        scale_embedding=True,
        gradient_checkpointing=False,
        pad_token_id=1,
        bos_token_id=0,
        eos_token_id=2,
        max_source_positions=6000,
        max_target_positions=1024,
        **kwargs
    ):
        self.vocab_size = vocab_size
        self.d_model = d_model
        self.decoder_ffn_dim = decoder_ffn_dim
        self.decoder_layers = decoder_layers
        self.decoder_attention_heads = decoder_attention_heads
        self.dropout = dropout
        self.attention_dropout = attention_dropout
        self.activation_dropout = activation_dropout
        self.activation_function = activation_function
        self.init_std = init_std
        self.decoder_layerdrop = decoder_layerdrop
        self.classifier_dropout = classifier_dropout
        self.use_cache = use_cache
        self.num_hidden_layers = decoder_layers
        self.gradient_checkpointing = gradient_checkpointing
        self.scale_embedding = scale_embedding  # scale factor will be sqrt(d_model) if True
        self.max_source_positions = max_source_positions
        self.max_target_positions = max_target_positions

        super().__init__(
            pad_token_id=pad_token_id,
            bos_token_id=bos_token_id,
            eos_token_id=eos_token_id,
            decoder_start_token_id=decoder_start_token_id,
            **kwargs,
        )