src/transformers/models/mctct/configuration_mctct.py/MCTCTConfig/__init__
class MCTCTConfig:    def __init__(
        self,
        vocab_size=8065,
        hidden_size=1536,
        num_hidden_layers=36,
        intermediate_size=6144,
        num_attention_heads=4,
        attention_head_dim=384,
        max_position_embeddings=920,
        layer_norm_eps=1e-5,
        layerdrop=0.3,
        hidden_act="relu",
        initializer_range=0.02,
        hidden_dropout_prob=0.3,
        attention_probs_dropout_prob=0.3,
        pad_token_id=1,
        bos_token_id=0,
        eos_token_id=2,
        conv_glu_dim=1,
        conv_dropout=0.3,
        num_conv_layers=1,
        conv_kernel=(7,),
        conv_stride=(3,),
        input_feat_per_channel=80,
        input_channels=1,
        conv_channels=None,
        ctc_loss_reduction="sum",
        ctc_zero_infinity=False,
        **kwargs,
    ):
        super().__init__(**kwargs, pad_token_id=pad_token_id, bos_token_id=bos_token_id, eos_token_id=eos_token_id)
        self.vocab_size = vocab_size
        self.hidden_size = hidden_size
        self.num_hidden_layers = num_hidden_layers
        self.intermediate_size = intermediate_size
        self.num_attention_heads = num_attention_heads
        self.attention_head_dim = attention_head_dim
        self.max_position_embeddings = max_position_embeddings
        self.layer_norm_eps = layer_norm_eps
        self.layerdrop = layerdrop
        self.hidden_act = hidden_act
        self.initializer_range = initializer_range
        self.hidden_dropout_prob = hidden_dropout_prob
        self.attention_probs_dropout_prob = attention_probs_dropout_prob
        self.pad_token_id = pad_token_id
        self.bos_token_id = bos_token_id
        self.eos_token_id = eos_token_id
        self.conv_glu_dim = conv_glu_dim
        self.conv_dropout = conv_dropout
        self.num_conv_layers = num_conv_layers
        self.input_feat_per_channel = input_feat_per_channel
        self.input_channels = input_channels
        self.conv_channels = conv_channels
        self.ctc_loss_reduction = ctc_loss_reduction
        self.ctc_zero_infinity = ctc_zero_infinity

        # prevents config testing fail with exporting to json
        self.conv_kernel = list(conv_kernel)
        self.conv_stride = list(conv_stride)

        if len(self.conv_kernel) != self.num_conv_layers:
            raise ValueError(
                "Configuration for convolutional module is incorrect. "
                "It is required that `len(config.conv_kernel)` == `config.num_conv_layers` "
                f"but is `len(config.conv_kernel) = {len(self.conv_kernel)}`, "
                f"`config.num_conv_layers = {self.num_conv_layers}`."
            )