src/transformers/models/xlm/configuration_xlm.py/XLMConfig/__init__
class XLMConfig:    def __init__(
        self,
        vocab_size=30145,
        emb_dim=2048,
        n_layers=12,
        n_heads=16,
        dropout=0.1,
        attention_dropout=0.1,
        gelu_activation=True,
        sinusoidal_embeddings=False,
        causal=False,
        asm=False,
        n_langs=1,
        use_lang_emb=True,
        max_position_embeddings=512,
        embed_init_std=2048**-0.5,
        layer_norm_eps=1e-12,
        init_std=0.02,
        bos_index=0,
        eos_index=1,
        pad_index=2,
        unk_index=3,
        mask_index=5,
        is_encoder=True,
        summary_type="first",
        summary_use_proj=True,
        summary_activation=None,
        summary_proj_to_labels=True,
        summary_first_dropout=0.1,
        start_n_top=5,
        end_n_top=5,
        mask_token_id=0,
        lang_id=0,
        pad_token_id=2,
        bos_token_id=0,
        **kwargs,
    ):
        """Constructs XLMConfig."""
        self.vocab_size = vocab_size
        self.emb_dim = emb_dim
        self.n_layers = n_layers
        self.n_heads = n_heads
        self.dropout = dropout
        self.attention_dropout = attention_dropout
        self.gelu_activation = gelu_activation
        self.sinusoidal_embeddings = sinusoidal_embeddings
        self.causal = causal
        self.asm = asm
        self.n_langs = n_langs
        self.use_lang_emb = use_lang_emb
        self.layer_norm_eps = layer_norm_eps
        self.bos_index = bos_index
        self.eos_index = eos_index
        self.pad_index = pad_index
        self.unk_index = unk_index
        self.mask_index = mask_index
        self.is_encoder = is_encoder
        self.max_position_embeddings = max_position_embeddings
        self.embed_init_std = embed_init_std
        self.init_std = init_std
        self.summary_type = summary_type
        self.summary_use_proj = summary_use_proj
        self.summary_activation = summary_activation
        self.summary_proj_to_labels = summary_proj_to_labels
        self.summary_first_dropout = summary_first_dropout
        self.start_n_top = start_n_top
        self.end_n_top = end_n_top
        self.mask_token_id = mask_token_id
        self.lang_id = lang_id

        if "n_words" in kwargs:
            self.n_words = kwargs["n_words"]

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