import warnings

from .generation import TFGenerationMixin

class 					_lowercase    (     UpperCAmelCase__			):






    '''simple docstring'''
    # warning at import time
    warnings.warn(
        'Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will '
        'be removed in Transformers v5. Import as `from transformers import TFGenerationMixin` instead.' ,  UpperCAmelCase__ ,  )
from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


a  :      Tuple            =    logging.get_logger(__name__)

a  :      List[str]            =    {
    """xlm-mlm-en-2048""": """https://huggingface.co/xlm-mlm-en-2048/resolve/main/config.json""",
    """xlm-mlm-ende-1024""": """https://huggingface.co/xlm-mlm-ende-1024/resolve/main/config.json""",
    """xlm-mlm-enfr-1024""": """https://huggingface.co/xlm-mlm-enfr-1024/resolve/main/config.json""",
    """xlm-mlm-enro-1024""": """https://huggingface.co/xlm-mlm-enro-1024/resolve/main/config.json""",
    """xlm-mlm-tlm-xnli15-1024""": """https://huggingface.co/xlm-mlm-tlm-xnli15-1024/resolve/main/config.json""",
    """xlm-mlm-xnli15-1024""": """https://huggingface.co/xlm-mlm-xnli15-1024/resolve/main/config.json""",
    """xlm-clm-enfr-1024""": """https://huggingface.co/xlm-clm-enfr-1024/resolve/main/config.json""",
    """xlm-clm-ende-1024""": """https://huggingface.co/xlm-clm-ende-1024/resolve/main/config.json""",
    """xlm-mlm-17-1280""": """https://huggingface.co/xlm-mlm-17-1280/resolve/main/config.json""",
    """xlm-mlm-100-1280""": """https://huggingface.co/xlm-mlm-100-1280/resolve/main/config.json""",
}

class 					_lowercase    (     UpperCAmelCase__			):






    '''simple docstring'''
    SCREAMING_SNAKE_CASE:				Any          =    'xlm'
    SCREAMING_SNAKE_CASE:				Optional[int]          =    {
        'hidden_size': 'emb_dim',
        'num_attention_heads': 'n_heads',
        'num_hidden_layers': 'n_layers',
        'n_words': 'vocab_size',  # For backward compatibility
    }




    def __init__(    self       ,						lowerCamelCase__=30_145       ,						lowerCamelCase__=2_048       ,						lowerCamelCase__=12       ,						lowerCamelCase__=16       ,						lowerCamelCase__=0.1       ,						lowerCamelCase__=0.1       ,						lowerCamelCase__=True       ,						lowerCamelCase__=False       ,						lowerCamelCase__=False       ,						lowerCamelCase__=False       ,						lowerCamelCase__=1       ,						lowerCamelCase__=True       ,						lowerCamelCase__=512       ,						lowerCamelCase__=2_048**-0.5       ,						lowerCamelCase__=1E-12       ,						lowerCamelCase__=0.0_2       ,						lowerCamelCase__=0       ,						lowerCamelCase__=1       ,						lowerCamelCase__=2       ,						lowerCamelCase__=3       ,						lowerCamelCase__=5       ,						lowerCamelCase__=True       ,						lowerCamelCase__="first"       ,						lowerCamelCase__=True       ,						lowerCamelCase__=None       ,						lowerCamelCase__=True       ,						lowerCamelCase__=0.1       ,						lowerCamelCase__=5       ,						lowerCamelCase__=5       ,						lowerCamelCase__=0       ,						lowerCamelCase__=0       ,						lowerCamelCase__=2       ,						lowerCamelCase__=0       ,						**lowerCamelCase__       ,						):
       lowerCAmelCase_:							Any       =	vocab_size
       lowerCAmelCase_:							int       =	emb_dim
       lowerCAmelCase_:							int       =	n_layers
       lowerCAmelCase_:							Optional[int]       =	n_heads
       lowerCAmelCase_:							Tuple       =	dropout
       lowerCAmelCase_:							Tuple       =	attention_dropout
       lowerCAmelCase_:							Tuple       =	gelu_activation
       lowerCAmelCase_:							Dict       =	sinusoidal_embeddings
       lowerCAmelCase_:							str       =	causal
       lowerCAmelCase_:							Tuple       =	asm
       lowerCAmelCase_:							Any       =	n_langs
       lowerCAmelCase_:							int       =	use_lang_emb
       lowerCAmelCase_:							Dict       =	layer_norm_eps
       lowerCAmelCase_:							Dict       =	bos_index
       lowerCAmelCase_:							Union[str, Any]       =	eos_index
       lowerCAmelCase_:							Optional[Any]       =	pad_index
       lowerCAmelCase_:							List[Any]       =	unk_index
       lowerCAmelCase_:							Dict       =	mask_index
       lowerCAmelCase_:							Any       =	is_encoder
       lowerCAmelCase_:							Dict       =	max_position_embeddings
       lowerCAmelCase_:							int       =	embed_init_std
       lowerCAmelCase_:							Optional[int]       =	init_std
       lowerCAmelCase_:							str       =	summary_type
       lowerCAmelCase_:							Union[str, Any]       =	summary_use_proj
       lowerCAmelCase_:							Dict       =	summary_activation
       lowerCAmelCase_:							List[Any]       =	summary_proj_to_labels
       lowerCAmelCase_:							List[str]       =	summary_first_dropout
       lowerCAmelCase_:							List[str]       =	start_n_top
       lowerCAmelCase_:							List[Any]       =	end_n_top
       lowerCAmelCase_:							Any       =	mask_token_id
       lowerCAmelCase_:							List[Any]       =	lang_id

       if "n_words" in kwargs:
          lowerCAmelCase_:							Union[str, Any]       =	kwargs["n_words"]

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





class 					_lowercase    (     UpperCAmelCase__			):






    '''simple docstring'''




    @property
    def      _a    (    self ):
       if self.task == "multiple-choice":
          lowerCAmelCase_:							Optional[Any]       =	{0: "batch", 1: "choice", 2: "sequence"}
       else:
          lowerCAmelCase_:							Any       =	{0: "batch", 1: "sequence"}
       return OrderedDict(
           [
               ("input_ids", dynamic_axis),
               ("attention_mask", dynamic_axis),
               ("token_type_ids", dynamic_axis),
           ] )