from collections import OrderedDict
from typing import Mapping

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


SCREAMING_SNAKE_CASE__		:					Any						=					logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__		:					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       snake_case					(      UpperCamelCase_						):
		lowercase_			=     'xlm'
		lowercase_			=     {
		    'hidden_size': 'emb_dim',
		    'num_attention_heads': 'n_heads',
		    'num_hidden_layers': 'n_layers',
		    'n_words': 'vocab_size',  # For backward compatibility
		}




		def __init__(      self     :	List[Any]     , a_     :	Tuple=3_0145     , a_     :	Union[str, Any]=2048     , a_     :	int=12     , a_     :	List[Any]=16     , a_     :	str=0.1     , a_     :	Union[str, Any]=0.1     , a_     :	Optional[int]=True     , a_     :	Dict=False     , a_     :	Optional[Any]=False     , a_     :	Optional[Any]=False     , a_     :	List[Any]=1     , a_     :	int=True     , a_     :	Dict=512     , a_     :	List[str]=2048**-0.5     , a_     :	Tuple=1e-1_2     , a_     :	Optional[int]=0.02     , a_     :	Any=0     , a_     :	Optional[int]=1     , a_     :	Union[str, Any]=2     , a_     :	List[Any]=3     , a_     :	List[str]=5     , a_     :	Optional[int]=True     , a_     :	List[str]="first"     , a_     :	int=True     , a_     :	Union[str, Any]=None     , a_     :	Optional[int]=True     , a_     :	Tuple=0.1     , a_     :	Any=5     , a_     :	List[str]=5     , a_     :	List[str]=0     , a_     :	Any=0     , a_     :	Dict=2     , a_     :	List[Any]=0     , **a_     :	Optional[int]     , )->       Optional[Any]:




							"""simple docstring"""
							SCREAMING_SNAKE_CASE__				:				List[Any]			=		vocab_size
							SCREAMING_SNAKE_CASE__				:				Optional[int]			=		emb_dim
							SCREAMING_SNAKE_CASE__				:				Dict			=		n_layers
							SCREAMING_SNAKE_CASE__				:				Any			=		n_heads
							SCREAMING_SNAKE_CASE__				:				int			=		dropout
							SCREAMING_SNAKE_CASE__				:				Optional[Any]			=		attention_dropout
							SCREAMING_SNAKE_CASE__				:				Any			=		gelu_activation
							SCREAMING_SNAKE_CASE__				:				List[Any]			=		sinusoidal_embeddings
							SCREAMING_SNAKE_CASE__				:				List[Any]			=		causal
							SCREAMING_SNAKE_CASE__				:				Union[str, Any]			=		asm
							SCREAMING_SNAKE_CASE__				:				int			=		n_langs
							SCREAMING_SNAKE_CASE__				:				Any			=		use_lang_emb
							SCREAMING_SNAKE_CASE__				:				int			=		layer_norm_eps
							SCREAMING_SNAKE_CASE__				:				str			=		bos_index
							SCREAMING_SNAKE_CASE__				:				Tuple			=		eos_index
							SCREAMING_SNAKE_CASE__				:				str			=		pad_index
							SCREAMING_SNAKE_CASE__				:				Union[str, Any]			=		unk_index
							SCREAMING_SNAKE_CASE__				:				str			=		mask_index
							SCREAMING_SNAKE_CASE__				:				Dict			=		is_encoder
							SCREAMING_SNAKE_CASE__				:				str			=		max_position_embeddings
							SCREAMING_SNAKE_CASE__				:				Dict			=		embed_init_std
							SCREAMING_SNAKE_CASE__				:				List[str]			=		init_std
							SCREAMING_SNAKE_CASE__				:				Dict			=		summary_type
							SCREAMING_SNAKE_CASE__				:				Optional[Any]			=		summary_use_proj
							SCREAMING_SNAKE_CASE__				:				Optional[Any]			=		summary_activation
							SCREAMING_SNAKE_CASE__				:				str			=		summary_proj_to_labels
							SCREAMING_SNAKE_CASE__				:				Optional[Any]			=		summary_first_dropout
							SCREAMING_SNAKE_CASE__				:				Tuple			=		start_n_top
							SCREAMING_SNAKE_CASE__				:				Tuple			=		end_n_top
							SCREAMING_SNAKE_CASE__				:				List[Any]			=		mask_token_id
							SCREAMING_SNAKE_CASE__				:				Optional[Any]			=		lang_id

							if "n_words" in kwargs:
												SCREAMING_SNAKE_CASE__				:				str			=		kwargs['n_words']

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




class       snake_case					(      UpperCamelCase_						):




		@property
		def 	__lowercase(      self     :	List[Any]				)->       Mapping[str, Mapping[int, str]]:




							"""simple docstring"""
							if self.task == "multiple-choice":
												SCREAMING_SNAKE_CASE__				:				int			=		{0: 'batch', 1: 'choice', 2: 'sequence'}
							else:
												SCREAMING_SNAKE_CASE__				:				Optional[Any]			=		{0: 'batch', 1: 'sequence'}
							return OrderedDict(
							    [
							        ('input_ids', dynamic_axis),
							        ('attention_mask', dynamic_axis),
							        ('token_type_ids', dynamic_axis),
							    ]				)




from packaging import version

from .import_utils import is_accelerate_available


if is_accelerate_available():
      import accelerate







def     _a				(      lowercase__  :			List[str] ):







     '''simple docstring'''


     if not is_accelerate_available():
          return method
     SCREAMING_SNAKE_CASE__				:				str			=		version.parse(accelerate.__version__ ).base_version
     if version.parse(lowercase__ ) < version.parse('0.17.0' ):
          return method

     def wrapper(self  :			Optional[int]     ,  *lowercase__  :			int     ,  **lowercase__  :			Tuple ):
          if hasattr(self     ,  '_hf_hook' ) and hasattr(self._hf_hook     ,  'pre_forward' ):
               self._hf_hook.pre_forward(self )
          return method(self     ,  *lowercase__     ,  **lowercase__ )

     return wrapper



