






'''simple docstring'''



from argparse import ArgumentParser

from . import BaseTransformersCLICommand



def    __UpperCAmelCase	(				SCREAMING_SNAKE_CASE__:	Any    )  ->			List[Any]:

   """simple docstring"""
   return DownloadCommand(args.model,					args.cache_dir,					args.force,					args.trust_remote_code    )



class 							__SCREAMING_SNAKE_CASE       (							lowercase_     ):




      @staticmethod
      def  __UpperCamelCase							(  lowerCamelCase      )							->int:



         '''simple docstring'''
         __a				     =    parser.add_parser('download'      )
         download_parser.add_argument(
             '--cache-dir' ,   type=lowerCamelCase ,   default=lowerCamelCase ,   help='Path to location to store the models'      )
         download_parser.add_argument(
             '--force' ,   action='store_true' ,   help='Force the model to be download even if already in cache-dir'      )
         download_parser.add_argument(
             '--trust-remote-code' ,   action='store_true' ,   help='Whether or not to allow for custom models defined on the Hub in their own modeling files. Use only if you\'ve reviewed the code as it will execute on your local machine' ,   )
         download_parser.add_argument('model' ,   type=lowerCamelCase ,   help='Name of the model to download'      )
         download_parser.set_defaults(func=lowerCamelCase      )




      def __init__(  self ,   lowerCamelCase ,   lowerCamelCase ,   lowerCamelCase ,   lowerCamelCase      )							->Dict:



         '''simple docstring'''
         __a				     =    model
         __a				     =    cache
         __a				     =    force
         __a				     =    trust_remote_code






      def  __UpperCamelCase							(  self      )							->Dict:



         '''simple docstring'''
         from ..models.auto import AutoModel, AutoTokenizer

         AutoModel.from_pretrained(
             self._model ,   cache_dir=self._cache ,   force_download=self._force ,   trust_remote_code=self._trust_remote_code      )
         AutoTokenizer.from_pretrained(
             self._model ,   cache_dir=self._cache ,   force_download=self._force ,   trust_remote_code=self._trust_remote_code      )








'''simple docstring'''



from collections import OrderedDict
from typing import Mapping

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


__UpperCamelCase      :       Dict      			=      logging.get_logger(__name__)

__UpperCamelCase      :       Optional[int]      			=      {
    """facebook/xmod-base""": """https://huggingface.co/facebook/xmod-base/resolve/main/config.json""",
    """facebook/xmod-large-prenorm""": """https://huggingface.co/facebook/xmod-large-prenorm/resolve/main/config.json""",
    """facebook/xmod-base-13-125k""": """https://huggingface.co/facebook/xmod-base-13-125k/resolve/main/config.json""",
    """facebook/xmod-base-30-125k""": """https://huggingface.co/facebook/xmod-base-30-125k/resolve/main/config.json""",
    """facebook/xmod-base-30-195k""": """https://huggingface.co/facebook/xmod-base-30-195k/resolve/main/config.json""",
    """facebook/xmod-base-60-125k""": """https://huggingface.co/facebook/xmod-base-60-125k/resolve/main/config.json""",
    """facebook/xmod-base-60-265k""": """https://huggingface.co/facebook/xmod-base-60-265k/resolve/main/config.json""",
    """facebook/xmod-base-75-125k""": """https://huggingface.co/facebook/xmod-base-75-125k/resolve/main/config.json""",
    """facebook/xmod-base-75-269k""": """https://huggingface.co/facebook/xmod-base-75-269k/resolve/main/config.json""",
}
class 							__SCREAMING_SNAKE_CASE       (							_lowerCAmelCase     ):
      __a  					="xmod"




      def __init__(  self ,   lowerCamelCase=3_0522 ,   lowerCamelCase=768 ,   lowerCamelCase=12 ,   lowerCamelCase=12 ,   lowerCamelCase=3072 ,   lowerCamelCase="gelu" ,   lowerCamelCase=0.1 ,   lowerCamelCase=0.1 ,   lowerCamelCase=512 ,   lowerCamelCase=2 ,   lowerCamelCase=0.02 ,   lowerCamelCase=1e-12 ,   lowerCamelCase=1 ,   lowerCamelCase=0 ,   lowerCamelCase=2 ,   lowerCamelCase="absolute" ,   lowerCamelCase=True ,   lowerCamelCase=None ,   lowerCamelCase=False ,   lowerCamelCase=2 ,   lowerCamelCase=False ,   lowerCamelCase=True ,   lowerCamelCase=True ,   lowerCamelCase=("en_XX",) ,   lowerCamelCase=None ,   **lowerCamelCase ,   )							->Any:



         '''simple docstring'''
         super().__init__(pad_token_id=lowerCamelCase ,   bos_token_id=lowerCamelCase ,   eos_token_id=lowerCamelCase ,   **lowerCamelCase      )

         __a				     =    vocab_size
         __a				     =    hidden_size
         __a				     =    num_hidden_layers
         __a				     =    num_attention_heads
         __a				     =    hidden_act
         __a				     =    intermediate_size
         __a				     =    hidden_dropout_prob
         __a				     =    attention_probs_dropout_prob
         __a				     =    max_position_embeddings
         __a				     =    type_vocab_size
         __a				     =    initializer_range
         __a				     =    layer_norm_eps
         __a				     =    position_embedding_type
         __a				     =    use_cache
         __a				     =    classifier_dropout
         __a				     =    pre_norm
         __a				     =    adapter_reduction_factor
         __a				     =    adapter_layer_norm
         __a				     =    adapter_reuse_layer_norm
         __a				     =    ln_before_adapter
         __a				     =    list(lowerCamelCase      )
         __a				     =    default_language







class 							__SCREAMING_SNAKE_CASE       (							_lowerCAmelCase     ):




      @property
      def  __UpperCamelCase							(  self      )							->Mapping[str, Mapping[int, str]]:



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