




'''simple docstring'''



from argparse import ArgumentParser

from . import BaseTransformersCLICommand
def 			SCREAMING_SNAKE_CASE_			(							__A    :			Any  )			->			Optional[int]:
   return DownloadCommand(args.model	,					args.cache_dir	,					args.force	,					args.trust_remote_code  )







class 		lowercase_   (			__lowerCAmelCase       ):


   """simple docstring"""

   @staticmethod
   def 							lowerCAmelCase_      (   __lowerCamelCase :     ArgumentParser   ):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE	=				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 :     Any  ,				__lowerCamelCase :     str  ,				__lowerCamelCase :     str  ,				__lowerCamelCase :     bool  ,				__lowerCamelCase :     bool   ):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE	=				model
      _SCREAMING_SNAKE_CASE	=				cache
      _SCREAMING_SNAKE_CASE	=				force
      _SCREAMING_SNAKE_CASE	=				trust_remote_code



   def 							lowerCAmelCase_      (   self :     Union[str, Any]   ):

      """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 typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


lowerCamelCase_			=						{
    'configuration_layoutlmv2': ['LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LayoutLMv2Config'],
    'processing_layoutlmv2': ['LayoutLMv2Processor'],
    'tokenization_layoutlmv2': ['LayoutLMv2Tokenizer'],
}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCamelCase_			=						['LayoutLMv2TokenizerFast']

try:
 if not is_vision_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCamelCase_			=						['LayoutLMv2FeatureExtractor']
 lowerCamelCase_			=						['LayoutLMv2ImageProcessor']

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCamelCase_			=						[
     'LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST',
     'LayoutLMv2ForQuestionAnswering',
     'LayoutLMv2ForSequenceClassification',
     'LayoutLMv2ForTokenClassification',
     'LayoutLMv2Layer',
     'LayoutLMv2Model',
     'LayoutLMv2PreTrainedModel',
 ]

if TYPE_CHECKING:
 from .configuration_layoutlmva import LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP, LayoutLMvaConfig
 from .processing_layoutlmva import LayoutLMvaProcessor
 from .tokenization_layoutlmva import LayoutLMvaTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_layoutlmva_fast import LayoutLMvaTokenizerFast

 try:
  if not is_vision_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .feature_extraction_layoutlmva import LayoutLMvaFeatureExtractor, LayoutLMvaImageProcessor

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_layoutlmva import (
      LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST,
      LayoutLMvaForQuestionAnswering,
      LayoutLMvaForSequenceClassification,
      LayoutLMvaForTokenClassification,
      LayoutLMvaLayer,
      LayoutLMvaModel,
      LayoutLMvaPreTrainedModel,
  )
else:
 import sys

 lowerCamelCase_			=						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)

