

'''simple docstring'''

from ctypes import c_float, sizeof
from enum import Enum
from typing import TYPE_CHECKING, Optional, Union


if TYPE_CHECKING:
       from .. import AutoFeatureExtractor, AutoProcessor, AutoTokenizer  # tests_ignore


class 					lowerCAmelCase       ( A				):
       lowerCAmelCase_				=	c_float







       @property
       def      snake_case				(							self     :	str ):







            """simple docstring"""







            return sizeof(self.value )






def 			__UpperCamelCase							(		lowercase__  :					int,   lowercase__  :					int,   lowercase__  :					int = 0	):






     '''simple docstring'''





     if dimension <= 0:
          __lowercase     						=fixed_dimension

     dimension -= num_token_to_add
     return dimension

def 			__UpperCamelCase							(		lowercase__  :					int,   lowercase__  :					ParameterFormat	):






     '''simple docstring'''





     return num_parameters * dtype.size







def 			__UpperCamelCase							(		lowercase__  :					str	):






     '''simple docstring'''





     from .. import AutoFeatureExtractor, AutoProcessor, AutoTokenizer  # tests_ignore

     try:
          return AutoProcessor.from_pretrained(lowercase__	)
     except (ValueError, OSError, KeyError):
          __lowercase						,       __lowercase     						=None, None
          try:
               __lowercase     						=AutoTokenizer.from_pretrained(lowercase__	)
          except (OSError, KeyError):
               pass
          try:
               __lowercase     						=AutoFeatureExtractor.from_pretrained(lowercase__	)
          except (OSError, KeyError):
               pass

          if tokenizer is not None and feature_extractor is not None:
               raise ValueError(
                   F'''Couldn\'t auto-detect preprocessor for {model_name}. Found both a tokenizer and a feature extractor.'''	)
          elif tokenizer is None and feature_extractor is None:
               return None
          elif tokenizer is not None:
               return tokenizer
          else:
               return feature_extractor





'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


UpperCAmelCase							=					{
    '''configuration_videomae''': ['''VIDEOMAE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''VideoMAEConfig'''],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase							=					[
           '''VIDEOMAE_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''VideoMAEForPreTraining''',
           '''VideoMAEModel''',
           '''VideoMAEPreTrainedModel''',
           '''VideoMAEForVideoClassification''',
       ]

try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase							=					['''VideoMAEFeatureExtractor''']
       UpperCAmelCase							=					['''VideoMAEImageProcessor''']

if TYPE_CHECKING:
       from .configuration_videomae import VIDEOMAE_PRETRAINED_CONFIG_ARCHIVE_MAP, VideoMAEConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_videomae import (
                  VIDEOMAE_PRETRAINED_MODEL_ARCHIVE_LIST,
                  VideoMAEForPreTraining,
                  VideoMAEForVideoClassification,
                  VideoMAEModel,
                  VideoMAEPreTrainedModel,
              )

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .feature_extraction_videomae import VideoMAEFeatureExtractor
              from .image_processing_videomae import VideoMAEImageProcessor

else:
       import sys

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


