code: 
  
  from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_flax_available,
      is_sentencepiece_available,
      is_tf_available,
      is_tokenizers_available,
      is_torch_available,
  )
  
  
  lowerCamelCase     =      {
      '''configuration_big_bird''': ['''BIG_BIRD_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BigBirdConfig''', '''BigBirdOnnxConfig'''],
  }
  
  try:
    if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    lowerCamelCase     =      ['''BigBirdTokenizer''']
  
  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    lowerCamelCase     =      ['''BigBirdTokenizerFast''']
  
  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    lowerCamelCase     =      [
        '''BIG_BIRD_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''BigBirdForCausalLM''',
        '''BigBirdForMaskedLM''',
        '''BigBirdForMultipleChoice''',
        '''BigBirdForPreTraining''',
        '''BigBirdForQuestionAnswering''',
        '''BigBirdForSequenceClassification''',
        '''BigBirdForTokenClassification''',
        '''BigBirdLayer''',
        '''BigBirdModel''',
        '''BigBirdPreTrainedModel''',
        '''load_tf_weights_in_big_bird''',
    ]
  
  try:
    if not is_flax_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    lowerCamelCase     =      [
        '''FlaxBigBirdForCausalLM''',
        '''FlaxBigBirdForMaskedLM''',
        '''FlaxBigBirdForMultipleChoice''',
        '''FlaxBigBirdForPreTraining''',
        '''FlaxBigBirdForQuestionAnswering''',
        '''FlaxBigBirdForSequenceClassification''',
        '''FlaxBigBirdForTokenClassification''',
        '''FlaxBigBirdModel''',
        '''FlaxBigBirdPreTrainedModel''',
    ]
  
  if TYPE_CHECKING:
    from .configuration_big_bird import BIG_BIRD_PRETRAINED_CONFIG_ARCHIVE_MAP, BigBirdConfig, BigBirdOnnxConfig
  
    try:
      if not is_sentencepiece_available():
        raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
      pass
    else:
      from .tokenization_big_bird import BigBirdTokenizer
  
    try:
      if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
      pass
    else:
      from .tokenization_big_bird_fast import BigBirdTokenizerFast
  
    try:
      if not is_torch_available():
        raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
      pass
    else:
      from .modeling_big_bird import (
          BIG_BIRD_PRETRAINED_MODEL_ARCHIVE_LIST,
          BigBirdForCausalLM,
          BigBirdForMaskedLM,
          BigBirdForMultipleChoice,
          BigBirdForPreTraining,
          BigBirdForQuestionAnswering,
          BigBirdForSequenceClassification,
          BigBirdForTokenClassification,
          BigBirdLayer,
          BigBirdModel,
          BigBirdPreTrainedModel,
          load_tf_weights_in_big_bird,
      )
  
    try:
      if not is_flax_available():
        raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
      pass
    else:
      from .modeling_flax_big_bird import (
          FlaxBigBirdForCausalLM,
          FlaxBigBirdForMaskedLM,
          FlaxBigBirdForMultipleChoice,
          FlaxBigBirdForPreTraining,
          FlaxBigBirdForQuestionAnswering,
          FlaxBigBirdForSequenceClassification,
          FlaxBigBirdForTokenClassification,
          FlaxBigBirdModel,
          FlaxBigBirdPreTrainedModel,
      )
  
  else:
    import sys
  
    lowerCamelCase     =      _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
  
style_context: 
  
  from dataclasses import dataclass
  from typing import List, Optional, Union
  
  import numpy as np
  import PIL
  from PIL import Image
  
  from ...utils import BaseOutput, is_torch_available, is_transformers_available
  
  
  
  
  
  
  
  @dataclass
  # Copied from diffusers.pipelines.stable_diffusion.__init__.StableDiffusionPipelineOutput with Stable->Alt
  class 		__magic_name__    (							lowerCamelCase__							):
  
     '''simple docstring'''
  
  
  
  
     lowerCamelCase__				:			Union[List[PIL.Image.Image], np.ndarray]
     lowerCamelCase__				:			Optional[List[bool]]
  
  
  if is_transformers_available() and is_torch_available():
         from .modeling_roberta_series import RobertaSeriesModelWithTransformation
         from .pipeline_alt_diffusion import AltDiffusionPipeline
         from .pipeline_alt_diffusion_imgaimg import AltDiffusionImgaImgPipeline
  