code: 
  
  
  
  
  
  
  """simple docstring"""
  
  from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_tf_available,
      is_tokenizers_available,
      is_torch_available,
  )
  
  
  lowercase__      =				{
      """configuration_openai""": ["""OPENAI_GPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """OpenAIGPTConfig"""],
      """tokenization_openai""": ["""OpenAIGPTTokenizer"""],
  }
  
  try:
  					if not is_tokenizers_available():
  										raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  					pass
  else:
  					lowercase__      =				["""OpenAIGPTTokenizerFast"""]
  
  try:
  					if not is_torch_available():
  										raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  					pass
  else:
  					lowercase__      =				[
  					    """OPENAI_GPT_PRETRAINED_MODEL_ARCHIVE_LIST""",
  					    """OpenAIGPTDoubleHeadsModel""",
  					    """OpenAIGPTForSequenceClassification""",
  					    """OpenAIGPTLMHeadModel""",
  					    """OpenAIGPTModel""",
  					    """OpenAIGPTPreTrainedModel""",
  					    """load_tf_weights_in_openai_gpt""",
  					]
  
  try:
  					if not is_tf_available():
  										raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  					pass
  else:
  					lowercase__      =				[
  					    """TF_OPENAI_GPT_PRETRAINED_MODEL_ARCHIVE_LIST""",
  					    """TFOpenAIGPTDoubleHeadsModel""",
  					    """TFOpenAIGPTForSequenceClassification""",
  					    """TFOpenAIGPTLMHeadModel""",
  					    """TFOpenAIGPTMainLayer""",
  					    """TFOpenAIGPTModel""",
  					    """TFOpenAIGPTPreTrainedModel""",
  					]
  
  
  if TYPE_CHECKING:
  					from .configuration_openai import OPENAI_GPT_PRETRAINED_CONFIG_ARCHIVE_MAP, OpenAIGPTConfig
  					from .tokenization_openai import OpenAIGPTTokenizer
  
  					try:
  										if not is_tokenizers_available():
  															raise OptionalDependencyNotAvailable()
  					except OptionalDependencyNotAvailable:
  										pass
  					else:
  										from .tokenization_openai_fast import OpenAIGPTTokenizerFast
  
  					try:
  										if not is_torch_available():
  															raise OptionalDependencyNotAvailable()
  					except OptionalDependencyNotAvailable:
  										pass
  					else:
  										from .modeling_openai import (
  										    OPENAI_GPT_PRETRAINED_MODEL_ARCHIVE_LIST,
  										    OpenAIGPTDoubleHeadsModel,
  										    OpenAIGPTForSequenceClassification,
  										    OpenAIGPTLMHeadModel,
  										    OpenAIGPTModel,
  										    OpenAIGPTPreTrainedModel,
  										    load_tf_weights_in_openai_gpt,
  										)
  
  					try:
  										if not is_tf_available():
  															raise OptionalDependencyNotAvailable()
  					except OptionalDependencyNotAvailable:
  										pass
  					else:
  										from .modeling_tf_openai import (
  										    TF_OPENAI_GPT_PRETRAINED_MODEL_ARCHIVE_LIST,
  										    TFOpenAIGPTDoubleHeadsModel,
  										    TFOpenAIGPTForSequenceClassification,
  										    TFOpenAIGPTLMHeadModel,
  										    TFOpenAIGPTMainLayer,
  										    TFOpenAIGPTModel,
  										    TFOpenAIGPTPreTrainedModel,
  										)
  
  else:
  					import sys
  
  					lowercase__      =				_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
  
style_context: 
  
  
  
  
  
  
  """simple docstring"""
  
  from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_torch_available,
      is_vision_available,
  )
  
  
  lowercase__      =				{
      """configuration_mobilevitv2""": [
          """MOBILEVITV2_PRETRAINED_CONFIG_ARCHIVE_MAP""",
          """MobileViTV2Config""",
          """MobileViTV2OnnxConfig""",
      ],
  }
  
  
  try:
  					if not is_torch_available():
  										raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  					pass
  else:
  					lowercase__      =				[
  					    """MOBILEVITV2_PRETRAINED_MODEL_ARCHIVE_LIST""",
  					    """MobileViTV2ForImageClassification""",
  					    """MobileViTV2ForSemanticSegmentation""",
  					    """MobileViTV2Model""",
  					    """MobileViTV2PreTrainedModel""",
  					]
  
  if TYPE_CHECKING:
  					from .configuration_mobilevitva import (
  					    MOBILEVITV2_PRETRAINED_CONFIG_ARCHIVE_MAP,
  					    MobileViTVaConfig,
  					    MobileViTVaOnnxConfig,
  					)
  
  					try:
  										if not is_torch_available():
  															raise OptionalDependencyNotAvailable()
  					except OptionalDependencyNotAvailable:
  										pass
  					else:
  										from .modeling_mobilevitva import (
  										    MOBILEVITV2_PRETRAINED_MODEL_ARCHIVE_LIST,
  										    MobileViTVaForImageClassification,
  										    MobileViTVaForSemanticSegmentation,
  										    MobileViTVaModel,
  										    MobileViTVaPreTrainedModel,
  										)
  
  else:
  					import sys
  
  					lowercase__      =				_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
  