



from typing import TYPE_CHECKING

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


lowerCAmelCase:      int		 =		{
    'configuration_gpt_neo': ['GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GPTNeoConfig', 'GPTNeoOnnxConfig'],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCAmelCase:      List[Any]		 =		[
         'GPT_NEO_PRETRAINED_MODEL_ARCHIVE_LIST',
         'GPTNeoForCausalLM',
         'GPTNeoForQuestionAnswering',
         'GPTNeoForSequenceClassification',
         'GPTNeoForTokenClassification',
         'GPTNeoModel',
         'GPTNeoPreTrainedModel',
         'load_tf_weights_in_gpt_neo',
     ]

try:
     if not is_flax_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCAmelCase:      Dict		 =		[
         'FlaxGPTNeoForCausalLM',
         'FlaxGPTNeoModel',
         'FlaxGPTNeoPreTrainedModel',
     ]


if TYPE_CHECKING:
     from .configuration_gpt_neo import GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoConfig, GPTNeoOnnxConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_gpt_neo import (
              GPT_NEO_PRETRAINED_MODEL_ARCHIVE_LIST,
              GPTNeoForCausalLM,
              GPTNeoForQuestionAnswering,
              GPTNeoForSequenceClassification,
              GPTNeoForTokenClassification,
              GPTNeoModel,
              GPTNeoPreTrainedModel,
              load_tf_weights_in_gpt_neo,
          )

     try:
          if not is_flax_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_flax_gpt_neo import FlaxGPTNeoForCausalLM, FlaxGPTNeoModel, FlaxGPTNeoPreTrainedModel


else:
     import sys

     lowerCAmelCase:      str		 =		_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




'''simple docstring'''






import warnings

from ...utils import logging
from .image_processing_chinese_clip import ChineseCLIPImageProcessor


lowerCAmelCase:      Optional[Any]		 =		logging.get_logger(__name__)

class 							a__(      lowerCamelCase__			):







    def __init__(   self				:						Union[str, Any]		,    *__snake_case				:						List[str]		,    **__snake_case				:						Union[str, Any]			):
      warnings.warn(
          'The class ChineseCLIPFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
          ' Please use ChineseCLIPImageProcessor instead.'		,    __snake_case		,    )
      super().__init__(*__snake_case		,    **__snake_case			)