





from typing import TYPE_CHECKING

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


lowercase    : Optional[Any]    	=  {
    """configuration_bloom""": ["""BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BloomConfig""", """BloomOnnxConfig"""],
}
try:
       if not is_tokenizers_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase    : Any    	=  ["""BloomTokenizerFast"""]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase    : Union[str, Any]    	=  [
           """BLOOM_PRETRAINED_MODEL_ARCHIVE_LIST""",
           """BloomForCausalLM""",
           """BloomModel""",
           """BloomPreTrainedModel""",
           """BloomForSequenceClassification""",
           """BloomForTokenClassification""",
           """BloomForQuestionAnswering""",
       ]

if TYPE_CHECKING:
       from .configuration_bloom import BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP, BloomConfig, BloomOnnxConfig

       try:
              if not is_tokenizers_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_bloom_fast import BloomTokenizerFast

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_bloom import (
                  BLOOM_PRETRAINED_MODEL_ARCHIVE_LIST,
                  BloomForCausalLM,
                  BloomForQuestionAnswering,
                  BloomForSequenceClassification,
                  BloomForTokenClassification,
                  BloomModel,
                  BloomPreTrainedModel,
              )

else:
       import sys

       lowercase    : Optional[Any]    	=  _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)













import warnings

from ...utils import logging
from .image_processing_clip import CLIPImageProcessor


lowercase    : str    	=  logging.get_logger(__name__)

class  __A(						__UpperCAmelCase ):

     def __init__(      self,       *A,       **A      ):





            """simple docstring"""

            warnings.warn(
                '''The class CLIPFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'''
                ''' use CLIPImageProcessor instead.''',       A,       )
            super().__init__(*A,       **A      )






