



"""simple docstring"""
import inspect
import warnings
from typing import Any, Dict, Optional, Union

from packaging import version


def 			_SCREAMING_SNAKE_CASE						(*__lowerCAmelCase ,  __lowerCAmelCase = None ,  __lowerCAmelCase=True ,  __lowerCAmelCase=2							) ->						Optional[Any]:







  '''simple docstring'''


  from .. import __version__

  lowercase_								= take_from
  lowercase_								= ()
  if not isinstance(args[0] ,  __lowerCAmelCase							):
    lowercase_								= (args,)

  for attribute, version_name, message in args:
    if version.parse(version.parse(__lowerCAmelCase							).base_version							) >= version.parse(__lowerCAmelCase							):
      raise ValueError(
          F'''The deprecation tuple {(attribute, version_name, message)} should be removed since diffusers\''''
          F''' version {__version__} is >= {version_name}'''							)

    lowercase_								= None
    if isinstance(__lowerCAmelCase ,  __lowerCAmelCase							) and attribute in deprecated_kwargs:
      values += (deprecated_kwargs.pop(__lowerCAmelCase							),)
      lowercase_								= F'''The `{attribute}` argument is deprecated and will be removed in version {version_name}.'''
    elif hasattr(__lowerCAmelCase ,  __lowerCAmelCase							):
      values += (getattr(__lowerCAmelCase ,  __lowerCAmelCase							),)
      lowercase_								= F'''The `{attribute}` attribute is deprecated and will be removed in version {version_name}.'''
    elif deprecated_kwargs is None:
      lowercase_								= F'''`{attribute}` is deprecated and will be removed in version {version_name}.'''

    if warning is not None:
      lowercase_								= warning + """ """ if standard_warn else """"""
      warnings.warn(warning + message ,  __lowerCAmelCase ,  stacklevel=__lowerCAmelCase							)

  if isinstance(__lowerCAmelCase ,  __lowerCAmelCase							) and len(__lowerCAmelCase							) > 0:
    lowercase_								= inspect.getouterframes(inspect.currentframe()							)[1]
    lowercase_								= call_frame.filename
    lowercase_								= call_frame.lineno
    lowercase_								= call_frame.function
    lowercase_					,    lowercase_								= next(iter(deprecated_kwargs.items()							)							)
    raise TypeError(F'''{function} in {filename} line {line_number-1} got an unexpected keyword argument `{key}`'''							)

  if len(__lowerCAmelCase							) == 0:
    return
  elif len(__lowerCAmelCase							) == 1:
    return values[0]
  return values






"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCAmelCase						:		Union[str, Any]			= {
    "configuration_longformer": [
        "LONGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "LongformerConfig",
        "LongformerOnnxConfig",
    ],
    "tokenization_longformer": ["LongformerTokenizer"],
}

try:
       if not is_tokenizers_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase						:		List[Any]			= ["LongformerTokenizerFast"]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase						:		Tuple			= [
           "LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
           "LongformerForMaskedLM",
           "LongformerForMultipleChoice",
           "LongformerForQuestionAnswering",
           "LongformerForSequenceClassification",
           "LongformerForTokenClassification",
           "LongformerModel",
           "LongformerPreTrainedModel",
           "LongformerSelfAttention",
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase						:		List[Any]			= [
           "TF_LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
           "TFLongformerForMaskedLM",
           "TFLongformerForMultipleChoice",
           "TFLongformerForQuestionAnswering",
           "TFLongformerForSequenceClassification",
           "TFLongformerForTokenClassification",
           "TFLongformerModel",
           "TFLongformerPreTrainedModel",
           "TFLongformerSelfAttention",
       ]


if TYPE_CHECKING:
       from .configuration_longformer import (
           LONGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
           LongformerConfig,
           LongformerOnnxConfig,
       )
       from .tokenization_longformer import LongformerTokenizer

       try:
              if not is_tokenizers_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_longformer_fast import LongformerTokenizerFast

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_longformer import (
                  LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
                  LongformerForMaskedLM,
                  LongformerForMultipleChoice,
                  LongformerForQuestionAnswering,
                  LongformerForSequenceClassification,
                  LongformerForTokenClassification,
                  LongformerModel,
                  LongformerPreTrainedModel,
                  LongformerSelfAttention,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_longformer import (
                  TF_LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
                  TFLongformerForMaskedLM,
                  TFLongformerForMultipleChoice,
                  TFLongformerForQuestionAnswering,
                  TFLongformerForSequenceClassification,
                  TFLongformerForTokenClassification,
                  TFLongformerModel,
                  TFLongformerPreTrainedModel,
                  TFLongformerSelfAttention,
              )

else:
       import sys

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

