





"""simple docstring"""




from collections import OrderedDict
from dataclasses import fields
from typing import Any, Tuple

import numpy as np

from .import_utils import is_torch_available





def 		UpperCAmelCase__						(	_UpperCAmelCase   ):






  """simple docstring"""





  if is_torch_available():
    import torch

    if isinstance(_UpperCAmelCase					,   torch.Tensor   ):
      return True

  return isinstance(_UpperCAmelCase					,   np.ndarray   )





class 					_UpperCAmelCase    (  UpperCAmelCase__						):



      '''simple docstring'''

      def    lowerCamelCase_     (	self    ):

        """simple docstring"""

        A_    :			Dict									=    fields(self    )

        # Safety and consistency checks
        if not len(snake_case_    ):
          raise ValueError(F"""{self.__class__.__name__} has no fields."""    )

        A_    :			Dict									=    getattr(self   , class_fields[0].name    )
        A_    :			str									=    all(getattr(self   , field.name    ) is None for field in class_fields[1:]    )

        if other_fields_are_none and isinstance(snake_case_   , snake_case_    ):
          for key, value in first_field.items():
            A_    :			Optional[Any]									=    value
        else:
          for field in class_fields:
            A_    :			List[Any]									=    getattr(self   , field.name    )
            if v is not None:
              A_    :			Any									=    v

      def __delitem__(	self   , *snake_case_   , **snake_case_    ):

        """simple docstring"""

        raise Exception(F"""You cannot use ``__delitem__`` on a {self.__class__.__name__} instance."""    )

      def    lowerCamelCase_     (	self   , *snake_case_   , **snake_case_    ):

        """simple docstring"""

        raise Exception(F"""You cannot use ``setdefault`` on a {self.__class__.__name__} instance."""    )

      def    lowerCamelCase_     (	self   , *snake_case_   , **snake_case_    ):

        """simple docstring"""

        raise Exception(F"""You cannot use ``pop`` on a {self.__class__.__name__} instance."""    )

      def    lowerCamelCase_     (	self   , *snake_case_   , **snake_case_    ):

        """simple docstring"""

        raise Exception(F"""You cannot use ``update`` on a {self.__class__.__name__} instance."""    )

      def __getitem__(	self   , snake_case_    ):

        """simple docstring"""

        if isinstance(snake_case_   , snake_case_    ):
          A_    :			str									=    dict(self.items()    )
          return inner_dict[k]
        else:
          return self.to_tuple()[k]

      def __setattr__(	self   , snake_case_   , snake_case_    ):

        """simple docstring"""

        if name in self.keys() and value is not None:
          # Don't call self.__setitem__ to avoid recursion errors
          super().__setitem__(snake_case_   , snake_case_    )
        super().__setattr__(snake_case_   , snake_case_    )

      def __setitem__(	self   , snake_case_   , snake_case_    ):

        """simple docstring"""

        super().__setitem__(snake_case_   , snake_case_    )
        # Don't call self.__setattr__ to avoid recursion errors
        super().__setattr__(snake_case_   , snake_case_    )

      def    lowerCamelCase_     (	self    ):

        """simple docstring"""

        return tuple(self[k] for k in self.keys()    )






"""simple docstring"""




from typing import TYPE_CHECKING

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


lowerCamelCase_	:		Union[str, Any]         =   {
    'configuration_camembert': ['CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CamembertConfig', 'CamembertOnnxConfig'],
}

try:
   if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase_	:		Any         =   ['CamembertTokenizer']

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase_	:		int         =   ['CamembertTokenizerFast']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase_	:		Optional[Any]         =   [
       'CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
       'CamembertForCausalLM',
       'CamembertForMaskedLM',
       'CamembertForMultipleChoice',
       'CamembertForQuestionAnswering',
       'CamembertForSequenceClassification',
       'CamembertForTokenClassification',
       'CamembertModel',
       'CamembertPreTrainedModel',
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase_	:		int         =   [
       'TF_CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
       'TFCamembertForCausalLM',
       'TFCamembertForMaskedLM',
       'TFCamembertForMultipleChoice',
       'TFCamembertForQuestionAnswering',
       'TFCamembertForSequenceClassification',
       'TFCamembertForTokenClassification',
       'TFCamembertModel',
       'TFCamembertPreTrainedModel',
   ]


if TYPE_CHECKING:
   from .configuration_camembert import CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, CamembertConfig, CamembertOnnxConfig

   try:
      if not is_sentencepiece_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_camembert import CamembertTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_camembert_fast import CamembertTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_camembert import (
          CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
          CamembertForCausalLM,
          CamembertForMaskedLM,
          CamembertForMultipleChoice,
          CamembertForQuestionAnswering,
          CamembertForSequenceClassification,
          CamembertForTokenClassification,
          CamembertModel,
          CamembertPreTrainedModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_camembert import (
          TF_CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFCamembertForCausalLM,
          TFCamembertForMaskedLM,
          TFCamembertForMultipleChoice,
          TFCamembertForQuestionAnswering,
          TFCamembertForSequenceClassification,
          TFCamembertForTokenClassification,
          TFCamembertModel,
          TFCamembertPreTrainedModel,
      )

else:
   import sys

   lowerCamelCase_	:		int         =   _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)