

from typing import TYPE_CHECKING

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


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

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

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

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase_    =					[
        '''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_    =					[
        '''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_    =					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


from __future__ import annotations

from collections.abc import Generator



def    UpperCamelCase(					lowercase_							)	->				Generator[int, None, None]:





  '''simple docstring'''





  if not isinstance(lowercase_			,					lowercase_							) or n < 1:
    raise Exception("""Sequence only defined for positive integers"""							)

  yield n
  while n != 1:
    if n % 2 == 0:
      n //= 2
    else:
      snake_case_       						=      3 * n + 1
    yield n



def    UpperCamelCase(					)	->				Optional[int]:





  '''simple docstring'''





  snake_case_       						=      43
  snake_case_       						=      tuple(collatz_sequence(lowercase_							)							)
  print(lowercase_							)
  print(f'''Collatz sequence from {n} took {len(lowercase_							)} steps.'''							)


if __name__ == "__main__":
    main()