
def 				A__    (  lowerCamelCase   ,			lowerCamelCase   ,			lowerCamelCase  )     ->		float:
				UpperCamelCase_:							List[str]		=  [1 / first_term]
				UpperCamelCase_:							Optional[int]		=  1 / first_term
				for _ in range(number_of_terms - 1  ):
								first_term += common_difference
								arithmetic_progression.append(lowerCamelCase  )
				UpperCamelCase_:							Any		=  [1 / step for step in arithmetic_progression]
				return sum(lowerCamelCase  )


if __name__ == "__main__":
							import doctest

							doctest.testmod()
							print(sum_of_harmonic_progression(1 / 2, 2, 2))









from typing import TYPE_CHECKING

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


UpperCamelCase__     :					int								=			{
    "configuration_camembert": ["CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "CamembertConfig", "CamembertOnnxConfig"],
}

try:
       if not is_sentencepiece_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCamelCase__     :					str								=			["CamembertTokenizer"]

try:
       if not is_tokenizers_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCamelCase__     :					Any								=			["CamembertTokenizerFast"]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCamelCase__     :					Union[str, 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:
       UpperCamelCase__     :					Optional[Any]								=			[
           "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

       UpperCamelCase__     :					List[str]								=			_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)


