





"""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__   	=	{
    '''configuration_rembert''': ['''REMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''RemBertConfig''', '''RemBertOnnxConfig''']
}

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

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

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase__   	=	[
						    '''REMBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''RemBertForCausalLM''',
						    '''RemBertForMaskedLM''',
						    '''RemBertForMultipleChoice''',
						    '''RemBertForQuestionAnswering''',
						    '''RemBertForSequenceClassification''',
						    '''RemBertForTokenClassification''',
						    '''RemBertLayer''',
						    '''RemBertModel''',
						    '''RemBertPreTrainedModel''',
						    '''load_tf_weights_in_rembert''',
						]


try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase__   	=	[
						    '''TF_REMBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''TFRemBertForCausalLM''',
						    '''TFRemBertForMaskedLM''',
						    '''TFRemBertForMultipleChoice''',
						    '''TFRemBertForQuestionAnswering''',
						    '''TFRemBertForSequenceClassification''',
						    '''TFRemBertForTokenClassification''',
						    '''TFRemBertLayer''',
						    '''TFRemBertModel''',
						    '''TFRemBertPreTrainedModel''',
						]


if TYPE_CHECKING:
						from .configuration_rembert import REMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, RemBertConfig, RemBertOnnxConfig

						try:
												if not is_sentencepiece_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_rembert import RemBertTokenizer

						try:
												if not is_tokenizers_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_rembert_fast import RemBertTokenizerFast

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_rembert import (
												    REMBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    RemBertForCausalLM,
												    RemBertForMaskedLM,
												    RemBertForMultipleChoice,
												    RemBertForQuestionAnswering,
												    RemBertForSequenceClassification,
												    RemBertForTokenClassification,
												    RemBertLayer,
												    RemBertModel,
												    RemBertPreTrainedModel,
												    load_tf_weights_in_rembert,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_rembert import (
												    TF_REMBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TFRemBertForCausalLM,
												    TFRemBertForMaskedLM,
												    TFRemBertForMultipleChoice,
												    TFRemBertForQuestionAnswering,
												    TFRemBertForSequenceClassification,
												    TFRemBertForTokenClassification,
												    TFRemBertLayer,
												    TFRemBertModel,
												    TFRemBertPreTrainedModel,
												)


else:
						import sys

						lowerCAmelCase__   	=	_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)












def 	_a      (						SCREAMING_SNAKE_CASE_							:				int = 1_00_00_00     ):
					__lowerCAmelCase				   =       [i - 1 for i in range(limit + 1     )]

					for i in range(2      ,      limit + 1     ):
										if phi[i] == i - 1:
															for j in range(2 * i      ,      limit + 1      ,      SCREAMING_SNAKE_CASE_     ):
																				phi[j] -= phi[j] // i

					return sum(phi[2 : limit + 1]     )


if __name__ == "__main__":
					print(solution())




