






def 							A     (       a_					)     ->						int:

					if not isinstance(a_							,a_					):
										raise ValueError('multiplicative_persistence() only accepts integral values'					)
					if num < 0:
										raise ValueError('multiplicative_persistence() does not accept negative values'					)

					__UpperCamelCase      :					Any       		=0
					__UpperCamelCase      :					List[str]       		=str(a_					)

					while len(a_					) != 1:
										__UpperCamelCase      :					Optional[int]       		=[int(a_					) for i in num_string]

										__UpperCamelCase      :					List[Any]       		=1
										for i in range(0							,len(a_					)					):
															total *= numbers[i]

										__UpperCamelCase      :					List[str]       		=str(a_					)

										steps += 1
					return steps






def 							A     (       a_					)     ->						int:

					if not isinstance(a_							,a_					):
										raise ValueError('additive_persistence() only accepts integral values'					)
					if num < 0:
										raise ValueError('additive_persistence() does not accept negative values'					)

					__UpperCamelCase      :					Union[str, Any]       		=0
					__UpperCamelCase      :					str       		=str(a_					)

					while len(a_					) != 1:
										__UpperCamelCase      :					Any       		=[int(a_					) for i in num_string]

										__UpperCamelCase      :					List[Any]       		=0
										for i in range(0							,len(a_					)					):
															total += numbers[i]

										__UpperCamelCase      :					Any       		=str(a_					)

										steps += 1
					return steps


if __name__ == "__main__":
							import doctest

							doctest.testmod()



"""simple docstring"""




from typing import TYPE_CHECKING

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


_A			:       Optional[int]   		=       {
    """configuration_llama""": ["""LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LlamaConfig"""],
}

try:
   if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _A			:       Union[str, Any]   		=       ["""LlamaTokenizer"""]

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _A			:       Dict   		=       ["""LlamaTokenizerFast"""]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _A			:       int   		=       [
       """LlamaForCausalLM""",
       """LlamaModel""",
       """LlamaPreTrainedModel""",
       """LlamaForSequenceClassification""",
   ]


if TYPE_CHECKING:
   from .configuration_llama import LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, LlamaConfig

   try:
      if not is_sentencepiece_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_llama import LlamaTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_llama_fast import LlamaTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_llama import LlamaForCausalLM, LlamaForSequenceClassification, LlamaModel, LlamaPreTrainedModel


else:
   import sys

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


