



"""simple docstring"""


def  _lowerCAmelCase      (   lowercase_						):

						if not all(char in '01' for char in bin_string						):
												raise ValueError('Non-binary value was passed to the function'						)
						if not bin_string:
												raise ValueError('Empty string was passed to the function'						)
						UpperCAmelCase             = ''
						while len(__UpperCAmelCase						) % 3 != 0:
												UpperCAmelCase             = '0' + bin_string
						UpperCAmelCase             = [
						    bin_string[index : index + 3]
						    for index in range(len(__UpperCAmelCase						)						)
						    if index % 3 == 0
						]
						for bin_group in bin_string_in_3_list:
												UpperCAmelCase             = 0
												for index, val in enumerate(__UpperCAmelCase						):
																		oct_val += int(2 ** (2 - index) * int(__UpperCAmelCase						)						)
												oct_string += str(__UpperCAmelCase						)
						return oct_string


if __name__ == "__main__":
				from doctest import testmod

				testmod()











'''simple docstring'''

from typing import TYPE_CHECKING

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


a  :				Tuple									=  {
    'configuration_llama': ['LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LlamaConfig'],
}

try:
							if not is_sentencepiece_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							a  :				Optional[Any]									=  ['LlamaTokenizer']

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							a  :				str									=  ['LlamaTokenizerFast']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							a  :				Optional[Any]									=  [
							    '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__)

