




'''simple docstring'''

def 		__magic_name__    (	__UpperCAmelCase,      __UpperCAmelCase	)		->					int:

					'''simple docstring'''

					while b:
										snake_case_			,snake_case_									=				b, a % b
					return a


def 		__magic_name__    (	__UpperCAmelCase,      __UpperCAmelCase	)		->					int:

					'''simple docstring'''

					return a if b == 0 else euclidean_gcd_recursive(__UpperCAmelCase,      a % b	)


def 		__magic_name__    (	)		->					Any:

					'''simple docstring'''

					print(F"euclidean_gcd(3, 5) = {euclidean_gcd(3,      5	)}"	)
					print(F"euclidean_gcd(5, 3) = {euclidean_gcd(5,      3	)}"	)
					print(F"euclidean_gcd(1, 3) = {euclidean_gcd(1,      3	)}"	)
					print(F"euclidean_gcd(3, 6) = {euclidean_gcd(3,      6	)}"	)
					print(F"euclidean_gcd(6, 3) = {euclidean_gcd(6,      3	)}"	)

					print(F"euclidean_gcd_recursive(3, 5) = {euclidean_gcd_recursive(3,      5	)}"	)
					print(F"euclidean_gcd_recursive(5, 3) = {euclidean_gcd_recursive(5,      3	)}"	)
					print(F"euclidean_gcd_recursive(1, 3) = {euclidean_gcd_recursive(1,      3	)}"	)
					print(F"euclidean_gcd_recursive(3, 6) = {euclidean_gcd_recursive(3,      6	)}"	)
					print(F"euclidean_gcd_recursive(6, 3) = {euclidean_gcd_recursive(6,      3	)}"	)


if __name__ == "__main__":
							main()







'''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__)

