



"""simple docstring"""
def        lowerCAmelCase_						(							SCREAMING_SNAKE_CASE__, SCREAMING_SNAKE_CASE__	)			->      str:
		a_     :      Union[str, Any] 						=     [1]
		for i in range(2, SCREAMING_SNAKE_CASE__	):
				factorials.append(factorials[-1] * i	)
		assert 0 <= k < factorials[-1] * n, "k out of bounds"

		a_     :      int 						=     []
		a_     :      Optional[Any] 						=     list(range(SCREAMING_SNAKE_CASE__	)	)

		# Find permutation
		while factorials:
				a_     :      Optional[int] 						=     factorials.pop()
				a_						,				a_     :      List[Any] 						=     divmod(SCREAMING_SNAKE_CASE__, SCREAMING_SNAKE_CASE__	)
				permutation.append(elements[number]	)
				elements.remove(elements[number]	)
		permutation.append(elements[0]	)

		return permutation


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,
)


SCREAMING_SNAKE_CASE_				= {
    """configuration_llama""": ["""LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LlamaConfig"""],
}

try:
					if not is_sentencepiece_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					SCREAMING_SNAKE_CASE_				= ["""LlamaTokenizer"""]

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

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					SCREAMING_SNAKE_CASE_				= [
					    """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

					SCREAMING_SNAKE_CASE_				= _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)