



from typing import TYPE_CHECKING

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


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

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

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

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_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

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




'''simple docstring'''





import math






def 						UpperCAmelCase__(				_SCREAMING_SNAKE_CASE					: int ):






			"""simple docstring"""




			if not isinstance(_SCREAMING_SNAKE_CASE,_SCREAMING_SNAKE_CASE ):
						__A=	f"""Input value of [number={number}] must be an integer"""
						raise TypeError(_SCREAMING_SNAKE_CASE )

			if number < 1:
						__A=	f"""Input value of [number={number}] must be > 0"""
						raise ValueError(_SCREAMING_SNAKE_CASE )
			elif number == 1:
						return 3
			elif number == 2:
						return 5
			else:
						__A=	int(math.log(number // 3,2 ) ) + 2

						__A=	[3, 5]
						__A=	2
						__A=	3
						for block in range(1,_SCREAMING_SNAKE_CASE ):
									for _ in range(_SCREAMING_SNAKE_CASE ):
												proth_list.append(2 ** (block + 1) + proth_list[proth_index - 1] )
												proth_index += 1
									increment *= 2

			return proth_list[number - 1]


if __name__ == "__main__":
					import doctest

					doctest.testmod()

					for number in range(1_1):
										UpperCAmelCase__  			=				0
										try:
															UpperCAmelCase__  			=				proth(number)
										except ValueError:
															print(F"""ValueError: there is no {number}th Proth number""")
															continue

										print(F"""The {number}th Proth number: {value}""")



