



"""simple docstring"""


from __future__ import annotations

def  _lowerCAmelCase      (   lowercase_		,	lowercase_		,	lowercase_		,	lowercase_						):  # noqa: E741

						while r - l > 1:
												UpperCAmelCase             = (l + r) // 2
												if v[m] >= key:
																		UpperCAmelCase             = m
												else:
																		UpperCAmelCase             = m  # noqa: E741
						return r

def  _lowerCAmelCase      (   lowercase_						):

						if len(__UpperCAmelCase						) == 0:
												return 0

						UpperCAmelCase             = [0] * len(__UpperCAmelCase						)
						UpperCAmelCase             = 1

						UpperCAmelCase             = v[0]

						for i in range(1		,	len(__UpperCAmelCase						)						):
												if v[i] < tail[0]:
																		UpperCAmelCase             = v[i]
												elif v[i] > tail[length - 1]:
																		UpperCAmelCase             = v[i]
																		length += 1
												else:
																		UpperCAmelCase             = v[i]

						return length


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  :				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__)

