
"""simple docstring"""
def     lowerCamelCase_    (	lowerCamelCase_ )     ->			tuple[int, int]:


					'''simple docstring'''
					# base case
					if len(lowerCamelCase_ ) == 1:
										return a[0], a[0]
					else:
										# split A into half.
										__a:						Tuple		    =					a[: len(lowerCamelCase_ ) // 2]
										__a:						List[Any]		    =					a[len(lowerCamelCase_ ) // 2 :]

										# 2 sub problems, 1/2 of original size.
										__a    ,				__a:						Optional[Any]		    =					max_difference(lowerCamelCase_ )
										__a    ,				__a:						List[Any]		    =					max_difference(lowerCamelCase_ )

										# get min of first and max of second
										# linear time
										__a:						Optional[int]		    =					min(lowerCamelCase_ )
										__a:						int		    =					max(lowerCamelCase_ )

										# 3 cases, either (small1, big1),
										# (min_first, max_second), (small2, big2)
										# constant comparisons
										if biga - smalla > max_second - min_first and biga - smalla > biga - smalla:
															return smalla, biga
										elif biga - smalla > max_second - min_first:
															return smalla, biga
										else:
															return min_first, max_second


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,
)


lowercase		:						List[str] =					{
    'configuration_open_llama': ['OPEN_LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'OpenLlamaConfig'],
}

try:
			if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowercase		:						Tuple =					['LlamaTokenizer']

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

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowercase		:						List[Any] =					[
			    'OpenLlamaForCausalLM',
			    'OpenLlamaModel',
			    'OpenLlamaPreTrainedModel',
			    'OpenLlamaForSequenceClassification',
			]


if TYPE_CHECKING:
			from .configuration_open_llama import OPEN_LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, OpenLlamaConfig

			try:
						if not is_sentencepiece_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from transformers import LlamaTokenizer

			try:
						if not is_tokenizers_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from transformers import LlamaTokenizerFast

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_open_llama import (
						    OpenLlamaForCausalLM,
						    OpenLlamaForSequenceClassification,
						    OpenLlamaModel,
						    OpenLlamaPreTrainedModel,
						)


else:
			import sys

			lowercase		:						Dict =					_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
