




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCAmelCase_		:					Tuple          =  {"configuration_opt": ["OPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "OPTConfig"]}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase_		:					str          =  [
							    "OPT_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "OPTForCausalLM",
							    "OPTModel",
							    "OPTPreTrainedModel",
							    "OPTForSequenceClassification",
							    "OPTForQuestionAnswering",
							]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase_		:					Dict          =  ["TFOPTForCausalLM", "TFOPTModel", "TFOPTPreTrainedModel"]

try:
							if not is_flax_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase_		:					Any          =  [
							    "FlaxOPTForCausalLM",
							    "FlaxOPTModel",
							    "FlaxOPTPreTrainedModel",
							]


if TYPE_CHECKING:
							from .configuration_opt import OPT_PRETRAINED_CONFIG_ARCHIVE_MAP, OPTConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_opt import (
														    OPT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    OPTForCausalLM,
														    OPTForQuestionAnswering,
														    OPTForSequenceClassification,
														    OPTModel,
														    OPTPreTrainedModel,
														)

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_opt import TFOPTForCausalLM, TFOPTModel, TFOPTPreTrainedModel

							try:
														if not is_flax_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_flax_opt import FlaxOPTForCausalLM, FlaxOPTModel, FlaxOPTPreTrainedModel

else:
							import sys

							UpperCAmelCase_		:					List[str]          =  _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)










UpperCAmelCase_		:					Tuple          =  0  # The first color of the flag.
UpperCAmelCase_		:					Any          =  1  # The second color of the flag.
UpperCAmelCase_		:					str          =  2  # The third color of the flag.
UpperCAmelCase_		:					Tuple          =  (red, white, blue)




def 		lowerCAmelCase_ (						lowerCamelCase ):
				if not sequence:
								return []
				if len(lowerCamelCase ) == 1:
								return list(lowerCamelCase )
				__magic_name__						:						int										=0
				__magic_name__						:						str										=len(lowerCamelCase ) - 1
				__magic_name__						:						Optional[Any]										=0
				while mid <= high:
								if sequence[mid] == colors[0]:
												__magic_name__					,			__magic_name__						:						Tuple										=sequence[mid], sequence[low]
												low += 1
												mid += 1
								elif sequence[mid] == colors[1]:
												mid += 1
								elif sequence[mid] == colors[2]:
												__magic_name__					,			__magic_name__						:						Optional[Any]										=sequence[high], sequence[mid]
												high -= 1
								else:
												__magic_name__						:						Optional[int]										=F"The elements inside the sequence must contains only {colors} values"
												raise ValueError(lowerCamelCase )
				return sequence


if __name__ == "__main__":
							import doctest

							doctest.testmod()

							UpperCAmelCase_		:					List[Any]          =  input("Enter numbers separated by commas:\n").strip()
							UpperCAmelCase_		:					Optional[int]          =  [int(item.strip()) for item in user_input.split(",")]
							print(F"""{dutch_national_flag_sort(unsorted)}""")




