






"""simple docstring"""

from typing import TYPE_CHECKING

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


lowercase__          = {"""configuration_xlnet""": ["""XLNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """XLNetConfig"""]}

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

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

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowercase__          = [
					    """XLNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """XLNetForMultipleChoice""",
					    """XLNetForQuestionAnswering""",
					    """XLNetForQuestionAnsweringSimple""",
					    """XLNetForSequenceClassification""",
					    """XLNetForTokenClassification""",
					    """XLNetLMHeadModel""",
					    """XLNetModel""",
					    """XLNetPreTrainedModel""",
					    """load_tf_weights_in_xlnet""",
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowercase__          = [
					    """TF_XLNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """TFXLNetForMultipleChoice""",
					    """TFXLNetForQuestionAnsweringSimple""",
					    """TFXLNetForSequenceClassification""",
					    """TFXLNetForTokenClassification""",
					    """TFXLNetLMHeadModel""",
					    """TFXLNetMainLayer""",
					    """TFXLNetModel""",
					    """TFXLNetPreTrainedModel""",
					]


if TYPE_CHECKING:
					from .configuration_xlnet import XLNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLNetConfig

					try:
										if not is_sentencepiece_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_xlnet import XLNetTokenizer

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_xlnet_fast import XLNetTokenizerFast

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_xlnet import (
										    XLNET_PRETRAINED_MODEL_ARCHIVE_LIST,
										    XLNetForMultipleChoice,
										    XLNetForQuestionAnswering,
										    XLNetForQuestionAnsweringSimple,
										    XLNetForSequenceClassification,
										    XLNetForTokenClassification,
										    XLNetLMHeadModel,
										    XLNetModel,
										    XLNetPreTrainedModel,
										    load_tf_weights_in_xlnet,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_xlnet import (
										    TF_XLNET_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TFXLNetForMultipleChoice,
										    TFXLNetForQuestionAnsweringSimple,
										    TFXLNetForSequenceClassification,
										    TFXLNetForTokenClassification,
										    TFXLNetLMHeadModel,
										    TFXLNetMainLayer,
										    TFXLNetModel,
										    TFXLNetPreTrainedModel,
										)

else:
					import sys

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








"""simple docstring"""

lowercase__          = 0  # The first color of the flag.
lowercase__          = 1  # The second color of the flag.
lowercase__          = 2  # The third color of the flag.
lowercase__          = (red, white, blue)

def 		__lowerCamelCase	(  __UpperCamelCase       )						->    list:

		"""simple docstring"""







		if not sequence:
				return []
		if len(__UpperCamelCase       ) == 1:
				return list(__UpperCamelCase       )
		lowerCAmelCase_   :							Optional[Any]									=			0
		lowerCAmelCase_   :							List[Any]									=			len(__UpperCamelCase       ) - 1
		lowerCAmelCase_   :							Union[str, Any]									=			0
		while mid <= high:
				if sequence[mid] == colors[0]:
						lowerCAmelCase_				,	lowerCAmelCase_   :							Any									=			sequence[mid], sequence[low]
						low += 1
						mid += 1
				elif sequence[mid] == colors[1]:
						mid += 1
				elif sequence[mid] == colors[2]:
						lowerCAmelCase_				,	lowerCAmelCase_   :							str									=			sequence[high], sequence[mid]
						high -= 1
				else:
						lowerCAmelCase_   :							str									=			f'''The elements inside the sequence must contains only {colors} values'''
						raise ValueError(__UpperCamelCase       )
		return sequence


if __name__ == "__main__":
					import doctest

					doctest.testmod()

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