




"""simple docstring"""
from typing import TYPE_CHECKING

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


a_				:    Optional[Any]										=     {"configuration_xlnet": ["XLNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLNetConfig"]}

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

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

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							a_				:    Optional[int]										=     [
							    "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:
							a_				:    Dict										=     [
							    "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

							a_				:    Optional[Any]										=     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)









"""simple docstring"""
import random
from typing import Any





def 						UpperCAmelCase				(			A__:    list     )  ->     list[Any]:
			for _ in range(len(A__     )     ):
						__lowerCamelCase					:	List[Any]	       =				random.randint(0							,				len(A__     ) - 1     )
						__lowerCamelCase					:	Optional[Any]	       =				random.randint(0							,				len(A__     ) - 1     )
						__lowerCamelCase       ,      __lowerCamelCase					:	Any	       =				data[b], data[a]
			return data


if __name__ == "__main__":
					a_				:    Any										=     [0, 1, 2, 3, 4, 5, 6, 7]
					a_				:    int										=     ['''python''', '''says''', '''hello''', '''!''']
					print('''Fisher-Yates Shuffle:''')
					print('''List''', integers, strings)
					print('''FY Shuffle''', fisher_yates_shuffle(integers), fisher_yates_shuffle(strings))



