

'''simple docstring'''





def 				_lowerCAmelCase			(   __magic_name__						:     str						)				->  str:
						lowercase :							Dict    		=0

						# if input_string is "aba" than new_input_string become "a|b|a"
						lowercase :							Any    		=''''''
						lowercase :							Optional[int]    		=''''''

						# append each character + "|" in new_string for range(0, length-1)
						for i in input_string[: len(__magic_name__						) - 1]:
												new_input_string += i + "|"
						# append last character
						new_input_string += input_string[-1]

						# we will store the starting and ending of previous furthest ending palindromic
						# substring
						lowercase		,	lowercase :							Tuple    		=0, 0

						# length[i] shows the length of palindromic substring with center i
						lowercase :							Any    		=[1 for i in range(len(__magic_name__						)						)]

						# for each character in new_string find corresponding palindromic string
						lowercase :							Dict    		=0
						for j in range(len(__magic_name__						)						):
												lowercase :							Optional[int]    		=1 if j > r else min(length[l + r - j] // 2   , r - j + 1						)
												while (
												    j - k >= 0
												    and j + k < len(__magic_name__						)
												    and new_input_string[k + j] == new_input_string[j - k]
												):
																		k += 1

												lowercase :							Optional[Any]    		=2 * k - 1

												# does this string is ending after the previously explored end (that is r) ?
												# if yes the update the new r to the last index of this
												if j + k - 1 > r:
																		lowercase :							Optional[Any]    		=j - k + 1  # noqa: E741
																		lowercase :							Tuple    		=j + k - 1

												# update max_length and start position
												if max_length < length[j]:
																		lowercase :							int    		=length[j]
																		lowercase :							Optional[Any]    		=j

    # create that string
						lowercase :							Dict    		=new_input_string[start - max_length // 2 : start + max_length // 2 + 1]
						for i in s:
												if i != "|":
																		output_string += i

						return output_string


if __name__ == "__main__":
							import doctest

							doctest.testmod()








'''simple docstring'''





from __future__ import annotations

import random
import unittest

from transformers import TransfoXLConfig, is_tf_available
from transformers.testing_utils import require_tf, slow

from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
from ...test_pipeline_mixin import PipelineTesterMixin


if is_tf_available():
							import tensorflow as tf

							from transformers import (
							    TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST,
							    TFTransfoXLForSequenceClassification,
							    TFTransfoXLLMHeadModel,
							    TFTransfoXLModel,
							)





class 		__SCREAMING_SNAKE_CASE							:







				def __init__(       self     :		List[str]		,					UpperCAmelCase__     :		Dict		,					):
										'''simple docstring'''
										lowercase :							Any    		=parent
										lowercase :							Optional[int]    		=13
										lowercase :							Union[str, Any]    		=7
										lowercase :							str    		=30
										lowercase :							Optional[int]    		=self.seq_length + self.mem_len
										lowercase :							Dict    		=15
										lowercase :							List[str]    		=True
										lowercase :							Optional[int]    		=True
										lowercase :							Tuple    		=99
										lowercase :							str    		=[10, 50, 80]
										lowercase :							List[Any]    		=32
										lowercase :							Optional[int]    		=32
										lowercase :							int    		=4
										lowercase :							Any    		=8
										lowercase :							List[Any]    		=128
										lowercase :							List[str]    		=2
										lowercase :							Tuple    		=2
										lowercase :							int    		=None
										lowercase :							Optional[int]    		=1
										lowercase :							int    		=0
										lowercase :							List[str]    		=3
										lowercase :							str    		=self.vocab_size - 1
										lowercase :							Tuple    		=0.01







				def  lowerCamelCase_	(       self     :		List[Any]   ):
										'''simple docstring'''
										lowercase :							str    		=ids_tensor([self.batch_size, self.seq_length]		,					self.vocab_size   )
										lowercase :							Tuple    		=ids_tensor([self.batch_size, self.seq_length]		,					self.vocab_size   )

										lowercase :							str    		=None
										if self.use_labels:
																lowercase :							Tuple    		=ids_tensor([self.batch_size, self.seq_length]		,					self.vocab_size   )

										lowercase :							Union[str, Any]    		=TransfoXLConfig(
										    vocab_size=self.vocab_size		,					mem_len=self.mem_len		,					clamp_len=self.clamp_len		,					cutoffs=self.cutoffs		,					d_model=self.hidden_size		,					d_embed=self.d_embed		,					n_head=self.num_attention_heads		,					d_head=self.d_head		,					d_inner=self.d_inner		,					div_val=self.div_val		,					n_layer=self.num_hidden_layers		,					eos_token_id=self.eos_token_id		,					pad_token_id=self.vocab_size - 1		,					init_range=self.init_range		,					num_labels=self.num_labels		,					)

										return (config, input_ids_a, input_ids_a, lm_labels)







				def  lowerCamelCase_	(       self     :		Union[str, Any]   ):
										'''simple docstring'''
										random.seed(self.seed   )
										tf.random.set_seed(self.seed   )







				def  lowerCamelCase_	(       self     :		Union[str, Any]		,					UpperCAmelCase__     :		Optional[Any]		,					UpperCAmelCase__     :		Dict		,					UpperCAmelCase__     :		List[str]		,					UpperCAmelCase__     :		List[str]   ):
										'''simple docstring'''
										lowercase :							Tuple    		=TFTransfoXLModel(UpperCAmelCase__   )

										lowercase		,	lowercase :							Optional[Any]    		=model(UpperCAmelCase__   ).to_tuple()

										lowercase :							List[str]    		={'''input_ids''': input_ids_a, '''mems''': mems_a}

										lowercase		,	lowercase :							Any    		=model(UpperCAmelCase__   ).to_tuple()

										self.parent.assertEqual(hidden_states_a.shape		,					(self.batch_size, self.seq_length, self.hidden_size)   )
										self.parent.assertEqual(hidden_states_a.shape		,					(self.batch_size, self.seq_length, self.hidden_size)   )
										self.parent.assertListEqual(
										    [mem.shape for mem in mems_a]		,					[(self.mem_len, self.batch_size, self.hidden_size)] * self.num_hidden_layers		,					)
										self.parent.assertListEqual(
										    [mem.shape for mem in mems_a]		,					[(self.mem_len, self.batch_size, self.hidden_size)] * self.num_hidden_layers		,					)







				def  lowerCamelCase_	(       self     :		int		,					UpperCAmelCase__     :		List[str]		,					UpperCAmelCase__     :		str		,					UpperCAmelCase__     :		Dict		,					UpperCAmelCase__     :		int   ):
										'''simple docstring'''
										lowercase :							int    		=TFTransfoXLLMHeadModel(UpperCAmelCase__   )

										lowercase		,	lowercase :							Tuple    		=model(UpperCAmelCase__   ).to_tuple()

										lowercase :							Optional[Any]    		={'''input_ids''': input_ids_a, '''labels''': lm_labels}
										lowercase		,	lowercase :							Optional[int]    		=model(UpperCAmelCase__   ).to_tuple()

										lowercase		,	lowercase :							List[str]    		=model([input_ids_a, mems_a]   ).to_tuple()

										lowercase :							int    		={'''input_ids''': input_ids_a, '''mems''': mems_a, '''labels''': lm_labels}

										lowercase		,	lowercase :							str    		=model(UpperCAmelCase__   ).to_tuple()

										self.parent.assertEqual(lm_logits_a.shape		,					(self.batch_size, self.seq_length, self.vocab_size)   )
										self.parent.assertListEqual(
										    [mem.shape for mem in mems_a]		,					[(self.mem_len, self.batch_size, self.hidden_size)] * self.num_hidden_layers		,					)

										self.parent.assertEqual(lm_logits_a.shape		,					(self.batch_size, self.seq_length, self.vocab_size)   )
										self.parent.assertListEqual(
										    [mem.shape for mem in mems_a]		,					[(self.mem_len, self.batch_size, self.hidden_size)] * self.num_hidden_layers		,					)







				def  lowerCamelCase_	(       self     :		str		,					UpperCAmelCase__     :		int		,					UpperCAmelCase__     :		Any		,					UpperCAmelCase__     :		List[str]		,					UpperCAmelCase__     :		Union[str, Any]   ):
										'''simple docstring'''
										lowercase :							Optional[int]    		=TFTransfoXLForSequenceClassification(UpperCAmelCase__   )
										lowercase :							Union[str, Any]    		=model(UpperCAmelCase__   )
										self.parent.assertEqual(result.logits.shape		,					(self.batch_size, self.num_labels)   )







				def  lowerCamelCase_	(       self     :		List[str]   ):
										'''simple docstring'''
										lowercase :							List[Any]    		=self.prepare_config_and_inputs()
										((lowercase)		,	(lowercase)		,	(lowercase)		,	(lowercase)) :							Optional[Any]    		=config_and_inputs
										lowercase :							Union[str, Any]    		={'''input_ids''': input_ids_a}
										return config, inputs_dict





@require_tf
class 		__SCREAMING_SNAKE_CASE							(			lowercase__						,							lowercase__						,							unittest.TestCase      ):
				lowerCamelCase_		       =    (
				    (TFTransfoXLModel, TFTransfoXLLMHeadModel, TFTransfoXLForSequenceClassification) if is_tf_available() else ()
				)
				lowerCamelCase_		       =    () if is_tf_available() else ()
				lowerCamelCase_		       =    (
				    {
				        'feature-extraction': TFTransfoXLModel,
				        'text-classification': TFTransfoXLForSequenceClassification,
				        'text-generation': TFTransfoXLLMHeadModel,
				        'zero-shot': TFTransfoXLForSequenceClassification,
				    }
				    if is_tf_available()
				    else {}
				)
				# TODO: add this test when TFTransfoXLLMHead has a linear output layer implemented
				lowerCamelCase_		       =    False
				lowerCamelCase_		       =    False
				lowerCamelCase_		       =    False
				lowerCamelCase_		       =    False







				def  lowerCamelCase_	(       self     :		Dict		,					UpperCAmelCase__     :		List[Any]		,					UpperCAmelCase__     :		Optional[int]		,					UpperCAmelCase__     :		int		,					UpperCAmelCase__     :		Optional[int]		,					UpperCAmelCase__     :		int   ):
										'''simple docstring'''
										if pipeline_test_casse_name == "TextGenerationPipelineTests":
																# Get `ValueError: AttributeError: 'NoneType' object has no attribute 'new_ones'` or `AssertionError`.
																# `TransfoXLConfig` was never used in pipeline tests: cannot create a simple
																# tokenizer.
																return True

										return False







				def  lowerCamelCase_	(       self     :		int   ):
										'''simple docstring'''
										lowercase :							Any    		=TFTransfoXLModelTester(self   )
										lowercase :							Optional[int]    		=ConfigTester(self		,					config_class=UpperCAmelCase__		,					d_embed=37   )







				def  lowerCamelCase_	(       self     :		Any   ):
										'''simple docstring'''
										self.config_tester.run_common_tests()







				def  lowerCamelCase_	(       self     :		Optional[int]   ):
										'''simple docstring'''
										self.model_tester.set_seed()
										lowercase :							List[str]    		=self.model_tester.prepare_config_and_inputs()
										self.model_tester.create_and_check_transfo_xl_model(*UpperCAmelCase__   )







				def  lowerCamelCase_	(       self     :		List[str]   ):
										'''simple docstring'''
										self.model_tester.set_seed()
										lowercase :							Any    		=self.model_tester.prepare_config_and_inputs()
										self.model_tester.create_and_check_transfo_xl_lm_head(*UpperCAmelCase__   )







				def  lowerCamelCase_	(       self     :		List[Any]   ):
										'''simple docstring'''
										lowercase :							Dict    		=self.model_tester.prepare_config_and_inputs()
										self.model_tester.create_and_check_transfo_xl_for_sequence_classification(*UpperCAmelCase__   )







				def  lowerCamelCase_	(       self     :		Optional[Any]   ):
										'''simple docstring'''
										lowercase		,	lowercase :							Tuple    		=self.model_tester.prepare_config_and_inputs_for_common()
										lowercase :							int    		=[TFTransfoXLForSequenceClassification]

										for model_class in self.all_model_classes:
																lowercase :							str    		=model_class(UpperCAmelCase__   )
																assert isinstance(model.get_input_embeddings()		,					tf.keras.layers.Layer   )
																if model_class in list_other_models_with_output_ebd:
																						lowercase :							Union[str, Any]    		=model.get_output_embeddings()
																						assert isinstance(UpperCAmelCase__		,					tf.keras.layers.Layer   )
																						lowercase :							Any    		=model.get_bias()
																						assert name is None
																else:
																						lowercase :							Optional[int]    		=model.get_output_embeddings()
																						assert x is None
																						lowercase :							Optional[int]    		=model.get_bias()
																						assert name is None







				def  lowerCamelCase_	(       self     :		Any   ):
										'''simple docstring'''
										# TODO JP: Make TransfoXL XLA compliant
										pass







				@slow
				def  lowerCamelCase_	(       self     :		Union[str, Any]   ):
										'''simple docstring'''
										for model_name in TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
																lowercase :							int    		=TFTransfoXLModel.from_pretrained(UpperCAmelCase__   )
																self.assertIsNotNone(UpperCAmelCase__   )







				@unittest.skip(reason='''This model doesn\'t play well with fit() due to not returning a single loss.'''   )
				def  lowerCamelCase_	(       self     :		int   ):
										'''simple docstring'''
										pass





@require_tf
class 		__SCREAMING_SNAKE_CASE							(			unittest.TestCase      ):







				@unittest.skip('''Skip test until #12651 is resolved.'''   )
				@slow
				def  lowerCamelCase_	(       self     :		Tuple   ):
										'''simple docstring'''
										lowercase :							Optional[Any]    		=TFTransfoXLLMHeadModel.from_pretrained('''transfo-xl-wt103'''   )
										# fmt: off
										lowercase :							Tuple    		=tf.convert_to_tensor([[33,1297,2,1,1009,4,1109,11739,4762,358,5,25,245,22,1706,17,20098,5,3215,21,37,1110,3,13,1041,4,24,603,490,2,71477,20098,104447,2,20961,1,2604,4,1,329,3,6224,831,16002,2,8,603,78967,29546,23,803,20,25,416,5,8,232,4,277,6,1855,4601,3,29546,54,8,3609,5,57211,49,4,1,277,18,8,1755,15691,3,341,25,416,693,42573,71,17,401,94,31,17919,2,29546,7873,18,1,435,23,11011,755,5,5167,3,7983,98,84,2,29546,3267,8,3609,4,1,4865,1075,2,6087,71,6,346,8,5854,3,29546,824,1400,1868,2,19,160,2,311,8,5496,2,20920,17,25,15097,3,24,24,0]]		,					dtype=tf.intaa   )  # noqa: E231
										# fmt: on
										#  In 1991 , the remains of Russian Tsar Nicholas II and his family
										#  ( except for Alexei and Maria ) are discovered .
										#  The voice of Nicholas's young son , Tsarevich Alexei Nikolaevich , narrates the
										#  remainder of the story . 1883 Western Siberia ,
										#  a young Grigori Rasputin is asked by his father and a group of men to perform magic .
										#  Rasputin has a vision and denounces one of the men as a horse thief . Although his
										#  father initially slaps him for making such an accusation , Rasputin watches as the
										#  man is chased outside and beaten . Twenty years later , Rasputin sees a vision of
										#  the Virgin Mary , prompting him to become a priest . Rasputin quickly becomes famous ,
										#  with people , even a bishop , begging for his blessing . <eod> </s> <eos>

										# fmt: off
										lowercase :							Optional[int]    		=[33,1297,2,1,1009,4,1109,11739,4762,358,5,25,245,22,1706,17,20098,5,3215,21,37,1110,3,13,1041,4,24,603,490,2,71477,20098,104447,2,20961,1,2604,4,1,329,3,6224,831,16002,2,8,603,78967,29546,23,803,20,25,416,5,8,232,4,277,6,1855,4601,3,29546,54,8,3609,5,57211,49,4,1,277,18,8,1755,15691,3,341,25,416,693,42573,71,17,401,94,31,17919,2,29546,7873,18,1,435,23,11011,755,5,5167,3,7983,98,84,2,29546,3267,8,3609,4,1,4865,1075,2,6087,71,6,346,8,5854,3,29546,824,1400,1868,2,19,160,2,311,8,5496,2,20920,17,25,15097,3,24,24,0,33,1,1857,2,1,1009,4,1109,11739,4762,358,5,25,245,28,1110,3,13,1041,4,24,603,490,2,71477,20098,104447,2,20961,1,2604,4,1,329,3,0]  # noqa: E231
										# fmt: on
										#  In 1991, the remains of Russian Tsar Nicholas II and his family (
										#  except for Alexei and Maria ) are discovered. The voice of young son,
										#  Tsarevich Alexei Nikolaevich, narrates the remainder of the story.
										#  1883 Western Siberia, a young Grigori Rasputin is asked by his father
										#  and a group of men to perform magic. Rasputin has a vision and
										#  denounces one of the men as a horse thief. Although his father initially
										#  slaps him for making such an accusation, Rasputin watches as the man
										#  is chased outside and beaten. Twenty years later, Rasputin sees a vision
										#  of the Virgin Mary, prompting him to become a priest.
										#  Rasputin quickly becomes famous, with people, even a bishop, begging for
										#  his blessing. <unk> <unk> <eos> In the 1990s, the remains of Russian Tsar
										# Nicholas II and his family were discovered. The voice of <unk> young son,
										# Tsarevich Alexei Nikolaevich, narrates the remainder of the story.<eos>

										lowercase :							int    		=model.generate(UpperCAmelCase__		,					max_length=200		,					do_sample=UpperCAmelCase__   )
										self.assertListEqual(output_ids[0].numpy().tolist()		,					UpperCAmelCase__   )





