'''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    a__				:






					def __init__(			self		:		Dict  ,    a		:		int  ,    ):





									"""simple docstring"""



									__lowerCamelCase          =  parent
									__lowerCamelCase          =  13
									__lowerCamelCase          =  7
									__lowerCamelCase          =  30
									__lowerCamelCase          =  self.seq_length + self.mem_len
									__lowerCamelCase          =  15
									__lowerCamelCase          =  True
									__lowerCamelCase          =  True
									__lowerCamelCase          =  99
									__lowerCamelCase          =  [10, 50, 80]
									__lowerCamelCase          =  32
									__lowerCamelCase          =  32
									__lowerCamelCase          =  4
									__lowerCamelCase          =  8
									__lowerCamelCase          =  1_28
									__lowerCamelCase          =  2
									__lowerCamelCase          =  2
									__lowerCamelCase          =  None
									__lowerCamelCase          =  1
									__lowerCamelCase          =  0
									__lowerCamelCase          =  3
									__lowerCamelCase          =  self.vocab_size - 1
									__lowerCamelCase          =  0.01






					def        SCREAMING_SNAKE_CASE__       (			self		:		Tuple   ):





									"""simple docstring"""



									__lowerCamelCase          =  ids_tensor([self.batch_size, self.seq_length]  ,    self.vocab_size   )
									__lowerCamelCase          =  ids_tensor([self.batch_size, self.seq_length]  ,    self.vocab_size   )

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

									__lowerCamelCase          =  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        SCREAMING_SNAKE_CASE__       (			self		:		Optional[Any]   ):





									"""simple docstring"""



									random.seed(self.seed   )
									tf.random.set_seed(self.seed   )






					def        SCREAMING_SNAKE_CASE__       (			self		:		Optional[Any]  ,    a		:		List[Any]  ,    a		:		List[str]  ,    a		:		Any  ,    a		:		Any   ):





									"""simple docstring"""



									__lowerCamelCase          =  TFTransfoXLModel(a   )

									__lowerCamelCase     ,  __lowerCamelCase          =  model(a   ).to_tuple()

									__lowerCamelCase          =  {'''input_ids''': input_ids_a, '''mems''': mems_a}

									__lowerCamelCase     ,  __lowerCamelCase          =  model(a   ).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        SCREAMING_SNAKE_CASE__       (			self		:		Optional[int]  ,    a		:		int  ,    a		:		Optional[Any]  ,    a		:		Optional[Any]  ,    a		:		List[str]   ):





									"""simple docstring"""



									__lowerCamelCase          =  TFTransfoXLLMHeadModel(a   )

									__lowerCamelCase     ,  __lowerCamelCase          =  model(a   ).to_tuple()

									__lowerCamelCase          =  {'''input_ids''': input_ids_a, '''labels''': lm_labels}
									__lowerCamelCase     ,  __lowerCamelCase          =  model(a   ).to_tuple()

									__lowerCamelCase     ,  __lowerCamelCase          =  model([input_ids_a, mems_a]   ).to_tuple()

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

									__lowerCamelCase     ,  __lowerCamelCase          =  model(a   ).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        SCREAMING_SNAKE_CASE__       (			self		:		List[str]  ,    a		:		List[str]  ,    a		:		Dict  ,    a		:		Any  ,    a		:		List[str]   ):





									"""simple docstring"""



									__lowerCamelCase          =  TFTransfoXLForSequenceClassification(a   )
									__lowerCamelCase          =  model(a   )
									self.parent.assertEqual(result.logits.shape  ,    (self.batch_size, self.num_labels)   )






					def        SCREAMING_SNAKE_CASE__       (			self		:		List[str]   ):





									"""simple docstring"""



									__lowerCamelCase          =  self.prepare_config_and_inputs()
									((__lowerCamelCase)     ,  (__lowerCamelCase)     ,  (__lowerCamelCase)     ,  (__lowerCamelCase))          =  config_and_inputs
									__lowerCamelCase          =  {'''input_ids''': input_ids_a}
									return config, inputs_dict




@require_tf
class    a__				(       UpperCAmelCase__							,       UpperCAmelCase__							,       unittest.TestCase			):
					lowerCamelCase  :					Optional[int]							=(
					    (TFTransfoXLModel, TFTransfoXLLMHeadModel, TFTransfoXLForSequenceClassification) if is_tf_available() else ()
					)
					lowerCamelCase  :					Optional[int]							=() if is_tf_available() else ()
					lowerCamelCase  :					List[Any]							=(
					    {
					        "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  :					str							=False
					lowerCamelCase  :					Tuple							=False
					lowerCamelCase  :					List[str]							=False
					lowerCamelCase  :					Optional[Any]							=False






					def        SCREAMING_SNAKE_CASE__       (			self		:		Union[str, Any]  ,    a		:		Union[str, Any]  ,    a		:		Any  ,    a		:		Tuple  ,    a		:		Tuple  ,    a		:		Union[str, Any]   ):





									"""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        SCREAMING_SNAKE_CASE__       (			self		:		List[str]   ):





									"""simple docstring"""



									__lowerCamelCase          =  TFTransfoXLModelTester(self   )
									__lowerCamelCase          =  ConfigTester(self  ,    config_class=a  ,    d_embed=37   )






					def        SCREAMING_SNAKE_CASE__       (			self		:		Optional[Any]   ):





									"""simple docstring"""



									self.config_tester.run_common_tests()






					def        SCREAMING_SNAKE_CASE__       (			self		:		Tuple   ):





									"""simple docstring"""



									self.model_tester.set_seed()
									__lowerCamelCase          =  self.model_tester.prepare_config_and_inputs()
									self.model_tester.create_and_check_transfo_xl_model(*a   )






					def        SCREAMING_SNAKE_CASE__       (			self		:		str   ):





									"""simple docstring"""



									self.model_tester.set_seed()
									__lowerCamelCase          =  self.model_tester.prepare_config_and_inputs()
									self.model_tester.create_and_check_transfo_xl_lm_head(*a   )






					def        SCREAMING_SNAKE_CASE__       (			self		:		Optional[Any]   ):





									"""simple docstring"""



									__lowerCamelCase          =  self.model_tester.prepare_config_and_inputs()
									self.model_tester.create_and_check_transfo_xl_for_sequence_classification(*a   )






					def        SCREAMING_SNAKE_CASE__       (			self		:		Union[str, Any]   ):





									"""simple docstring"""



									__lowerCamelCase     ,  __lowerCamelCase          =  self.model_tester.prepare_config_and_inputs_for_common()
									__lowerCamelCase          =  [TFTransfoXLForSequenceClassification]

									for model_class in self.all_model_classes:
													__lowerCamelCase          =  model_class(a   )
													assert isinstance(model.get_input_embeddings()  ,    tf.keras.layers.Layer   )
													if model_class in list_other_models_with_output_ebd:
																	__lowerCamelCase          =  model.get_output_embeddings()
																	assert isinstance(a  ,    tf.keras.layers.Layer   )
																	__lowerCamelCase          =  model.get_bias()
																	assert name is None
													else:
																	__lowerCamelCase          =  model.get_output_embeddings()
																	assert x is None
																	__lowerCamelCase          =  model.get_bias()
																	assert name is None






					def        SCREAMING_SNAKE_CASE__       (			self		:		Any   ):





									"""simple docstring"""



									pass






					@slow
					def        SCREAMING_SNAKE_CASE__       (			self		:		Union[str, Any]   ):





									"""simple docstring"""



									for model_name in TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
													__lowerCamelCase          =  TFTransfoXLModel.from_pretrained(a   )
													self.assertIsNotNone(a   )






					@unittest.skip(reason='''This model doesn\'t play well with fit() due to not returning a single loss.'''   )
					def        SCREAMING_SNAKE_CASE__       (			self		:		List[str]   ):





									"""simple docstring"""



									pass




@require_tf
class    a__				(       unittest.TestCase			):






					@unittest.skip('''Skip test until #12651 is resolved.'''   )
					@slow
					def        SCREAMING_SNAKE_CASE__       (			self		:		Union[str, Any]   ):





									"""simple docstring"""



									__lowerCamelCase          =  TFTransfoXLLMHeadModel.from_pretrained('''transfo-xl-wt103'''   )
									# fmt: off
									__lowerCamelCase          =  tf.convert_to_tensor([[33,12_97,2,1,10_09,4,11_09,1_17_39,47_62,3_58,5,25,2_45,22,17_06,17,2_00_98,5,32_15,21,37,11_10,3,13,10_41,4,24,6_03,4_90,2,7_14_77,2_00_98,10_44_47,2,2_09_61,1,26_04,4,1,3_29,3,62_24,8_31,1_60_02,2,8,6_03,7_89_67,2_95_46,23,8_03,20,25,4_16,5,8,2_32,4,2_77,6,18_55,46_01,3,2_95_46,54,8,36_09,5,5_72_11,49,4,1,2_77,18,8,17_55,1_56_91,3,3_41,25,4_16,6_93,4_25_73,71,17,4_01,94,31,1_79_19,2,2_95_46,78_73,18,1,4_35,23,1_10_11,7_55,5,51_67,3,79_83,98,84,2,2_95_46,32_67,8,36_09,4,1,48_65,10_75,2,60_87,71,6,3_46,8,58_54,3,2_95_46,8_24,14_00,18_68,2,19,1_60,2,3_11,8,54_96,2,2_09_20,17,25,1_50_97,3,24,24,0]]  ,    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
									__lowerCamelCase          =  [33,12_97,2,1,10_09,4,11_09,1_17_39,47_62,3_58,5,25,2_45,22,17_06,17,2_00_98,5,32_15,21,37,11_10,3,13,10_41,4,24,6_03,4_90,2,7_14_77,2_00_98,10_44_47,2,2_09_61,1,26_04,4,1,3_29,3,62_24,8_31,1_60_02,2,8,6_03,7_89_67,2_95_46,23,8_03,20,25,4_16,5,8,2_32,4,2_77,6,18_55,46_01,3,2_95_46,54,8,36_09,5,5_72_11,49,4,1,2_77,18,8,17_55,1_56_91,3,3_41,25,4_16,6_93,4_25_73,71,17,4_01,94,31,1_79_19,2,2_95_46,78_73,18,1,4_35,23,1_10_11,7_55,5,51_67,3,79_83,98,84,2,2_95_46,32_67,8,36_09,4,1,48_65,10_75,2,60_87,71,6,3_46,8,58_54,3,2_95_46,8_24,14_00,18_68,2,19,1_60,2,3_11,8,54_96,2,2_09_20,17,25,1_50_97,3,24,24,0,33,1,18_57,2,1,10_09,4,11_09,1_17_39,47_62,3_58,5,25,2_45,28,11_10,3,13,10_41,4,24,6_03,4_90,2,7_14_77,2_00_98,10_44_47,2,2_09_61,1,26_04,4,1,3_29,3,0]  # 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>

									__lowerCamelCase          =  model.generate(a  ,    max_length=2_00  ,    do_sample=a   )
									self.assertListEqual(output_ids[0].numpy().tolist()  ,    a   )

'''simple docstring'''




def __lowerCAmelCase			(							UpperCamelCase__    )     ->   str:
    __lowerCamelCase          =  []
    __lowerCamelCase          =  set({'''(''', '''[''', '''{'''}    )
    __lowerCamelCase          =  set({''')''', ''']''', '''}'''}    )
    __lowerCamelCase          =  {'''{''': '''}''', '''[''': ''']''', '''(''': ''')'''}

    for i in range(len(UpperCamelCase__    )    ):
        if s[i] in open_brackets:
            stack.append(s[i]    )

        elif s[i] in closed_brackets and (
            len(UpperCamelCase__    ) == 0 or (len(UpperCamelCase__    ) > 0 and open_to_closed[stack.pop()] != s[i])
        ):
            return False

    return len(UpperCamelCase__    ) == 0






def __lowerCAmelCase			(							)     ->   Union[str, Any]:
    __lowerCamelCase          =  input('''Enter sequence of brackets: '''    )
    if is_balanced(UpperCamelCase__    ):
        print(UpperCamelCase__    ,  '''is balanced'''    )
    else:
        print(UpperCamelCase__    ,  '''is not balanced'''    )


if __name__ == "__main__":
  main()
