


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 			_lowercase :


       """simple docstring"""




       def __init__(   self							:			List[Any]					,      __lowerCamelCase							:			str					,      ):


             '''simple docstring'''



             lowerCamelCase__		:				str    =  parent
             lowerCamelCase__		:				Union[str, Any]    =  13
             lowerCamelCase__		:				int    =  7
             lowerCamelCase__		:				str    =  30
             lowerCamelCase__		:				Optional[Any]    =  self.seq_length + self.mem_len
             lowerCamelCase__		:				str    =  15
             lowerCamelCase__		:				int    =  True
             lowerCamelCase__		:				int    =  True
             lowerCamelCase__		:				int    =  99
             lowerCamelCase__		:				Dict    =  [10, 50, 80]
             lowerCamelCase__		:				Optional[Any]    =  32
             lowerCamelCase__		:				str    =  32
             lowerCamelCase__		:				List[str]    =  4
             lowerCamelCase__		:				str    =  8
             lowerCamelCase__		:				int    =  128
             lowerCamelCase__		:				str    =  2
             lowerCamelCase__		:				Optional[int]    =  2
             lowerCamelCase__		:				Optional[Any]    =  None
             lowerCamelCase__		:				List[Any]    =  1
             lowerCamelCase__		:				Optional[Any]    =  0
             lowerCamelCase__		:				Optional[int]    =  3
             lowerCamelCase__		:				Optional[Any]    =  self.vocab_size - 1
             lowerCamelCase__		:				Dict    =  0.0_1





       def 						lowerCAmelCase     (   self							:			int       ):


             '''simple docstring'''



             lowerCamelCase__		:				int    =  ids_tensor([self.batch_size, self.seq_length]					,      self.vocab_size       )
             lowerCamelCase__		:				Any    =  ids_tensor([self.batch_size, self.seq_length]					,      self.vocab_size       )

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

             lowerCamelCase__		:				int    =  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							:			Optional[int]       ):


             '''simple docstring'''



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





       def 						lowerCAmelCase     (   self							:			int					,      __lowerCamelCase							:			int					,      __lowerCamelCase							:			List[str]					,      __lowerCamelCase							:			str					,      __lowerCamelCase							:			Union[str, Any]       ):


             '''simple docstring'''



             lowerCamelCase__		:				Optional[int]    =  TFTransfoXLModel(__lowerCamelCase       )

             lowerCamelCase__    ,   lowerCamelCase__		:				Optional[int]    =  model(__lowerCamelCase       ).to_tuple()

             lowerCamelCase__		:				List[Any]    =  {"input_ids": input_ids_a, "mems": mems_a}

             lowerCamelCase__    ,   lowerCamelCase__		:				Optional[int]    =  model(__lowerCamelCase       ).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							:			str					,      __lowerCamelCase							:			Union[str, Any]					,      __lowerCamelCase							:			Dict					,      __lowerCamelCase							:			int					,      __lowerCamelCase							:			List[Any]       ):


             '''simple docstring'''



             lowerCamelCase__		:				List[str]    =  TFTransfoXLLMHeadModel(__lowerCamelCase       )

             lowerCamelCase__    ,   lowerCamelCase__		:				int    =  model(__lowerCamelCase       ).to_tuple()

             lowerCamelCase__		:				Tuple    =  {"input_ids": input_ids_a, "labels": lm_labels}
             lowerCamelCase__    ,   lowerCamelCase__		:				Union[str, Any]    =  model(__lowerCamelCase       ).to_tuple()

             lowerCamelCase__    ,   lowerCamelCase__		:				Any    =  model([input_ids_a, mems_a]       ).to_tuple()

             lowerCamelCase__		:				List[str]    =  {"input_ids": input_ids_a, "mems": mems_a, "labels": lm_labels}

             lowerCamelCase__    ,   lowerCamelCase__		:				List[str]    =  model(__lowerCamelCase       ).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							:			Dict					,      __lowerCamelCase							:			Dict					,      __lowerCamelCase							:			Any					,      __lowerCamelCase							:			Optional[Any]					,      __lowerCamelCase							:			Optional[int]       ):


             '''simple docstring'''



             lowerCamelCase__		:				str    =  TFTransfoXLForSequenceClassification(__lowerCamelCase       )
             lowerCamelCase__		:				Union[str, Any]    =  model(__lowerCamelCase       )
             self.parent.assertEqual(result.logits.shape					,      (self.batch_size, self.num_labels)       )





       def 						lowerCAmelCase     (   self							:			Dict       ):


             '''simple docstring'''



             lowerCamelCase__		:				Dict    =  self.prepare_config_and_inputs()
             ((lowerCamelCase__)    ,   (lowerCamelCase__)    ,   (lowerCamelCase__)    ,   (lowerCamelCase__))		:				Optional[Any]    =  config_and_inputs
             lowerCamelCase__		:				Tuple    =  {"input_ids": input_ids_a}
             return config, inputs_dict







@require_tf
class 			_lowercase (							lowercase__							,  lowercase__							,  unittest.TestCase):


       """simple docstring"""




       A__											=			(
           (TFTransfoXLModel, TFTransfoXLLMHeadModel, TFTransfoXLForSequenceClassification) if is_tf_available() else ()
       )
       A__											=			() if is_tf_available() else ()
       A__											=			(
           {
               "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
       A__											=			False
       A__											=			False
       A__											=			False
       A__											=			False





       def 						lowerCAmelCase     (   self							:			str					,      __lowerCamelCase							:			Union[str, Any]					,      __lowerCamelCase							:			List[str]					,      __lowerCamelCase							:			Union[str, Any]					,      __lowerCamelCase							:			int					,      __lowerCamelCase							:			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 						lowerCAmelCase     (   self							:			str       ):


             '''simple docstring'''



             lowerCamelCase__		:				int    =  TFTransfoXLModelTester(self       )
             lowerCamelCase__		:				Dict    =  ConfigTester(self					,      config_class=__lowerCamelCase					,      d_embed=37       )





       def 						lowerCAmelCase     (   self							:			str       ):


             '''simple docstring'''



             self.config_tester.run_common_tests()





       def 						lowerCAmelCase     (   self							:			List[str]       ):


             '''simple docstring'''



             self.model_tester.set_seed()
             lowerCamelCase__		:				int    =  self.model_tester.prepare_config_and_inputs()
             self.model_tester.create_and_check_transfo_xl_model(*__lowerCamelCase       )





       def 						lowerCAmelCase     (   self							:			Optional[int]       ):


             '''simple docstring'''



             self.model_tester.set_seed()
             lowerCamelCase__		:				Dict    =  self.model_tester.prepare_config_and_inputs()
             self.model_tester.create_and_check_transfo_xl_lm_head(*__lowerCamelCase       )





       def 						lowerCAmelCase     (   self							:			Optional[int]       ):


             '''simple docstring'''



             lowerCamelCase__		:				Tuple    =  self.model_tester.prepare_config_and_inputs()
             self.model_tester.create_and_check_transfo_xl_for_sequence_classification(*__lowerCamelCase       )





       def 						lowerCAmelCase     (   self							:			int       ):


             '''simple docstring'''



             lowerCamelCase__    ,   lowerCamelCase__		:				Tuple    =  self.model_tester.prepare_config_and_inputs_for_common()
             lowerCamelCase__		:				Any    =  [TFTransfoXLForSequenceClassification]

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





       def 						lowerCAmelCase     (   self							:			int       ):


             '''simple docstring'''



             pass





       @slow
       def 						lowerCAmelCase     (   self							:			str       ):


             '''simple docstring'''



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





       @unittest.skip(reason="This model doesn't play well with fit() due to not returning a single loss."       )
       def 						lowerCAmelCase     (   self							:			Optional[Any]       ):


             '''simple docstring'''



             pass







@require_tf
class 			_lowercase (							unittest.TestCase):


       """simple docstring"""




       @unittest.skip("Skip test until #12651 is resolved."       )
       @slow
       def 						lowerCAmelCase     (   self							:			Tuple       ):


             '''simple docstring'''



             lowerCamelCase__		:				Optional[int]    =  TFTransfoXLLMHeadModel.from_pretrained("transfo-xl-wt103"       )
             # fmt: off
             lowerCamelCase__		:				Optional[int]    =  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
             lowerCamelCase__		:				Union[str, Any]    =  [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>

             lowerCamelCase__		:				Any    =  model.generate(__lowerCamelCase					,      max_length=200					,      do_sample=__lowerCamelCase       )
             self.assertListEqual(output_ids[0].numpy().tolist()					,      __lowerCamelCase       )






from collections import defaultdict

def       lowercase_		(		_A			:    int						):

      """simple docstring"""




      lowerCamelCase__		:				Union[str, Any]    =  1
      lowerCamelCase__		:				Dict    =  True
      for v in tree[start]:
            if v not in visited:
                  ret += dfs(_A						)
      if ret % 2 == 0:
            cuts.append(_A						)
      return ret

def       lowercase_		(		):

      """simple docstring"""




      dfs(1						)


if __name__ == "__main__":
    A,  A      :    Tuple		=					10, 9
    A      :    int		=					defaultdict(list)
    A      :    dict[int, bool]		=					{}
    A      :    list[int]		=					[]
    A      :    List[str]		=					0
    A      :    Tuple		=					[(2, 1), (3, 1), (4, 3), (5, 2), (6, 1), (7, 2), (8, 6), (9, 8), (10, 8)]
    for u, v in edges:
        tree[u].append(v)
        tree[v].append(u)
    even_tree()
    print(len(cuts) - 1)


