



"""simple docstring"""





import unittest

import numpy as np

from transformers import BertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow

from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask


if is_flax_available():
  from transformers.models.bert.modeling_flax_bert import (
      FlaxBertForMaskedLM,
      FlaxBertForMultipleChoice,
      FlaxBertForNextSentencePrediction,
      FlaxBertForPreTraining,
      FlaxBertForQuestionAnswering,
      FlaxBertForSequenceClassification,
      FlaxBertForTokenClassification,
      FlaxBertModel,
  )
class 				lowercase__       (   unittest.TestCase				):







       '''simple docstring'''


       def __init__(							self      :  Optional[Any]		,    _UpperCAmelCase      :  List[Any]		,    _UpperCAmelCase      :  Optional[Any]=13		,    _UpperCAmelCase      :  Optional[int]=7		,    _UpperCAmelCase      :  int=True		,    _UpperCAmelCase      :  List[Any]=True		,    _UpperCAmelCase      :  Optional[int]=True		,    _UpperCAmelCase      :  Tuple=True		,    _UpperCAmelCase      :  Dict=99		,    _UpperCAmelCase      :  Optional[Any]=32		,    _UpperCAmelCase      :  Optional[Any]=5		,    _UpperCAmelCase      :  Dict=4		,    _UpperCAmelCase      :  Tuple=37		,    _UpperCAmelCase      :  Optional[int]="gelu"		,    _UpperCAmelCase      :  Tuple=0.1		,    _UpperCAmelCase      :  str=0.1		,    _UpperCAmelCase      :  int=512		,    _UpperCAmelCase      :  Union[str, Any]=16		,    _UpperCAmelCase      :  str=2		,    _UpperCAmelCase      :  List[Any]=0.02		,    _UpperCAmelCase      :  List[Any]=4		,    )			->						str:


             '''simple docstring'''




             UpperCAmelCase_      			=							parent
             UpperCAmelCase_      			=							batch_size
             UpperCAmelCase_      			=							seq_length
             UpperCAmelCase_      			=							is_training
             UpperCAmelCase_      			=							use_attention_mask
             UpperCAmelCase_      			=							use_token_type_ids
             UpperCAmelCase_      			=							use_labels
             UpperCAmelCase_      			=							vocab_size
             UpperCAmelCase_      			=							hidden_size
             UpperCAmelCase_      			=							num_hidden_layers
             UpperCAmelCase_      			=							num_attention_heads
             UpperCAmelCase_      			=							intermediate_size
             UpperCAmelCase_      			=							hidden_act
             UpperCAmelCase_      			=							hidden_dropout_prob
             UpperCAmelCase_      			=							attention_probs_dropout_prob
             UpperCAmelCase_      			=							max_position_embeddings
             UpperCAmelCase_      			=							type_vocab_size
             UpperCAmelCase_      			=							type_sequence_label_size
             UpperCAmelCase_      			=							initializer_range
             UpperCAmelCase_      			=							num_choices



       def 					lowercase__    (							self      :  List[Any]   )			->						List[str]:


             '''simple docstring'''




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

             UpperCAmelCase_      			=							None
             if self.use_attention_mask:
                   UpperCAmelCase_      			=							random_attention_mask([self.batch_size, self.seq_length]   )

             UpperCAmelCase_      			=							None
             if self.use_token_type_ids:
                   UpperCAmelCase_      			=							ids_tensor([self.batch_size, self.seq_length]		,    self.type_vocab_size   )

             UpperCAmelCase_      			=							BertConfig(
                 vocab_size=self.vocab_size		,    hidden_size=self.hidden_size		,    num_hidden_layers=self.num_hidden_layers		,    num_attention_heads=self.num_attention_heads		,    intermediate_size=self.intermediate_size		,    hidden_act=self.hidden_act		,    hidden_dropout_prob=self.hidden_dropout_prob		,    attention_probs_dropout_prob=self.attention_probs_dropout_prob		,    max_position_embeddings=self.max_position_embeddings		,    type_vocab_size=self.type_vocab_size		,    is_decoder=_UpperCAmelCase		,    initializer_range=self.initializer_range		,    )

             return config, input_ids, token_type_ids, attention_mask



       def 					lowercase__    (							self      :  Optional[int]   )			->						Dict:


             '''simple docstring'''




             UpperCAmelCase_      			=							self.prepare_config_and_inputs()
             UpperCAmelCase_			,   UpperCAmelCase_			,   UpperCAmelCase_			,   UpperCAmelCase_      			=							config_and_inputs
             UpperCAmelCase_      			=							{"input_ids": input_ids, "token_type_ids": token_type_ids, "attention_mask": attention_mask}
             return config, inputs_dict







       def 					lowercase__    (							self      :  Optional[Any]   )			->						Optional[Any]:


             '''simple docstring'''




             UpperCAmelCase_      			=							self.prepare_config_and_inputs()
             UpperCAmelCase_			,   UpperCAmelCase_			,   UpperCAmelCase_			,   UpperCAmelCase_      			=							config_and_inputs

             UpperCAmelCase_      			=							True
             UpperCAmelCase_      			=							floats_tensor([self.batch_size, self.seq_length, self.hidden_size]   )
             UpperCAmelCase_      			=							ids_tensor([self.batch_size, self.seq_length]		,    vocab_size=2   )

             return (
                 config,
                 input_ids,
                 attention_mask,
                 encoder_hidden_states,
                 encoder_attention_mask,
             )



@require_flax
class 				lowercase__       (   SCREAMING_SNAKE_CASE    , unittest.TestCase				):







       '''simple docstring'''


       UpperCamelCase						=					True

       UpperCamelCase						=					(
           (
               FlaxBertModel,
               FlaxBertForPreTraining,
               FlaxBertForMaskedLM,
               FlaxBertForMultipleChoice,
               FlaxBertForQuestionAnswering,
               FlaxBertForNextSentencePrediction,
               FlaxBertForSequenceClassification,
               FlaxBertForTokenClassification,
               FlaxBertForQuestionAnswering,
           )
           if is_flax_available()
           else ()
       )



       def 					lowercase__    (							self      :  Tuple   )			->						Optional[int]:


             '''simple docstring'''




             UpperCAmelCase_      			=							FlaxBertModelTester(self   )







       @slow
       def 					lowercase__    (							self      :  Optional[int]   )			->						str:


             '''simple docstring'''




             UpperCAmelCase_      			=							FlaxBertModel.from_pretrained("bert-base-cased"   )
             UpperCAmelCase_      			=							model(np.ones((1, 1)   )   )
             self.assertIsNotNone(_UpperCAmelCase   )









"""simple docstring"""





from __future__ import annotations

from collections import namedtuple
from dataclasses import dataclass
@dataclass
class 				lowercase__       :







       '''simple docstring'''


       UpperCamelCase						=					42
       UpperCamelCase						=					None
       UpperCamelCase						=					None



lowerCamelCase       	=						namedtuple("""CoinsDistribResult""", """moves excess""")
def        a__     (				lowerCAmelCase__				):

      if root is None:
            return 0

      # Validation
      def count_nodes(lowerCAmelCase__				) -> int:
            if node is None:
                  return 0

            return count_nodes(node.left				) + count_nodes(node.right				) + 1

      def count_coins(lowerCAmelCase__				) -> int:
            if node is None:
                  return 0

            return count_coins(node.left				) + count_coins(node.right				) + node.data

      if count_nodes(lowerCAmelCase__				) != count_coins(lowerCAmelCase__				):
            raise ValueError("The nodes number should be same as the number of coins"				)

      # Main calculation
      def get_distrib(lowerCAmelCase__				) -> CoinsDistribResult:

            if node is None:
                  return CoinsDistribResult(0     ,      1				)

            UpperCAmelCase_			,   UpperCAmelCase_      			=							get_distrib(node.left				)
            UpperCAmelCase_			,   UpperCAmelCase_      			=							get_distrib(node.right				)

            UpperCAmelCase_      			=							1 - left_distrib_excess
            UpperCAmelCase_      			=							1 - right_distrib_excess

            UpperCAmelCase_      			=							(
                left_distrib_moves
                + right_distrib_moves
                + abs(lowerCAmelCase__				)
                + abs(lowerCAmelCase__				)
            )
            UpperCAmelCase_      			=							node.data - coins_to_left - coins_to_right

            return CoinsDistribResult(lowerCAmelCase__     ,      lowerCAmelCase__				)

      return get_distrib(lowerCAmelCase__				)[0]


if __name__ == "__main__":
  import doctest

  doctest.testmod()




