





'''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 __a			( unittest.TestCase      ):





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

      '''simple docstring'''

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





   def   UpperCAmelCase__  (       self					:      Optional[Any]     ):

      '''simple docstring'''

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

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

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

      __SCREAMING_SNAKE_CASE   				=							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=lowerCamelCase					,initializer_range=self.initializer_range					,)

      return config, input_ids, token_type_ids, attention_mask





   def   UpperCAmelCase__  (       self					:      int     ):

      '''simple docstring'''

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





   def   UpperCAmelCase__  (       self					:      Tuple     ):

      '''simple docstring'''

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

      __SCREAMING_SNAKE_CASE   				=							True
      __SCREAMING_SNAKE_CASE   				=							floats_tensor([self.batch_size, self.seq_length, self.hidden_size]     )
      __SCREAMING_SNAKE_CASE   				=							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 __a			( _snake_case, unittest.TestCase      ):
   __UpperCamelCase :			Dict						   =						True

   __UpperCamelCase :			List[Any]						   =						(
       (
           FlaxBertModel,
           FlaxBertForPreTraining,
           FlaxBertForMaskedLM,
           FlaxBertForMultipleChoice,
           FlaxBertForQuestionAnswering,
           FlaxBertForNextSentencePrediction,
           FlaxBertForSequenceClassification,
           FlaxBertForTokenClassification,
           FlaxBertForQuestionAnswering,
       )
       if is_flax_available()
       else ()
   )





   def   UpperCAmelCase__  (       self					:      int     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							FlaxBertModelTester(self     )





   @slow
   def   UpperCAmelCase__  (       self					:      Dict     ):

      '''simple docstring'''

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












'''simple docstring'''

def     __magic_name__							(				__UpperCAmelCase				,						__UpperCAmelCase   )    ->       str:

   '''simple docstring'''







   __SCREAMING_SNAKE_CASE   				=							(boundary[1] - boundary[0]) / steps
   __SCREAMING_SNAKE_CASE   				=							boundary[0]
   __SCREAMING_SNAKE_CASE   				=							boundary[1]
   __SCREAMING_SNAKE_CASE   				=							make_points(__UpperCAmelCase				,						__UpperCAmelCase				,						__UpperCAmelCase   )
   __SCREAMING_SNAKE_CASE   				=							0.0
   y += (h / 2.0) * f(__UpperCAmelCase   )
   for i in x_i:
      # print(i)
      y += h * f(__UpperCAmelCase   )
   y += (h / 2.0) * f(__UpperCAmelCase   )
   return y

def     __magic_name__							(				__UpperCAmelCase				,						__UpperCAmelCase				,						__UpperCAmelCase   )    ->       Optional[Any]:

   '''simple docstring'''







   __SCREAMING_SNAKE_CASE   				=							a + h
   while x < (b - h):
      yield x
      __SCREAMING_SNAKE_CASE   				=							x + h

def     __magic_name__							(				__UpperCAmelCase   )    ->       int:  # enter your function here

   '''simple docstring'''







   __SCREAMING_SNAKE_CASE   				=							(x - 0) * (x - 0)
   return y

def     __magic_name__							(				)    ->       Tuple:

   '''simple docstring'''







   __SCREAMING_SNAKE_CASE   				=							0.0  # Lower bound of integration
   __SCREAMING_SNAKE_CASE   				=							1.0  # Upper bound of integration
   __SCREAMING_SNAKE_CASE   				=							1_0.0  # define number of steps or resolution
   __SCREAMING_SNAKE_CASE   				=							[a, b]  # define boundary of integration
   __SCREAMING_SNAKE_CASE   				=							method_a(__UpperCAmelCase				,						__UpperCAmelCase   )
   print(f"""y = {y}"""   )


if __name__ == "__main__":
    main()





