






'''simple docstring'''

import unittest

import numpy as np

from transformers import RobertaConfig, 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.roberta.modeling_flax_roberta import (
         FlaxRobertaForCausalLM,
         FlaxRobertaForMaskedLM,
         FlaxRobertaForMultipleChoice,
         FlaxRobertaForQuestionAnswering,
         FlaxRobertaForSequenceClassification,
         FlaxRobertaForTokenClassification,
         FlaxRobertaModel,
     )






class        a_		(    unittest.TestCase       ):

  def __init__(   self    ,	_SCREAMING_SNAKE_CASE    ,	_SCREAMING_SNAKE_CASE=13    ,	_SCREAMING_SNAKE_CASE=7    ,	_SCREAMING_SNAKE_CASE=True    ,	_SCREAMING_SNAKE_CASE=True    ,	_SCREAMING_SNAKE_CASE=True    ,	_SCREAMING_SNAKE_CASE=True    ,	_SCREAMING_SNAKE_CASE=99    ,	_SCREAMING_SNAKE_CASE=32    ,	_SCREAMING_SNAKE_CASE=5    ,	_SCREAMING_SNAKE_CASE=4    ,	_SCREAMING_SNAKE_CASE=37    ,	_SCREAMING_SNAKE_CASE="gelu"    ,	_SCREAMING_SNAKE_CASE=0.1    ,	_SCREAMING_SNAKE_CASE=0.1    ,	_SCREAMING_SNAKE_CASE=512    ,	_SCREAMING_SNAKE_CASE=16    ,	_SCREAMING_SNAKE_CASE=2    ,	_SCREAMING_SNAKE_CASE=0.0_2    ,	_SCREAMING_SNAKE_CASE=4    ,	)						->   Union[str, Any]:



        """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 						A__		(   self   )						->   Union[str, Any]:



        """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       						=      RobertaConfig(
            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=_lowercase    ,	initializer_range=self.initializer_range    ,	)

        return config, input_ids, token_type_ids, attention_mask

  def 						A__		(   self   )						->   str:



        """simple docstring"""






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


  def 						A__		(   self   )						->   List[str]:



        """simple docstring"""






        UpperCamelCase       						=      self.prepare_config_and_inputs()
        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,
            token_type_ids,
            encoder_hidden_states,
            encoder_attention_mask,
        )






@require_flax
class        a_		(    __snake_case			, unittest.TestCase       ):
  lowercase  	=   True

  lowercase  	=   (
      (
          FlaxRobertaModel,
          FlaxRobertaForCausalLM,
          FlaxRobertaForMaskedLM,
          FlaxRobertaForSequenceClassification,
          FlaxRobertaForTokenClassification,
          FlaxRobertaForMultipleChoice,
          FlaxRobertaForQuestionAnswering,
      )
      if is_flax_available()
      else ()
  )

  def 						A__		(   self   )						->   Dict:



        """simple docstring"""






        UpperCamelCase       						=      FlaxRobertaModelTester(self   )


  @slow
  def 						A__		(   self   )						->   int:



        """simple docstring"""






        for model_class_name in self.all_model_classes:
              UpperCamelCase       						=      model_class_name.from_pretrained("""roberta-base"""    ,	from_pt=_lowercase   )
              UpperCamelCase       						=      model(np.ones((1, 1)   )   )
              self.assertIsNotNone(_lowercase   )








'''simple docstring'''

def 					lowercase__				(   __UpperCamelCase	,		__UpperCamelCase					)->				str:
      if not isinstance(__UpperCamelCase	,		__UpperCamelCase					):
            raise ValueError("""iterations must be defined as integers"""					)
      if not isinstance(__UpperCamelCase	,		__UpperCamelCase					) or not number >= 1:
            raise ValueError(
                """starting number must be
                         and integer and be more than 0"""					)
      if not iterations >= 1:
            raise ValueError("""Iterations must be done more than 0 times to play FizzBuzz"""					)

      UpperCamelCase       						=      """"""
      while number <= iterations:
            if number % 3 == 0:
                  out += "Fizz"
            if number % 5 == 0:
                  out += "Buzz"
            if 0 not in (number % 3, number % 5):
                  out += str(__UpperCamelCase					)

            # print(out)
            number += 1
            out += " "
      return out


if __name__ == "__main__":
     import doctest

     doctest.testmod()
