

'''simple docstring'''



import unittest

import numpy as np

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

from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask


if is_flax_available():
     import jax.numpy as jnp

     from transformers.models.distilbert.modeling_flax_distilbert import (
         FlaxDistilBertForMaskedLM,
         FlaxDistilBertForMultipleChoice,
         FlaxDistilBertForQuestionAnswering,
         FlaxDistilBertForSequenceClassification,
         FlaxDistilBertForTokenClassification,
         FlaxDistilBertModel,
     )



class 				_snake_case					(   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=5_12      , _SCREAMING_SNAKE_CASE=16      , _SCREAMING_SNAKE_CASE=2      , _SCREAMING_SNAKE_CASE=0.02      , _SCREAMING_SNAKE_CASE=4      , ):





      '''simple docstring'''

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

  def   _SCREAMING_SNAKE_CASE				(				self	):





      '''simple docstring'''

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

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

      lowerCAmelCase 						=							DistilBertConfig(
          vocab_size=self.vocab_size      , dim=self.hidden_size      , n_layers=self.num_hidden_layers      , n_heads=self.num_attention_heads      , hidden_dim=self.intermediate_size      , hidden_act=self.hidden_act      , dropout=self.hidden_dropout_prob      , attention_dropout=self.attention_probs_dropout_prob      , max_position_embeddings=self.max_position_embeddings      , initializer_range=self.initializer_range      , tie_weights_=_SCREAMING_SNAKE_CASE      , )

      return config, input_ids, attention_mask


  def   _SCREAMING_SNAKE_CASE				(				self	):





      '''simple docstring'''

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



@require_flax
class 				_snake_case					(   a_     , unittest.TestCase			):
  SCREAMING_SNAKE_CASE			:       Tuple				=     (
      (
          FlaxDistilBertModel,
          FlaxDistilBertForMaskedLM,
          FlaxDistilBertForMultipleChoice,
          FlaxDistilBertForQuestionAnswering,
          FlaxDistilBertForSequenceClassification,
          FlaxDistilBertForTokenClassification,
          FlaxDistilBertForQuestionAnswering,
      )
      if is_flax_available()
      else ()
  )

  def   _SCREAMING_SNAKE_CASE				(				self	):





      '''simple docstring'''

      lowerCAmelCase 						=							FlaxDistilBertModelTester(self	)


  @slow
  def   _SCREAMING_SNAKE_CASE				(				self	):





      '''simple docstring'''

      for model_class_name in self.all_model_classes:
          lowerCAmelCase 						=							model_class_name.from_pretrained('distilbert-base-uncased'	)
          lowerCAmelCase 						=							model(np.ones((1, 1)	)	)
          self.assertIsNotNone(_SCREAMING_SNAKE_CASE	)



@require_flax
class 				_snake_case					(   unittest.TestCase			):

  @slow
  def   _SCREAMING_SNAKE_CASE				(				self	):





      '''simple docstring'''

      lowerCAmelCase 						=							FlaxDistilBertModel.from_pretrained('distilbert-base-uncased'	)
      lowerCAmelCase 						=							np.array([[0, 3_45, 2_32, 3_28, 7_40, 1_40, 16_95, 69, 60_78, 15_88, 2]]	)
      lowerCAmelCase 						=							np.array([[0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]	)
      lowerCAmelCase 						=							model(_SCREAMING_SNAKE_CASE      , attention_mask=_SCREAMING_SNAKE_CASE	)[0]
      lowerCAmelCase 						=							(1, 11, 7_68)
      self.assertEqual(output.shape      , _SCREAMING_SNAKE_CASE	)
      lowerCAmelCase 						=							np.array([[[-0.1_639, 0.3_299, 0.1_648], [-0.1_746, 0.3_289, 0.1_710], [-0.1_884, 0.3_357, 0.1_810]]]	)

      self.assertTrue(jnp.allclose(output[:, 1:4, 1:4]      , _SCREAMING_SNAKE_CASE      , atol=1e-4	)	)








'''simple docstring'''



def       snake_case   (	snake_case      : list			) ->  list:


    """simple docstring"""


    if any(not isinstance(snake_case					,		snake_case			) or x < 0 for x in sequence			):
        raise TypeError('Sequence must be list of non-negative integers'			)
    for _ in range(len(snake_case			)			):
        for i, (rod_upper, rod_lower) in enumerate(zip(snake_case					,		sequence[1:]			)			):
            if rod_upper > rod_lower:
                sequence[i] -= rod_upper - rod_lower
                sequence[i + 1] += rod_upper - rod_lower
    return sequence


if __name__ == "__main__":
     assert bead_sort([5, 4, 3, 2, 1]) == [1, 2, 3, 4, 5]
     assert bead_sort([7, 9, 4, 3, 5]) == [3, 4, 5, 7, 9]





