




"""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			):







   """simple docstring"""




   def __init__(		self       ,					lowerCamelCase_       ,					lowerCamelCase_=1_3       ,					lowerCamelCase_=7       ,					lowerCamelCase_=True       ,					lowerCamelCase_=True       ,					lowerCamelCase_=True       ,					lowerCamelCase_=True       ,					lowerCamelCase_=9_9       ,					lowerCamelCase_=3_2       ,					lowerCamelCase_=5       ,					lowerCamelCase_=4       ,					lowerCamelCase_=3_7       ,					lowerCamelCase_="gelu"       ,					lowerCamelCase_=0.1       ,					lowerCamelCase_=0.1       ,					lowerCamelCase_=5_1_2       ,					lowerCamelCase_=1_6       ,					lowerCamelCase_=2       ,					lowerCamelCase_=0.02       ,					lowerCamelCase_=4       ,					)				->   Any:
       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   UpperCAmelCase__			(		self)				->   Optional[Any]:
       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              =	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_=lowerCamelCase_       ,					)

       return config, input_ids, attention_mask







   def   UpperCAmelCase__			(		self)				->   str:
       UpperCamelCase              =	self.prepare_config_and_inputs()
       UpperCamelCase       ,	UpperCamelCase       ,	UpperCamelCase              =	config_and_inputs
       UpperCamelCase              =	{'''input_ids''': input_ids, '''attention_mask''': attention_mask}
       return config, inputs_dict

@require_flax
class 				snake_case_			(					lowerCamelCase_	, unittest.TestCase			):







   """simple docstring"""




   A_				      =       (
       (
           FlaxDistilBertModel,
           FlaxDistilBertForMaskedLM,
           FlaxDistilBertForMultipleChoice,
           FlaxDistilBertForQuestionAnswering,
           FlaxDistilBertForSequenceClassification,
           FlaxDistilBertForTokenClassification,
           FlaxDistilBertForQuestionAnswering,
       )
       if is_flax_available()
       else ()
   )







   def   UpperCAmelCase__			(		self)				->   List[str]:
       UpperCamelCase              =	FlaxDistilBertModelTester(self)







   @slow
   def   UpperCAmelCase__			(		self)				->   Dict:
       for model_class_name in self.all_model_classes:
           UpperCamelCase              =	model_class_name.from_pretrained('''distilbert-base-uncased''')
           UpperCamelCase              =	model(np.ones((1, 1)))
           self.assertIsNotNone(lowerCamelCase_)

@require_flax
class 				snake_case_			(					unittest.TestCase			):







   """simple docstring"""




   @slow
   def   UpperCAmelCase__			(		self)				->   Optional[int]:
       UpperCamelCase              =	FlaxDistilBertModel.from_pretrained('''distilbert-base-uncased''')
       UpperCamelCase              =	np.array([[0, 3_4_5, 2_3_2, 3_2_8, 7_4_0, 1_4_0, 1_6_9_5, 6_9, 6_0_7_8, 1_5_8_8, 2]])
       UpperCamelCase              =	np.array([[0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]])
       UpperCamelCase              =	model(lowerCamelCase_       ,					attention_mask=lowerCamelCase_)[0]
       UpperCamelCase              =	(1, 1_1, 7_6_8)
       self.assertEqual(output.shape       ,					lowerCamelCase_)
       UpperCamelCase              =	np.array([[[-0.1639, 0.3299, 0.1648], [-0.1746, 0.3289, 0.1710], [-0.1884, 0.3357, 0.1810]]])

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





import functools


def 					_a							(					lowerCAmelCase    ,						lowerCAmelCase )->	int:

		# Validation
		if not isinstance(lowerCAmelCase    ,						lowerCAmelCase ) or not all(isinstance(lowerCAmelCase    ,						lowerCAmelCase ) for day in days ):
				raise ValueError('The parameter days should be a list of integers' )

		if len(lowerCAmelCase ) != 3 or not all(isinstance(lowerCAmelCase    ,						lowerCAmelCase ) for cost in costs ):
				raise ValueError('The parameter costs should be a list of three integers' )

		if len(lowerCAmelCase ) == 0:
				return 0

		if min(lowerCAmelCase ) <= 0:
				raise ValueError('All days elements should be greater than 0' )

		if max(lowerCAmelCase ) >= 366:
				raise ValueError('All days elements should be less than 366' )

		SCREAMING_SNAKE_CASE_					      =							set(lowerCAmelCase )

		@functools.cache
		def dynamic_programming(lowerCAmelCase ) -> int:
				if index > 365:
						return 0

				if index not in days_set:
						return dynamic_programming(index + 1 )

				return min(
				    costs[0] + dynamic_programming(index + 1 )    ,						costs[1] + dynamic_programming(index + 7 )    ,						costs[2] + dynamic_programming(index + 30 )    ,						)

		return dynamic_programming(1 )


if __name__ == "__main__":
						import doctest

						doctest.testmod()