





"""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=13   ,		__lowerCamelCase=7   ,		__lowerCamelCase=True   ,		__lowerCamelCase=True   ,		__lowerCamelCase=True   ,		__lowerCamelCase=True   ,		__lowerCamelCase=99   ,		__lowerCamelCase=32   ,		__lowerCamelCase=5   ,		__lowerCamelCase=4   ,		__lowerCamelCase=37   ,		__lowerCamelCase="gelu"   ,		__lowerCamelCase=0.1   ,		__lowerCamelCase=0.1   ,		__lowerCamelCase=512   ,		__lowerCamelCase=16   ,		__lowerCamelCase=2   ,		__lowerCamelCase=0.0_2   ,		__lowerCamelCase=4   ,		):



     '''simple docstring'''




     __A       :		Union[str, Any]							=	parent
     __A       :		Tuple							=	batch_size
     __A       :		Any							=	seq_length
     __A       :		Optional[int]							=	is_training
     __A       :		Any							=	use_attention_mask
     __A       :		Union[str, Any]							=	use_token_type_ids
     __A       :		Optional[Any]							=	use_labels
     __A       :		Union[str, Any]							=	vocab_size
     __A       :		int							=	hidden_size
     __A       :		Dict							=	num_hidden_layers
     __A       :		Dict							=	num_attention_heads
     __A       :		Optional[int]							=	intermediate_size
     __A       :		Tuple							=	hidden_act
     __A       :		Tuple							=	hidden_dropout_prob
     __A       :		Any							=	attention_probs_dropout_prob
     __A       :		int							=	max_position_embeddings
     __A       :		Dict							=	type_vocab_size
     __A       :		Union[str, Any]							=	type_sequence_label_size
     __A       :		Any							=	initializer_range
     __A       :		Optional[Any]							=	num_choices

 def    UpperCamelCase__(       self    ):



     '''simple docstring'''




     __A       :		int							=	ids_tensor([self.batch_size, self.seq_length]   ,		self.vocab_size    )

     __A       :		Union[str, Any]							=	None
     if self.use_attention_mask:
         __A       :		Optional[int]							=	random_attention_mask([self.batch_size, self.seq_length]    )

     __A       :		str							=	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    ):



     '''simple docstring'''




     __A       :		Dict							=	self.prepare_config_and_inputs()
     __A					,			__A					,			__A       :		Optional[Any]							=	config_and_inputs
     __A       :		List[Any]							=	{'''input_ids''': input_ids, '''attention_mask''': attention_mask}
     return config, inputs_dict






@require_flax
class 						__snake_case   (						SCREAMING_SNAKE_CASE__				,				unittest.TestCase	):





 """simple docstring"""


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

 def    UpperCamelCase__(       self    ):



     '''simple docstring'''




     __A       :		List[str]							=	FlaxDistilBertModelTester(self    )







 @slow
 def    UpperCamelCase__(       self    ):



     '''simple docstring'''




     for model_class_name in self.all_model_classes:
         __A       :		List[Any]							=	model_class_name.from_pretrained('''distilbert-base-uncased'''    )
         __A       :		Optional[int]							=	model(np.ones((1, 1)    )    )
         self.assertIsNotNone(__lowerCamelCase    )






@require_flax
class 						__snake_case   (						unittest.TestCase	):





 """simple docstring"""


 @slow
 def    UpperCamelCase__(       self    ):



     '''simple docstring'''




     __A       :		str							=	FlaxDistilBertModel.from_pretrained('''distilbert-base-uncased'''    )
     __A       :		Optional[Any]							=	np.array([[0, 345, 232, 328, 740, 140, 1695, 69, 6078, 1588, 2]]    )
     __A       :		str							=	np.array([[0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]    )
     __A       :		int							=	model(__lowerCamelCase   ,		attention_mask=__lowerCamelCase    )[0]
     __A       :		Union[str, Any]							=	(1, 11, 768)
     self.assertEqual(output.shape   ,		__lowerCamelCase    )
     __A       :		Optional[int]							=	np.array([[[-0.1_6_3_9, 0.3_2_9_9, 0.1_6_4_8], [-0.1_7_4_6, 0.3_2_8_9, 0.1_7_1_0], [-0.1_8_8_4, 0.3_3_5_7, 0.1_8_1_0]]]    )

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











"""simple docstring"""



def 						__lowercase	(  snake_case_    :    int = 2000000		)  ->int:



    '''simple docstring'''







    __A       :		List[Any]							=	[0 for i in range(n + 1		)]
    __A       :		str							=	1
    __A       :		Dict							=	1

    for i in range(2							,int(n**0.5		) + 1		):
        if primality_list[i] == 0:
            for j in range(i * i							,n + 1							,snake_case_		):
                __A       :		List[Any]							=	1
    __A       :		Union[str, Any]							=	0
    for i in range(snake_case_		):
        if primality_list[i] == 0:
            sum_of_primes += i
    return sum_of_primes


if __name__ == "__main__":
       print(f'''{solution() = }''')




