


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 				A       (			unittest.TestCase				):
					'''simple docstring'''






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




							"""simple docstring"""


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

					def     lowerCamelCase__	(self       :		Dict						)		->  List[str]:




							"""simple docstring"""


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

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

							lowercase__	     =						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_=_UpperCAmelCase ,   )

							return config, input_ids, attention_mask


					def     lowerCamelCase__	(self       :		Any						)		->  List[Any]:




							"""simple docstring"""


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






@require_flax
class 				A       (			UpperCAmelCase__					,    unittest.TestCase				):
					'''simple docstring'''






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

					def     lowerCamelCase__	(self       :		List[Any]						)		->  Tuple:




							"""simple docstring"""


							lowercase__	     =						FlaxDistilBertModelTester(self						)


					@slow
					def     lowerCamelCase__	(self       :		List[str]						)		->  List[Any]:




							"""simple docstring"""


							for model_class_name in self.all_model_classes:
									lowercase__	     =						model_class_name.from_pretrained("""distilbert-base-uncased"""						)
									lowercase__	     =						model(np.ones((1, 1)						)						)
									self.assertIsNotNone(_UpperCAmelCase						)






@require_flax
class 				A       (			unittest.TestCase				):
					'''simple docstring'''






					@slow
					def     lowerCamelCase__	(self       :		Optional[int]						)		->  Optional[Any]:




							"""simple docstring"""


							lowercase__	     =						FlaxDistilBertModel.from_pretrained("""distilbert-base-uncased"""						)
							lowercase__	     =						np.array([[0, 345, 232, 328, 740, 140, 1695, 69, 6078, 1588, 2]]						)
							lowercase__	     =						np.array([[0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]						)
							lowercase__	     =						model(_UpperCAmelCase ,   attention_mask=_UpperCAmelCase						)[0]
							lowercase__	     =						(1, 11, 768)
							self.assertEqual(output.shape ,   _UpperCAmelCase						)
							lowercase__	     =						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] ,   _UpperCAmelCase ,   atol=1E-4						)						)








"""simple docstring"""



def 						__lowercase	(  snake_case_    :    list		)  ->float:



    '''simple docstring'''







    __A       :		Tuple							=	0
    while len(snake_case_		) > 1:
        __A       :		List[Any]							=	0
        # Consider two files with minimum cost to be merged
        for _ in range(2		):
            __A       :		Dict							=	files.index(min(snake_case_		)		)
            temp += files[min_index]
            files.pop(snake_case_		)
        files.append(snake_case_		)
        optimal_merge_cost += temp
    return optimal_merge_cost


if __name__ == "__main__":
       import doctest

       doctest.testmod()




