






import unittest

from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device

from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor
from ...test_pipeline_mixin import PipelineTesterMixin


if is_torch_available():
   import torch

   from transformers import (
       DebertaVaForMaskedLM,
       DebertaVaForMultipleChoice,
       DebertaVaForQuestionAnswering,
       DebertaVaForSequenceClassification,
       DebertaVaForTokenClassification,
       DebertaVaModel,
   )
   from transformers.models.deberta_va.modeling_deberta_va import DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST
class  lowerCAmelCase_       (				snake_case__					):




       def __init__(   self     :   List[str] ,							SCREAMING_SNAKE_CASE_     :   Any ,							SCREAMING_SNAKE_CASE_     :   List[str]=13 ,							SCREAMING_SNAKE_CASE_     :   Tuple=7 ,							SCREAMING_SNAKE_CASE_     :   List[Any]=True ,							SCREAMING_SNAKE_CASE_     :   List[Any]=True ,							SCREAMING_SNAKE_CASE_     :   int=True ,							SCREAMING_SNAKE_CASE_     :   Tuple=True ,							SCREAMING_SNAKE_CASE_     :   List[Any]=99 ,							SCREAMING_SNAKE_CASE_     :   Any=32 ,							SCREAMING_SNAKE_CASE_     :   Dict=5 ,							SCREAMING_SNAKE_CASE_     :   Tuple=4 ,							SCREAMING_SNAKE_CASE_     :   Optional[Any]=37 ,							SCREAMING_SNAKE_CASE_     :   List[Any]="gelu" ,							SCREAMING_SNAKE_CASE_     :   List[str]=0.1 ,							SCREAMING_SNAKE_CASE_     :   Dict=0.1 ,							SCREAMING_SNAKE_CASE_     :   str=512 ,							SCREAMING_SNAKE_CASE_     :   Tuple=16 ,							SCREAMING_SNAKE_CASE_     :   int=2 ,							SCREAMING_SNAKE_CASE_     :   List[str]=0.02 ,							SCREAMING_SNAKE_CASE_     :   str=False ,							SCREAMING_SNAKE_CASE_     :   List[Any]=True ,							SCREAMING_SNAKE_CASE_     :   Union[str, Any]="None" ,							SCREAMING_SNAKE_CASE_     :   Optional[int]=3 ,							SCREAMING_SNAKE_CASE_     :   Union[str, Any]=4 ,							SCREAMING_SNAKE_CASE_     :   int=None ,							):
           lowerCAmelCase__      			=						parent
           lowerCAmelCase__      			=						batch_size
           lowerCAmelCase__      			=						seq_length
           lowerCAmelCase__      			=						is_training
           lowerCAmelCase__      			=						use_input_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_labels
           lowerCAmelCase__      			=						num_choices
           lowerCAmelCase__      			=						relative_attention
           lowerCAmelCase__      			=						position_biased_input
           lowerCAmelCase__      			=						pos_att_type
           lowerCAmelCase__      			=						scope




       def 						__snake_case					(   self     :   Optional[Any]	):
           lowerCAmelCase__      			=						ids_tensor([self.batch_size, self.seq_length] ,							self.vocab_size	)

           lowerCAmelCase__      			=						None
           if self.use_input_mask:
               lowerCAmelCase__      			=						ids_tensor([self.batch_size, self.seq_length] ,							vocab_size=2	)

           lowerCAmelCase__      			=						None
           if self.use_token_type_ids:
               lowerCAmelCase__      			=						ids_tensor([self.batch_size, self.seq_length] ,							self.type_vocab_size	)

           lowerCAmelCase__      			=						None
           lowerCAmelCase__      			=						None
           lowerCAmelCase__      			=						None
           if self.use_labels:
               lowerCAmelCase__      			=						ids_tensor([self.batch_size] ,							self.type_sequence_label_size	)
               lowerCAmelCase__      			=						ids_tensor([self.batch_size, self.seq_length] ,							self.num_labels	)
               lowerCAmelCase__      			=						ids_tensor([self.batch_size] ,							self.num_choices	)

           lowerCAmelCase__      			=						self.get_config()

           return config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels




       def 						__snake_case					(   self     :   Tuple	):
           return DebertaVaConfig(
               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 ,							initializer_range=self.initializer_range ,							relative_attention=self.relative_attention ,							position_biased_input=self.position_biased_input ,							pos_att_type=self.pos_att_type ,							)




       def 						__snake_case					(   self     :   Any ,							SCREAMING_SNAKE_CASE_     :   str	):
           self.parent.assertListEqual(list(result.loss.size()	) ,							[]	)




       def 						__snake_case					(   self     :   str ,							SCREAMING_SNAKE_CASE_     :   Dict ,							SCREAMING_SNAKE_CASE_     :   List[str] ,							SCREAMING_SNAKE_CASE_     :   Optional[int] ,							SCREAMING_SNAKE_CASE_     :   int ,							SCREAMING_SNAKE_CASE_     :   Any ,							SCREAMING_SNAKE_CASE_     :   List[str] ,							SCREAMING_SNAKE_CASE_     :   str	):
           lowerCAmelCase__      			=						DebertaVaModel(config=SCREAMING_SNAKE_CASE_	)
           model.to(SCREAMING_SNAKE_CASE_	)
           model.eval()
           lowerCAmelCase__      			=						model(SCREAMING_SNAKE_CASE_ ,							attention_mask=SCREAMING_SNAKE_CASE_ ,							token_type_ids=SCREAMING_SNAKE_CASE_	)[0]
           lowerCAmelCase__      			=						model(SCREAMING_SNAKE_CASE_ ,							token_type_ids=SCREAMING_SNAKE_CASE_	)[0]
           lowerCAmelCase__      			=						model(SCREAMING_SNAKE_CASE_	)[0]

           self.parent.assertListEqual(list(sequence_output.size()	) ,							[self.batch_size, self.seq_length, self.hidden_size]	)




       def 						__snake_case					(   self     :   int ,							SCREAMING_SNAKE_CASE_     :   int ,							SCREAMING_SNAKE_CASE_     :   Union[str, Any] ,							SCREAMING_SNAKE_CASE_     :   List[Any] ,							SCREAMING_SNAKE_CASE_     :   Dict ,							SCREAMING_SNAKE_CASE_     :   str ,							SCREAMING_SNAKE_CASE_     :   Tuple ,							SCREAMING_SNAKE_CASE_     :   Any	):
           lowerCAmelCase__      			=						DebertaVaForMaskedLM(config=SCREAMING_SNAKE_CASE_	)
           model.to(SCREAMING_SNAKE_CASE_	)
           model.eval()
           lowerCAmelCase__      			=						model(SCREAMING_SNAKE_CASE_ ,							attention_mask=SCREAMING_SNAKE_CASE_ ,							token_type_ids=SCREAMING_SNAKE_CASE_ ,							labels=SCREAMING_SNAKE_CASE_	)

           self.parent.assertEqual(result.logits.shape ,							(self.batch_size, self.seq_length, self.vocab_size)	)




       def 						__snake_case					(   self     :   int ,							SCREAMING_SNAKE_CASE_     :   List[Any] ,							SCREAMING_SNAKE_CASE_     :   Tuple ,							SCREAMING_SNAKE_CASE_     :   Optional[int] ,							SCREAMING_SNAKE_CASE_     :   Optional[int] ,							SCREAMING_SNAKE_CASE_     :   int ,							SCREAMING_SNAKE_CASE_     :   Union[str, Any] ,							SCREAMING_SNAKE_CASE_     :   Any	):
           lowerCAmelCase__      			=						self.num_labels
           lowerCAmelCase__      			=						DebertaVaForSequenceClassification(SCREAMING_SNAKE_CASE_	)
           model.to(SCREAMING_SNAKE_CASE_	)
           model.eval()
           lowerCAmelCase__      			=						model(SCREAMING_SNAKE_CASE_ ,							attention_mask=SCREAMING_SNAKE_CASE_ ,							token_type_ids=SCREAMING_SNAKE_CASE_ ,							labels=SCREAMING_SNAKE_CASE_	)
           self.parent.assertListEqual(list(result.logits.size()	) ,							[self.batch_size, self.num_labels]	)
           self.check_loss_output(SCREAMING_SNAKE_CASE_	)




       def 						__snake_case					(   self     :   Optional[int] ,							SCREAMING_SNAKE_CASE_     :   Optional[int] ,							SCREAMING_SNAKE_CASE_     :   Optional[int] ,							SCREAMING_SNAKE_CASE_     :   Tuple ,							SCREAMING_SNAKE_CASE_     :   Optional[int] ,							SCREAMING_SNAKE_CASE_     :   Any ,							SCREAMING_SNAKE_CASE_     :   Tuple ,							SCREAMING_SNAKE_CASE_     :   List[str]	):
           lowerCAmelCase__      			=						self.num_labels
           lowerCAmelCase__      			=						DebertaVaForTokenClassification(config=SCREAMING_SNAKE_CASE_	)
           model.to(SCREAMING_SNAKE_CASE_	)
           model.eval()
           lowerCAmelCase__      			=						model(SCREAMING_SNAKE_CASE_ ,							attention_mask=SCREAMING_SNAKE_CASE_ ,							token_type_ids=SCREAMING_SNAKE_CASE_ ,							labels=SCREAMING_SNAKE_CASE_	)
           self.parent.assertEqual(result.logits.shape ,							(self.batch_size, self.seq_length, self.num_labels)	)




       def 						__snake_case					(   self     :   Tuple ,							SCREAMING_SNAKE_CASE_     :   Tuple ,							SCREAMING_SNAKE_CASE_     :   str ,							SCREAMING_SNAKE_CASE_     :   List[str] ,							SCREAMING_SNAKE_CASE_     :   Dict ,							SCREAMING_SNAKE_CASE_     :   List[Any] ,							SCREAMING_SNAKE_CASE_     :   List[str] ,							SCREAMING_SNAKE_CASE_     :   List[Any]	):
           lowerCAmelCase__      			=						DebertaVaForQuestionAnswering(config=SCREAMING_SNAKE_CASE_	)
           model.to(SCREAMING_SNAKE_CASE_	)
           model.eval()
           lowerCAmelCase__      			=						model(
               SCREAMING_SNAKE_CASE_ ,							attention_mask=SCREAMING_SNAKE_CASE_ ,							token_type_ids=SCREAMING_SNAKE_CASE_ ,							start_positions=SCREAMING_SNAKE_CASE_ ,							end_positions=SCREAMING_SNAKE_CASE_ ,							)
           self.parent.assertEqual(result.start_logits.shape ,							(self.batch_size, self.seq_length)	)
           self.parent.assertEqual(result.end_logits.shape ,							(self.batch_size, self.seq_length)	)




       def 						__snake_case					(   self     :   str ,							SCREAMING_SNAKE_CASE_     :   Optional[Any] ,							SCREAMING_SNAKE_CASE_     :   List[str] ,							SCREAMING_SNAKE_CASE_     :   Dict ,							SCREAMING_SNAKE_CASE_     :   List[Any] ,							SCREAMING_SNAKE_CASE_     :   List[Any] ,							SCREAMING_SNAKE_CASE_     :   Dict ,							SCREAMING_SNAKE_CASE_     :   List[Any]	):
           lowerCAmelCase__      			=						DebertaVaForMultipleChoice(config=SCREAMING_SNAKE_CASE_	)
           model.to(SCREAMING_SNAKE_CASE_	)
           model.eval()
           lowerCAmelCase__      			=						input_ids.unsqueeze(1	).expand(-1 ,							self.num_choices ,							-1	).contiguous()
           lowerCAmelCase__      			=						token_type_ids.unsqueeze(1	).expand(-1 ,							self.num_choices ,							-1	).contiguous()
           lowerCAmelCase__      			=						input_mask.unsqueeze(1	).expand(-1 ,							self.num_choices ,							-1	).contiguous()
           lowerCAmelCase__      			=						model(
               SCREAMING_SNAKE_CASE_ ,							attention_mask=SCREAMING_SNAKE_CASE_ ,							token_type_ids=SCREAMING_SNAKE_CASE_ ,							labels=SCREAMING_SNAKE_CASE_ ,							)
           self.parent.assertEqual(result.logits.shape ,							(self.batch_size, self.num_choices)	)




       def 						__snake_case					(   self     :   Dict	):
           lowerCAmelCase__      			=						self.prepare_config_and_inputs()
           (
               (
               lowerCAmelCase__		
           )			,		(
               lowerCAmelCase__		
           )			,		(
               lowerCAmelCase__		
           )			,		(
               lowerCAmelCase__		
           )			,		(
               lowerCAmelCase__		
           )			,		(
               lowerCAmelCase__		
           )			,		(
               lowerCAmelCase__		
           )			,				
           )      			=						config_and_inputs
           lowerCAmelCase__      			=						{'''input_ids''': input_ids, '''token_type_ids''': token_type_ids, '''attention_mask''': input_mask}
           return config, inputs_dict



@require_torch
class  lowerCAmelCase_       (				snake_case__     ,    snake_case__     ,    unittest.TestCase					):
       UpperCamelCase_		:Dict		      =    (
           (
               DebertaVaModel,
               DebertaVaForMaskedLM,
               DebertaVaForSequenceClassification,
               DebertaVaForTokenClassification,
               DebertaVaForQuestionAnswering,
               DebertaVaForMultipleChoice,
           )
           if is_torch_available()
           else ()
       )
       UpperCamelCase_		:Tuple		      =    (
           {
               'feature-extraction': DebertaVaModel,
               'fill-mask': DebertaVaForMaskedLM,
               'question-answering': DebertaVaForQuestionAnswering,
               'text-classification': DebertaVaForSequenceClassification,
               'token-classification': DebertaVaForTokenClassification,
               'zero-shot': DebertaVaForSequenceClassification,
           }
           if is_torch_available()
           else {}
       )

       UpperCamelCase_		:str		      =    True
       UpperCamelCase_		:List[Any]		      =    False
       UpperCamelCase_		:Tuple		      =    False
       UpperCamelCase_		:Any		      =    False
       UpperCamelCase_		:Optional[Any]		      =    False




       def 						__snake_case					(   self     :   List[Any]	):
           lowerCAmelCase__      			=						DebertaVaModelTester(self	)
           lowerCAmelCase__      			=						ConfigTester(self ,							config_class=SCREAMING_SNAKE_CASE_ ,							hidden_size=37	)




       def 						__snake_case					(   self     :   List[str]	):
           self.config_tester.run_common_tests()




       def 						__snake_case					(   self     :   int	):
           lowerCAmelCase__      			=						self.model_tester.prepare_config_and_inputs()
           self.model_tester.create_and_check_deberta_model(*SCREAMING_SNAKE_CASE_	)




       def 						__snake_case					(   self     :   str	):
           lowerCAmelCase__      			=						self.model_tester.prepare_config_and_inputs()
           self.model_tester.create_and_check_deberta_for_sequence_classification(*SCREAMING_SNAKE_CASE_	)




       def 						__snake_case					(   self     :   Optional[int]	):
           lowerCAmelCase__      			=						self.model_tester.prepare_config_and_inputs()
           self.model_tester.create_and_check_deberta_for_masked_lm(*SCREAMING_SNAKE_CASE_	)




       def 						__snake_case					(   self     :   Dict	):
           lowerCAmelCase__      			=						self.model_tester.prepare_config_and_inputs()
           self.model_tester.create_and_check_deberta_for_question_answering(*SCREAMING_SNAKE_CASE_	)




       def 						__snake_case					(   self     :   int	):
           lowerCAmelCase__      			=						self.model_tester.prepare_config_and_inputs()
           self.model_tester.create_and_check_deberta_for_token_classification(*SCREAMING_SNAKE_CASE_	)




       def 						__snake_case					(   self     :   Optional[int]	):
           lowerCAmelCase__      			=						self.model_tester.prepare_config_and_inputs()
           self.model_tester.create_and_check_deberta_for_multiple_choice(*SCREAMING_SNAKE_CASE_	)




       @slow
       def 						__snake_case					(   self     :   Optional[Any]	):
           for model_name in DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
               lowerCAmelCase__      			=						DebertaVaModel.from_pretrained(SCREAMING_SNAKE_CASE_	)
               self.assertIsNotNone(SCREAMING_SNAKE_CASE_	)



@require_torch
@require_sentencepiece
@require_tokenizers
class  lowerCAmelCase_       (				unittest.TestCase					):




       @unittest.skip(reason='''Model not available yet'''	)
       def 						__snake_case					(   self     :   int	):
           pass




       @slow
       def 						__snake_case					(   self     :   List[str]	):
           lowerCAmelCase__      			=						DebertaVaModel.from_pretrained('''microsoft/deberta-v2-xlarge'''	)

           lowerCAmelCase__      			=						torch.tensor([[0, 31_414, 232, 328, 740, 1_140, 12_695, 69, 46_078, 1_588, 2]]	)
           lowerCAmelCase__      			=						torch.tensor([[0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]	)
           with torch.no_grad():
               lowerCAmelCase__      			=						model(SCREAMING_SNAKE_CASE_ ,							attention_mask=SCREAMING_SNAKE_CASE_	)[0]
           # compare the actual values for a slice.
           lowerCAmelCase__      			=						torch.tensor(
               [[[0.2_356, 0.1_948, 0.0_369], [-0.1_063, 0.3_586, -0.5_152], [-0.6_399, -0.0_259, -0.2_525]]]	)
           self.assertTrue(torch.allclose(output[:, 1:4, 1:4] ,							SCREAMING_SNAKE_CASE_ ,							atol=1e-4	) ,							f'{output[:, 1:4, 1:4]}'	)













from pathlib import Path

import fire





def 	lowerCAmelCase_		(lowercase__						:       str     ,					lowercase__						:       str     ,					lowercase__						:       int       )		->    Dict:


				'''simple docstring'''




				lowerCAmelCase__      			=						Path(lowercase__       )
				lowerCAmelCase__      			=						Path(lowercase__       )
				dest_dir.mkdir(exist_ok=lowercase__       )
				for path in src_dir.iterdir():
								lowerCAmelCase__      			=						[x.rstrip() for x in list(path.open().readlines()       )][:n]
								lowerCAmelCase__      			=						dest_dir.joinpath(path.name       )
								print(lowercase__       )
								dest_path.open('''w'''       ).write('''\n'''.join(lowercase__       )       )


if __name__ == "__main__":
			fire.Fire(minify)





