






'''simple docstring'''
from __future__ import annotations

import unittest

from transformers import DebertaVaConfig, is_tf_available
from transformers.testing_utils import require_tf, slow

from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pipeline_mixin import PipelineTesterMixin


if is_tf_available():
 import tensorflow as tf

 from transformers import (
     TFDebertaVaForMaskedLM,
     TFDebertaVaForQuestionAnswering,
     TFDebertaVaForSequenceClassification,
     TFDebertaVaForTokenClassification,
     TFDebertaVaModel,
 )


class        _UpperCAmelCase						:




    def __init__(			self  :       int  ,     a  :       str  ,     a  :       Tuple=1_3  ,     a  :       List[Any]=7  ,     a  :       List[str]=True  ,     a  :       Any=True  ,     a  :       int=True  ,     a  :       List[Any]=True  ,     a  :       List[Any]=9_9  ,     a  :       List[str]=3_2  ,     a  :       Optional[int]=2  ,     a  :       Tuple=4  ,     a  :       Optional[int]=3_7  ,     a  :       int="gelu"  ,     a  :       int=0.1  ,     a  :       int=0.1  ,     a  :       List[str]=5_1_2  ,     a  :       Dict=1_6  ,     a  :       List[str]=2  ,     a  :       int=0.02  ,     a  :       Dict=False  ,     a  :       List[str]=True  ,     a  :       Union[str, Any]="None"  ,     a  :       str=3  ,     a  :       Optional[int]=4  ,     a  :       Any=None  ,     ):






       '''simple docstring'''






       lowercase_	:    Optional[Any]           =     parent
       lowercase_	:    Tuple           =     batch_size
       lowercase_	:    Optional[int]           =     seq_length
       lowercase_	:    Dict           =     is_training
       lowercase_	:    Tuple           =     use_input_mask
       lowercase_	:    str           =     use_token_type_ids
       lowercase_	:    Tuple           =     use_labels
       lowercase_	:    str           =     vocab_size
       lowercase_	:    List[str]           =     hidden_size
       lowercase_	:    Optional[Any]           =     num_hidden_layers
       lowercase_	:    Optional[Any]           =     num_attention_heads
       lowercase_	:    Any           =     intermediate_size
       lowercase_	:    Any           =     hidden_act
       lowercase_	:    str           =     hidden_dropout_prob
       lowercase_	:    Tuple           =     attention_probs_dropout_prob
       lowercase_	:    Optional[int]           =     max_position_embeddings
       lowercase_	:    Tuple           =     type_vocab_size
       lowercase_	:    List[str]           =     type_sequence_label_size
       lowercase_	:    int           =     initializer_range
       lowercase_	:    Union[str, Any]           =     num_labels
       lowercase_	:    Any           =     num_choices
       lowercase_	:    List[str]           =     relative_attention
       lowercase_	:    str           =     position_biased_input
       lowercase_	:    Optional[int]           =     pos_att_type
       lowercase_	:    List[Any]           =     scope




    def 				lowerCAmelCase__				(			self  :       Optional[Any]			):






       '''simple docstring'''






       lowercase_	:    List[Any]           =     ids_tensor([self.batch_size, self.seq_length]  ,     self.vocab_size			)

       lowercase_	:    Tuple           =     None
       if self.use_input_mask:
          lowercase_	:    int           =     random_attention_mask([self.batch_size, self.seq_length]			)

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

       lowercase_	:    Dict           =     None
       lowercase_	:    Tuple           =     None
       lowercase_	:    Dict           =     None
       if self.use_labels:
          lowercase_	:    str           =     ids_tensor([self.batch_size]  ,     self.type_sequence_label_size			)
          lowercase_	:    Union[str, Any]           =     ids_tensor([self.batch_size, self.seq_length]  ,     self.num_labels			)

       lowercase_	:    str           =     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  ,     relative_attention=self.relative_attention  ,     position_biased_input=self.position_biased_input  ,     initializer_range=self.initializer_range  ,     return_dict=a  ,     )

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




    def 				lowerCAmelCase__				(			self  :       List[Any]  ,     a  :       Optional[Any]  ,     a  :       int  ,     a  :       Optional[Any]  ,     a  :       Tuple  ,     a  :       Any  ,     a  :       Union[str, Any]  ,     a  :       Any			):






       '''simple docstring'''






       lowercase_	:    Any           =     TFDebertaVaModel(config=a			)
       lowercase_	:    int           =     {"input_ids": input_ids, "attention_mask": input_mask, "token_type_ids": token_type_ids}

       lowercase_	:    List[Any]           =     [input_ids, input_mask]
       lowercase_	:    Tuple           =     model(a			)

       lowercase_	:    Any           =     model(a			)

       self.parent.assertEqual(result.last_hidden_state.shape  ,     (self.batch_size, self.seq_length, self.hidden_size)			)




    def 				lowerCAmelCase__				(			self  :       Optional[int]  ,     a  :       List[Any]  ,     a  :       Dict  ,     a  :       List[str]  ,     a  :       Any  ,     a  :       List[str]  ,     a  :       Tuple  ,     a  :       List[str]			):






       '''simple docstring'''






       lowercase_	:    Any           =     TFDebertaVaForMaskedLM(config=a			)
       lowercase_	:    Tuple           =     {
           "input_ids": input_ids,
           "attention_mask": input_mask,
           "token_type_ids": token_type_ids,
       }
       lowercase_	:    str           =     model(a			)
       self.parent.assertEqual(result.logits.shape  ,     (self.batch_size, self.seq_length, self.vocab_size)			)




    def 				lowerCAmelCase__				(			self  :       int  ,     a  :       Dict  ,     a  :       List[Any]  ,     a  :       Optional[Any]  ,     a  :       str  ,     a  :       List[Any]  ,     a  :       Union[str, Any]  ,     a  :       Union[str, Any]			):






       '''simple docstring'''






       lowercase_	:    int           =     self.num_labels
       lowercase_	:    Optional[Any]           =     TFDebertaVaForSequenceClassification(config=a			)
       lowercase_	:    Tuple           =     {
           "input_ids": input_ids,
           "attention_mask": input_mask,
           "token_type_ids": token_type_ids,
       }

       lowercase_	:    Optional[int]           =     model(a			)
       self.parent.assertEqual(result.logits.shape  ,     (self.batch_size, self.num_labels)			)




    def 				lowerCAmelCase__				(			self  :       Optional[Any]  ,     a  :       Union[str, Any]  ,     a  :       Tuple  ,     a  :       Dict  ,     a  :       Optional[Any]  ,     a  :       str  ,     a  :       List[str]  ,     a  :       List[Any]			):






       '''simple docstring'''






       lowercase_	:    Optional[int]           =     self.num_labels
       lowercase_	:    Optional[int]           =     TFDebertaVaForTokenClassification(config=a			)
       lowercase_	:    List[str]           =     {
           "input_ids": input_ids,
           "attention_mask": input_mask,
           "token_type_ids": token_type_ids,
       }
       lowercase_	:    Optional[Any]           =     model(a			)
       self.parent.assertEqual(result.logits.shape  ,     (self.batch_size, self.seq_length, self.num_labels)			)




    def 				lowerCAmelCase__				(			self  :       str  ,     a  :       Tuple  ,     a  :       str  ,     a  :       List[str]  ,     a  :       List[str]  ,     a  :       List[Any]  ,     a  :       Union[str, Any]  ,     a  :       Optional[Any]			):






       '''simple docstring'''






       lowercase_	:    Dict           =     TFDebertaVaForQuestionAnswering(config=a			)
       lowercase_	:    Any           =     {
           "input_ids": input_ids,
           "attention_mask": input_mask,
           "token_type_ids": token_type_ids,
       }

       lowercase_	:    Tuple           =     model(a			)
       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 				lowerCAmelCase__				(			self  :       List[str]			):






       '''simple docstring'''






       lowercase_	:    List[Any]           =     self.prepare_config_and_inputs()
       (
           (
           lowercase_
       )    ,		(
           lowercase_
       )    ,		(
           lowercase_
       )    ,		(
           lowercase_
       )    ,		(
           lowercase_
       )    ,		(
           lowercase_
       )    ,		(
           lowercase_
       )    ,		
       )	:    Optional[Any]           =     config_and_inputs
       lowercase_	:    str           =     {"input_ids": input_ids, "token_type_ids": token_type_ids, "attention_mask": input_mask}
       return config, inputs_dict


@require_tf
class        _UpperCAmelCase						(		snake_case				,					snake_case				,					unittest.TestCase			):
    __lowerCamelCase:   List[str]		       =    (
        (
            TFDebertaVaModel,
            TFDebertaVaForMaskedLM,
            TFDebertaVaForQuestionAnswering,
            TFDebertaVaForSequenceClassification,
            TFDebertaVaForTokenClassification,
        )
        if is_tf_available()
        else ()
    )
    __lowerCamelCase:   Dict		       =    (
        {
            'feature-extraction': TFDebertaVaModel,
            'fill-mask': TFDebertaVaForMaskedLM,
            'question-answering': TFDebertaVaForQuestionAnswering,
            'text-classification': TFDebertaVaForSequenceClassification,
            'token-classification': TFDebertaVaForTokenClassification,
            'zero-shot': TFDebertaVaForSequenceClassification,
        }
        if is_tf_available()
        else {}
    )

    __lowerCamelCase:   Optional[int]		       =    False
    __lowerCamelCase:   List[Any]		       =    False




    def 				lowerCAmelCase__				(			self  :       Tuple			):






       '''simple docstring'''






       lowercase_	:    Tuple           =     TFDebertaVaModelTester(self			)
       lowercase_	:    Dict           =     ConfigTester(self  ,     config_class=a  ,     hidden_size=3_7			)




    def 				lowerCAmelCase__				(			self  :       Any			):






       '''simple docstring'''






       self.config_tester.run_common_tests()




    def 				lowerCAmelCase__				(			self  :       Tuple			):






       '''simple docstring'''






       lowercase_	:    List[str]           =     self.model_tester.prepare_config_and_inputs()
       self.model_tester.create_and_check_model(*a			)




    def 				lowerCAmelCase__				(			self  :       Optional[int]			):






       '''simple docstring'''






       lowercase_	:    List[str]           =     self.model_tester.prepare_config_and_inputs()
       self.model_tester.create_and_check_for_masked_lm(*a			)




    def 				lowerCAmelCase__				(			self  :       Tuple			):






       '''simple docstring'''






       lowercase_	:    Dict           =     self.model_tester.prepare_config_and_inputs()
       self.model_tester.create_and_check_for_question_answering(*a			)




    def 				lowerCAmelCase__				(			self  :       Dict			):






       '''simple docstring'''






       lowercase_	:    Tuple           =     self.model_tester.prepare_config_and_inputs()
       self.model_tester.create_and_check_for_sequence_classification(*a			)




    def 				lowerCAmelCase__				(			self  :       int			):






       '''simple docstring'''






       lowercase_	:    int           =     self.model_tester.prepare_config_and_inputs()
       self.model_tester.create_and_check_for_token_classification(*a			)





    @slow
    def 				lowerCAmelCase__				(			self  :       str			):






       '''simple docstring'''






       lowercase_	:    Any           =     TFDebertaVaModel.from_pretrained("kamalkraj/deberta-v2-xlarge"			)
       self.assertIsNotNone(a			)


@require_tf
class        _UpperCAmelCase						(		unittest.TestCase			):




    @unittest.skip(reason="Model not available yet"			)
    def 				lowerCAmelCase__				(			self  :       int			):






       '''simple docstring'''






       pass





    @slow
    def 				lowerCAmelCase__				(			self  :       List[Any]			):






       '''simple docstring'''






       lowercase_	:    Tuple           =     TFDebertaVaModel.from_pretrained("kamalkraj/deberta-v2-xlarge"			)
       lowercase_	:    Any           =     tf.constant([[0, 3_1_4_1_4, 2_3_2, 3_2_8, 7_4_0, 1_1_4_0, 1_2_6_9_5, 6_9, 4_6_0_7_8, 1_5_8_8, 2]]			)
       lowercase_	:    Dict           =     tf.constant([[0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]			)
       lowercase_	:    Optional[int]           =     model(a  ,     attention_mask=a			)[0]

       lowercase_	:    int           =     tf.constant(
           [[[0.2356, 0.1948, 0.0369], [-0.1063, 0.3586, -0.5152], [-0.6399, -0.0259, -0.2525]]]			)
       tf.debugging.assert_near(output[:, 1:4, 1:4]  ,     a  ,     atol=1e-4			)












'''simple docstring'''
import heapq as hq
import math
from collections.abc import Iterator


class        _UpperCAmelCase						:




    def __init__(			self  :       Optional[Any]  ,     a  :       Any			):






       '''simple docstring'''






       lowercase_	:    List[Any]           =     str(id_			)
       lowercase_	:    List[str]           =     None
       lowercase_	:    Tuple           =     None
       lowercase_	:    Dict           =     []
       lowercase_	:    Union[str, Any]           =     {}  # {vertex:distance}




    def __lt__(			self  :       Optional[Any]  ,     a  :       int			):






       '''simple docstring'''






       return self.key < other.key




    def __repr__(			self  :       Union[str, Any]			):






       '''simple docstring'''






       return self.id




    def 				lowerCAmelCase__				(			self  :       Union[str, Any]  ,     a  :       Optional[int]			):






       '''simple docstring'''






       self.neighbors.append(a			)





    def 				lowerCAmelCase__				(			self  :       Dict  ,     a  :       int  ,     a  :       Optional[int]			):






       '''simple docstring'''






       lowercase_	:    int           =     weight




def 		__SCREAMING_SNAKE_CASE					(  _UpperCamelCase						,		_UpperCamelCase						,		_UpperCamelCase						,		_UpperCamelCase							):


   """simple docstring"""




   graph[a - 1].add_neighbor(graph[b - 1]							)
   graph[b - 1].add_neighbor(graph[a - 1]							)
   # add the edges:
   graph[a - 1].add_edge(graph[b - 1]						,		_UpperCamelCase							)
   graph[b - 1].add_edge(graph[a - 1]						,		_UpperCamelCase							)




def 		__SCREAMING_SNAKE_CASE					(  _UpperCamelCase						,		_UpperCamelCase							):


   """simple docstring"""




   lowercase_	:    Any           =     []
   for u in graph:
      lowercase_	:    List[Any]           =     math.inf
      lowercase_	:    str           =     None
   lowercase_	:    Tuple           =     0
   lowercase_	:    Tuple           =     graph[:]
   while q:
      lowercase_	:    List[Any]           =     min(_UpperCamelCase							)
      q.remove(_UpperCamelCase							)
      for v in u.neighbors:
         if (v in q) and (u.edges[v.id] < v.key):
            lowercase_	:    Optional[int]           =     u
            lowercase_	:    Union[str, Any]           =     u.edges[v.id]
   for i in range(1						,		len(_UpperCamelCase							)							):
      a.append((int(graph[i].id							) + 1, int(graph[i].pi.id							) + 1)							)
   return a




def 		__SCREAMING_SNAKE_CASE					(  _UpperCamelCase						,		_UpperCamelCase							):


   """simple docstring"""




   for u in graph:
      lowercase_	:    str           =     math.inf
      lowercase_	:    int           =     None
   lowercase_	:    List[Any]           =     0

   lowercase_	:    str           =     list(_UpperCamelCase							)
   hq.heapify(_UpperCamelCase							)

   while h:
      lowercase_	:    List[Any]           =     hq.heappop(_UpperCamelCase							)
      for v in u.neighbors:
         if (v in h) and (u.edges[v.id] < v.key):
            lowercase_	:    str           =     u
            lowercase_	:    Optional[int]           =     u.edges[v.id]
            hq.heapify(_UpperCamelCase							)

   for i in range(1						,		len(_UpperCamelCase							)							):
      yield (int(graph[i].id							) + 1, int(graph[i].pi.id							) + 1)




def 		__SCREAMING_SNAKE_CASE					(  ):


   """simple docstring"""






if __name__ == "__main__":
 import doctest

 doctest.testmod()




