






from __future__ import annotations

import unittest

from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, 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 numpy as np
 import tensorflow as tf

 from transformers import (
     TF_FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
     FlaubertConfig,
     TFFlaubertForMultipleChoice,
     TFFlaubertForQuestionAnsweringSimple,
     TFFlaubertForSequenceClassification,
     TFFlaubertForTokenClassification,
     TFFlaubertModel,
     TFFlaubertWithLMHeadModel,
 )







class      UpperCAmelCase_		:



      """simple docstring"""
      def __init__(							self       ,							SCREAMING_SNAKE_CASE_       ,							)							-> List[Any]:
          UpperCamelCase			:Any      				=  parent
          UpperCamelCase			:Union[str, Any]      				=  13
          UpperCamelCase			:Tuple      				=  7
          UpperCamelCase			:Dict      				=  True
          UpperCamelCase			:Union[str, Any]      				=  True
          UpperCamelCase			:Tuple      				=  True
          UpperCamelCase			:Optional[int]      				=  True
          UpperCamelCase			:List[str]      				=  True
          UpperCamelCase			:List[Any]      				=  False
          UpperCamelCase			:Optional[Any]      				=  False
          UpperCamelCase			:List[Any]      				=  False
          UpperCamelCase			:List[Any]      				=  2
          UpperCamelCase			:List[Any]      				=  99
          UpperCamelCase			:Union[str, Any]      				=  0
          UpperCamelCase			:Union[str, Any]      				=  32
          UpperCamelCase			:Union[str, Any]      				=  2
          UpperCamelCase			:Dict      				=  4
          UpperCamelCase			:Dict      				=  0.1
          UpperCamelCase			:Tuple      				=  0.1
          UpperCamelCase			:Optional[Any]      				=  512
          UpperCamelCase			:List[Any]      				=  16
          UpperCamelCase			:Dict      				=  2
          UpperCamelCase			:Any      				=  0.02
          UpperCamelCase			:str      				=  3
          UpperCamelCase			:str      				=  4
          UpperCamelCase			:Union[str, Any]      				=  '''last'''
          UpperCamelCase			:Optional[int]      				=  True
          UpperCamelCase			:Any      				=  None
          UpperCamelCase			:Optional[Any]      				=  0
      def        UpperCAmelCase		(							self					)							-> Dict:
          UpperCamelCase			:str      				=  ids_tensor([self.batch_size, self.seq_length]       ,							self.vocab_size					)
          UpperCamelCase			:Union[str, Any]      				=  random_attention_mask([self.batch_size, self.seq_length]       ,							dtype=tf.floataa					)

          UpperCamelCase			:Tuple      				=  None
          if self.use_input_lengths:
              UpperCamelCase			:List[str]      				=  (
                  ids_tensor([self.batch_size]       ,							vocab_size=2					) + self.seq_length - 2
              )  # small variation of seq_length

          UpperCamelCase			:Tuple      				=  None
          if self.use_token_type_ids:
              UpperCamelCase			:Optional[int]      				=  ids_tensor([self.batch_size, self.seq_length]       ,							self.n_langs					)

          UpperCamelCase			:Any      				=  None
          UpperCamelCase			:Tuple      				=  None
          UpperCamelCase			:Tuple      				=  None
          if self.use_labels:
              UpperCamelCase			:Dict      				=  ids_tensor([self.batch_size]       ,							self.type_sequence_label_size					)
              UpperCamelCase			:Tuple      				=  ids_tensor([self.batch_size, self.seq_length]       ,							self.num_labels					)
              UpperCamelCase			:List[str]      				=  ids_tensor([self.batch_size]       ,							2       ,							dtype=tf.floataa					)
              UpperCamelCase			:Tuple      				=  ids_tensor([self.batch_size]       ,							self.num_choices					)

          UpperCamelCase			:Optional[Any]      				=  FlaubertConfig(
              vocab_size=self.vocab_size       ,							n_special=self.n_special       ,							emb_dim=self.hidden_size       ,							n_layers=self.num_hidden_layers       ,							n_heads=self.num_attention_heads       ,							dropout=self.hidden_dropout_prob       ,							attention_dropout=self.attention_probs_dropout_prob       ,							gelu_activation=self.gelu_activation       ,							sinusoidal_embeddings=self.sinusoidal_embeddings       ,							asm=self.asm       ,							causal=self.causal       ,							n_langs=self.n_langs       ,							max_position_embeddings=self.max_position_embeddings       ,							initializer_range=self.initializer_range       ,							summary_type=self.summary_type       ,							use_proj=self.use_proj       ,							bos_token_id=self.bos_token_id       ,							)

          return (
              config,
              input_ids,
              token_type_ids,
              input_lengths,
              sequence_labels,
              token_labels,
              is_impossible_labels,
              choice_labels,
              input_mask,
          )
      def        UpperCAmelCase		(							self       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							)							-> Union[str, Any]:
          UpperCamelCase			:List[Any]      				=  TFFlaubertModel(config=__lowercase					)
          UpperCamelCase			:Dict      				=  {'''input_ids''': input_ids, '''lengths''': input_lengths, '''langs''': token_type_ids}
          UpperCamelCase			:Optional[Any]      				=  model(__lowercase					)

          UpperCamelCase			:int      				=  [input_ids, input_mask]
          UpperCamelCase			:List[str]      				=  model(__lowercase					)
          self.parent.assertEqual(result.last_hidden_state.shape       ,							(self.batch_size, self.seq_length, self.hidden_size)					)
      def        UpperCAmelCase		(							self       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							)							-> Any:
          UpperCamelCase			:List[Any]      				=  TFFlaubertWithLMHeadModel(__lowercase					)

          UpperCamelCase			:Dict      				=  {'''input_ids''': input_ids, '''lengths''': input_lengths, '''langs''': token_type_ids}
          UpperCamelCase			:Optional[Any]      				=  model(__lowercase					)

          self.parent.assertEqual(result.logits.shape       ,							(self.batch_size, self.seq_length, self.vocab_size)					)
      def        UpperCAmelCase		(							self       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							)							-> int:
          UpperCamelCase			:List[str]      				=  TFFlaubertForQuestionAnsweringSimple(__lowercase					)

          UpperCamelCase			:List[str]      				=  {'''input_ids''': input_ids, '''lengths''': input_lengths}

          UpperCamelCase			:List[Any]      				=  model(__lowercase					)

          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        UpperCAmelCase		(							self       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							)							-> List[str]:
          UpperCamelCase			:Union[str, Any]      				=  TFFlaubertForSequenceClassification(__lowercase					)

          UpperCamelCase			:Dict      				=  {'''input_ids''': input_ids, '''lengths''': input_lengths}

          UpperCamelCase			:Dict      				=  model(__lowercase					)

          self.parent.assertEqual(result.logits.shape       ,							(self.batch_size, self.type_sequence_label_size)					)
      def        UpperCAmelCase		(							self       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							)							-> int:
          UpperCamelCase			:int      				=  self.num_labels
          UpperCamelCase			:Any      				=  TFFlaubertForTokenClassification(config=__lowercase					)
          UpperCamelCase			:Union[str, Any]      				=  {'''input_ids''': input_ids, '''attention_mask''': input_mask, '''token_type_ids''': token_type_ids}
          UpperCamelCase			:Dict      				=  model(__lowercase					)
          self.parent.assertEqual(result.logits.shape       ,							(self.batch_size, self.seq_length, self.num_labels)					)
      def        UpperCAmelCase		(							self       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							)							-> Optional[Any]:
          UpperCamelCase			:Any      				=  self.num_choices
          UpperCamelCase			:Optional[int]      				=  TFFlaubertForMultipleChoice(config=__lowercase					)
          UpperCamelCase			:Tuple      				=  tf.tile(tf.expand_dims(__lowercase       ,							1					)       ,							(1, self.num_choices, 1)					)
          UpperCamelCase			:List[Any]      				=  tf.tile(tf.expand_dims(__lowercase       ,							1					)       ,							(1, self.num_choices, 1)					)
          UpperCamelCase			:List[str]      				=  tf.tile(tf.expand_dims(__lowercase       ,							1					)       ,							(1, self.num_choices, 1)					)
          UpperCamelCase			:str      				=  {
              '''input_ids''': multiple_choice_inputs_ids,
              '''attention_mask''': multiple_choice_input_mask,
              '''token_type_ids''': multiple_choice_token_type_ids,
          }
          UpperCamelCase			:str      				=  model(__lowercase					)
          self.parent.assertEqual(result.logits.shape       ,							(self.batch_size, self.num_choices)					)




      def        UpperCAmelCase		(							self					)							-> Union[str, Any]:
          UpperCamelCase			:Optional[int]      				=  self.prepare_config_and_inputs()
          (
              (
              UpperCamelCase  
          )				,  (
              UpperCamelCase  
          )				,  (
              UpperCamelCase  
          )				,  (
              UpperCamelCase  
          )				,  (
              UpperCamelCase  
          )				,  (
              UpperCamelCase  
          )				,  (
              UpperCamelCase  
          )				,  (
              UpperCamelCase  
          )				,  (
              UpperCamelCase  
          )				,    
          )			:List[str]      				=  config_and_inputs
          UpperCamelCase			:List[str]      				=  {
              '''input_ids''': input_ids,
              '''token_type_ids''': token_type_ids,
              '''langs''': token_type_ids,
              '''lengths''': input_lengths,
          }
          return config, inputs_dict







@require_tf
class      UpperCAmelCase_		(   lowercase,      lowercase,      unittest.TestCase					):



      """simple docstring"""
      UpperCamelCase_							:   Tuple 	=(
          (
              TFFlaubertModel,
              TFFlaubertWithLMHeadModel,
              TFFlaubertForSequenceClassification,
              TFFlaubertForQuestionAnsweringSimple,
              TFFlaubertForTokenClassification,
              TFFlaubertForMultipleChoice,
          )
          if is_tf_available()
          else ()
      )
      UpperCamelCase_							:   List[Any] 	=(
          (TFFlaubertWithLMHeadModel,) if is_tf_available() else ()
      )  # TODO (PVP): Check other models whether language generation is also applicable
      UpperCamelCase_							:   Any 	=(
          {
              'feature-extraction': TFFlaubertModel,
              'fill-mask': TFFlaubertWithLMHeadModel,
              'question-answering': TFFlaubertForQuestionAnsweringSimple,
              'text-classification': TFFlaubertForSequenceClassification,
              'token-classification': TFFlaubertForTokenClassification,
              'zero-shot': TFFlaubertForSequenceClassification,
          }
          if is_tf_available()
          else {}
      )
      UpperCamelCase_							:   List[Any] 	=False
      UpperCamelCase_							:   Dict 	=False
      def        UpperCAmelCase		(							self       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_					)							-> Optional[Any]:







          if (
              pipeline_test_casse_name == "QAPipelineTests"
              and tokenizer_name is not None
              and not tokenizer_name.endswith('''Fast'''					)
          ):
              # `QAPipelineTests` fails for a few models when the slower tokenizer are used.
              # (The slower tokenizers were never used for pipeline tests before the pipeline testing rework)
              # TODO: check (and possibly fix) the `QAPipelineTests` with slower tokenizer
              return True

          return False
      def        UpperCAmelCase		(							self					)							-> List[Any]:
          UpperCamelCase			:int      				=  TFFlaubertModelTester(self					)
          UpperCamelCase			:Dict      				=  ConfigTester(self       ,							config_class=__lowercase       ,							emb_dim=37					)
      def        UpperCAmelCase		(							self					)							-> List[Any]:
          self.config_tester.run_common_tests()
      def        UpperCAmelCase		(							self					)							-> Optional[Any]:
          UpperCamelCase			:str      				=  self.model_tester.prepare_config_and_inputs()
          self.model_tester.create_and_check_flaubert_model(*__lowercase					)
      def        UpperCAmelCase		(							self					)							-> int:
          UpperCamelCase			:Any      				=  self.model_tester.prepare_config_and_inputs()
          self.model_tester.create_and_check_flaubert_lm_head(*__lowercase					)
      def        UpperCAmelCase		(							self					)							-> Tuple:
          UpperCamelCase			:Union[str, Any]      				=  self.model_tester.prepare_config_and_inputs()
          self.model_tester.create_and_check_flaubert_qa(*__lowercase					)
      def        UpperCAmelCase		(							self					)							-> Tuple:
          UpperCamelCase			:List[str]      				=  self.model_tester.prepare_config_and_inputs()
          self.model_tester.create_and_check_flaubert_sequence_classif(*__lowercase					)
      def        UpperCAmelCase		(							self					)							-> Optional[int]:
          UpperCamelCase			:int      				=  self.model_tester.prepare_config_and_inputs()
          self.model_tester.create_and_check_flaubert_for_token_classification(*__lowercase					)
      def        UpperCAmelCase		(							self					)							-> Optional[Any]:
          UpperCamelCase			:Tuple      				=  self.model_tester.prepare_config_and_inputs()
          self.model_tester.create_and_check_flaubert_for_multiple_choice(*__lowercase					)




      @slow
      def        UpperCAmelCase		(							self					)							-> Any:







          for model_name in TF_FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
              UpperCamelCase			:Dict      				=  TFFlaubertModel.from_pretrained(__lowercase					)
              self.assertIsNotNone(__lowercase					)







@require_tf
@require_sentencepiece
@require_tokenizers
class      UpperCAmelCase_		(   unittest.TestCase					):



      """simple docstring"""
      @slow
      def        UpperCAmelCase		(							self					)							-> Dict:
          UpperCamelCase			:int      				=  TFFlaubertModel.from_pretrained('''jplu/tf-flaubert-small-cased'''					)

          UpperCamelCase			:Any      				=  tf.convert_to_tensor(
              [[0, 158, 735, 2592, 1424, 6727, 82, 1]]       ,							dtype=tf.intaa       ,							)  # "J'aime flaubert !"

          UpperCamelCase			:Optional[int]      				=  model(__lowercase					)[0]
          UpperCamelCase			:str      				=  tf.TensorShape((1, 8, 512)					)
          self.assertEqual(output.shape       ,							__lowercase					)
          # compare the actual values for a slice.
          UpperCamelCase			:str      				=  tf.convert_to_tensor(
              [
                  [
                      [-1.876_8773, -1.56_6555, 0.2707_2418],
                      [-1.692_0038, -0.587_3505, 1.932_9599],
                      [-2.956_3985, -1.699_3835, 1.797_2052],
                  ]
              ]       ,							dtype=tf.floataa       ,							)

          self.assertTrue(np.allclose(output[:, :3, :3].numpy()       ,							expected_slice.numpy()       ,							atol=1e-4					)					)








'''simple docstring'''

class 	lowerCAmelCase  :







       def __init__(				self      :			List[Any]    ,   __lowercase      :			str    ,   __lowercase      :			Any    ,   __lowercase      :			str   ):







            """simple docstring"""







            __lowercase      		=name
            __lowercase      		=value
            __lowercase      		=weight







       def __repr__(				self      :			List[str]   ):







            """simple docstring"""







            return f'''{self.__class__.__name__}({self.name}, {self.value}, {self.weight})'''







       def       snake_case (				self      :			List[Any]   ):







            """simple docstring"""







            return self.value







       def       snake_case (				self      :			str   ):







            """simple docstring"""







            return self.name







       def       snake_case (				self      :			Optional[Any]   ):







            """simple docstring"""







            return self.weight







       def       snake_case (				self      :			Tuple   ):







            """simple docstring"""







            return self.value / self.weight






def 					__UpperCamelCase				(						lowercase__    :	Dict,       lowercase__    :	List[str],       lowercase__    :	str			):






     '''simple docstring'''





     __lowercase      		=[]
     for i in range(len(lowercase__			)			):
          menu.append(Things(name[i],       value[i],       weight[i]			)			)
     return menu

def 					__UpperCamelCase				(						lowercase__    :	List[Any],       lowercase__    :	List[Any],       lowercase__    :	str			):






     '''simple docstring'''





     __lowercase      		=sorted(lowercase__,       key=lowercase__,       reverse=lowercase__			)
     __lowercase      		=[]
     __lowercase		,  __lowercase      		=0.0, 0.0
     for i in range(len(lowercase__			)			):
          if (total_cost + items_copy[i].get_weight()) <= max_cost:
               result.append(items_copy[i]			)
               total_cost += items_copy[i].get_weight()
               total_value += items_copy[i].get_value()
     return (result, total_value)

def 					__UpperCamelCase				(						):






     '''simple docstring'''







if __name__ == "__main__":
       import doctest

       doctest.testmod()


