






"""simple docstring"""







from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


lowerCAmelCase_		:			Dict				   =					{
    '''auto_factory''': ['''get_values'''],
    '''configuration_auto''': ['''ALL_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CONFIG_MAPPING''', '''MODEL_NAMES_MAPPING''', '''AutoConfig'''],
    '''feature_extraction_auto''': ['''FEATURE_EXTRACTOR_MAPPING''', '''AutoFeatureExtractor'''],
    '''image_processing_auto''': ['''IMAGE_PROCESSOR_MAPPING''', '''AutoImageProcessor'''],
    '''processing_auto''': ['''PROCESSOR_MAPPING''', '''AutoProcessor'''],
    '''tokenization_auto''': ['''TOKENIZER_MAPPING''', '''AutoTokenizer'''],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase_		:			Any				   =					[
     '''MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING''',
     '''MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING''',
     '''MODEL_FOR_AUDIO_XVECTOR_MAPPING''',
     '''MODEL_FOR_BACKBONE_MAPPING''',
     '''MODEL_FOR_CAUSAL_IMAGE_MODELING_MAPPING''',
     '''MODEL_FOR_CAUSAL_LM_MAPPING''',
     '''MODEL_FOR_CTC_MAPPING''',
     '''MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING''',
     '''MODEL_FOR_DEPTH_ESTIMATION_MAPPING''',
     '''MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING''',
     '''MODEL_FOR_IMAGE_SEGMENTATION_MAPPING''',
     '''MODEL_FOR_INSTANCE_SEGMENTATION_MAPPING''',
     '''MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING''',
     '''MODEL_FOR_MASKED_LM_MAPPING''',
     '''MODEL_FOR_MASK_GENERATION_MAPPING''',
     '''MODEL_FOR_MULTIPLE_CHOICE_MAPPING''',
     '''MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING''',
     '''MODEL_FOR_OBJECT_DETECTION_MAPPING''',
     '''MODEL_FOR_PRETRAINING_MAPPING''',
     '''MODEL_FOR_QUESTION_ANSWERING_MAPPING''',
     '''MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING''',
     '''MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING''',
     '''MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING''',
     '''MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING''',
     '''MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING''',
     '''MODEL_FOR_TEXT_ENCODING_MAPPING''',
     '''MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING''',
     '''MODEL_FOR_UNIVERSAL_SEGMENTATION_MAPPING''',
     '''MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING''',
     '''MODEL_FOR_VISION_2_SEQ_MAPPING''',
     '''MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING''',
     '''MODEL_MAPPING''',
     '''MODEL_WITH_LM_HEAD_MAPPING''',
     '''MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING''',
     '''MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING''',
     '''AutoModel''',
     '''AutoBackbone''',
     '''AutoModelForAudioClassification''',
     '''AutoModelForAudioFrameClassification''',
     '''AutoModelForAudioXVector''',
     '''AutoModelForCausalLM''',
     '''AutoModelForCTC''',
     '''AutoModelForDepthEstimation''',
     '''AutoModelForImageClassification''',
     '''AutoModelForImageSegmentation''',
     '''AutoModelForInstanceSegmentation''',
     '''AutoModelForMaskGeneration''',
     '''AutoModelForTextEncoding''',
     '''AutoModelForMaskedImageModeling''',
     '''AutoModelForMaskedLM''',
     '''AutoModelForMultipleChoice''',
     '''AutoModelForNextSentencePrediction''',
     '''AutoModelForObjectDetection''',
     '''AutoModelForPreTraining''',
     '''AutoModelForQuestionAnswering''',
     '''AutoModelForSemanticSegmentation''',
     '''AutoModelForSeq2SeqLM''',
     '''AutoModelForSequenceClassification''',
     '''AutoModelForSpeechSeq2Seq''',
     '''AutoModelForTableQuestionAnswering''',
     '''AutoModelForTokenClassification''',
     '''AutoModelForUniversalSegmentation''',
     '''AutoModelForVideoClassification''',
     '''AutoModelForVision2Seq''',
     '''AutoModelForVisualQuestionAnswering''',
     '''AutoModelForDocumentQuestionAnswering''',
     '''AutoModelWithLMHead''',
     '''AutoModelForZeroShotImageClassification''',
     '''AutoModelForZeroShotObjectDetection''',
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase_		:			List[Any]				   =					[
     '''TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING''',
     '''TF_MODEL_FOR_CAUSAL_LM_MAPPING''',
     '''TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING''',
     '''TF_MODEL_FOR_MASK_GENERATION_MAPPING''',
     '''TF_MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING''',
     '''TF_MODEL_FOR_MASKED_LM_MAPPING''',
     '''TF_MODEL_FOR_MULTIPLE_CHOICE_MAPPING''',
     '''TF_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING''',
     '''TF_MODEL_FOR_PRETRAINING_MAPPING''',
     '''TF_MODEL_FOR_QUESTION_ANSWERING_MAPPING''',
     '''TF_MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING''',
     '''TF_MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING''',
     '''TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING''',
     '''TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING''',
     '''TF_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING''',
     '''TF_MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING''',
     '''TF_MODEL_FOR_TEXT_ENCODING_MAPPING''',
     '''TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING''',
     '''TF_MODEL_FOR_VISION_2_SEQ_MAPPING''',
     '''TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING''',
     '''TF_MODEL_MAPPING''',
     '''TF_MODEL_WITH_LM_HEAD_MAPPING''',
     '''TFAutoModel''',
     '''TFAutoModelForAudioClassification''',
     '''TFAutoModelForCausalLM''',
     '''TFAutoModelForImageClassification''',
     '''TFAutoModelForMaskedImageModeling''',
     '''TFAutoModelForMaskedLM''',
     '''TFAutoModelForMaskGeneration''',
     '''TFAutoModelForMultipleChoice''',
     '''TFAutoModelForNextSentencePrediction''',
     '''TFAutoModelForPreTraining''',
     '''TFAutoModelForDocumentQuestionAnswering''',
     '''TFAutoModelForQuestionAnswering''',
     '''TFAutoModelForSemanticSegmentation''',
     '''TFAutoModelForSeq2SeqLM''',
     '''TFAutoModelForSequenceClassification''',
     '''TFAutoModelForSpeechSeq2Seq''',
     '''TFAutoModelForTableQuestionAnswering''',
     '''TFAutoModelForTextEncoding''',
     '''TFAutoModelForTokenClassification''',
     '''TFAutoModelForVision2Seq''',
     '''TFAutoModelForZeroShotImageClassification''',
     '''TFAutoModelWithLMHead''',
 ]

try:
 if not is_flax_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase_		:			Any				   =					[
     '''FLAX_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING''',
     '''FLAX_MODEL_FOR_CAUSAL_LM_MAPPING''',
     '''FLAX_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING''',
     '''FLAX_MODEL_FOR_MASKED_LM_MAPPING''',
     '''FLAX_MODEL_FOR_MULTIPLE_CHOICE_MAPPING''',
     '''FLAX_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING''',
     '''FLAX_MODEL_FOR_PRETRAINING_MAPPING''',
     '''FLAX_MODEL_FOR_QUESTION_ANSWERING_MAPPING''',
     '''FLAX_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING''',
     '''FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING''',
     '''FLAX_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING''',
     '''FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING''',
     '''FLAX_MODEL_FOR_VISION_2_SEQ_MAPPING''',
     '''FLAX_MODEL_MAPPING''',
     '''FlaxAutoModel''',
     '''FlaxAutoModelForCausalLM''',
     '''FlaxAutoModelForImageClassification''',
     '''FlaxAutoModelForMaskedLM''',
     '''FlaxAutoModelForMultipleChoice''',
     '''FlaxAutoModelForNextSentencePrediction''',
     '''FlaxAutoModelForPreTraining''',
     '''FlaxAutoModelForQuestionAnswering''',
     '''FlaxAutoModelForSeq2SeqLM''',
     '''FlaxAutoModelForSequenceClassification''',
     '''FlaxAutoModelForSpeechSeq2Seq''',
     '''FlaxAutoModelForTokenClassification''',
     '''FlaxAutoModelForVision2Seq''',
 ]


if TYPE_CHECKING:
 from .auto_factory import get_values
 from .configuration_auto import ALL_PRETRAINED_CONFIG_ARCHIVE_MAP, CONFIG_MAPPING, MODEL_NAMES_MAPPING, AutoConfig
 from .feature_extraction_auto import FEATURE_EXTRACTOR_MAPPING, AutoFeatureExtractor
 from .image_processing_auto import IMAGE_PROCESSOR_MAPPING, AutoImageProcessor
 from .processing_auto import PROCESSOR_MAPPING, AutoProcessor
 from .tokenization_auto import TOKENIZER_MAPPING, AutoTokenizer

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_auto import (
      MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING,
      MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING,
      MODEL_FOR_AUDIO_XVECTOR_MAPPING,
      MODEL_FOR_BACKBONE_MAPPING,
      MODEL_FOR_CAUSAL_IMAGE_MODELING_MAPPING,
      MODEL_FOR_CAUSAL_LM_MAPPING,
      MODEL_FOR_CTC_MAPPING,
      MODEL_FOR_DEPTH_ESTIMATION_MAPPING,
      MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING,
      MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING,
      MODEL_FOR_IMAGE_SEGMENTATION_MAPPING,
      MODEL_FOR_INSTANCE_SEGMENTATION_MAPPING,
      MODEL_FOR_MASK_GENERATION_MAPPING,
      MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING,
      MODEL_FOR_MASKED_LM_MAPPING,
      MODEL_FOR_MULTIPLE_CHOICE_MAPPING,
      MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING,
      MODEL_FOR_OBJECT_DETECTION_MAPPING,
      MODEL_FOR_PRETRAINING_MAPPING,
      MODEL_FOR_QUESTION_ANSWERING_MAPPING,
      MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING,
      MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
      MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
      MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING,
      MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING,
      MODEL_FOR_TEXT_ENCODING_MAPPING,
      MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING,
      MODEL_FOR_UNIVERSAL_SEGMENTATION_MAPPING,
      MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING,
      MODEL_FOR_VISION_2_SEQ_MAPPING,
      MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING,
      MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING,
      MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING,
      MODEL_MAPPING,
      MODEL_WITH_LM_HEAD_MAPPING,
      AutoBackbone,
      AutoModel,
      AutoModelForAudioClassification,
      AutoModelForAudioFrameClassification,
      AutoModelForAudioXVector,
      AutoModelForCausalLM,
      AutoModelForCTC,
      AutoModelForDepthEstimation,
      AutoModelForDocumentQuestionAnswering,
      AutoModelForImageClassification,
      AutoModelForImageSegmentation,
      AutoModelForInstanceSegmentation,
      AutoModelForMaskedImageModeling,
      AutoModelForMaskedLM,
      AutoModelForMaskGeneration,
      AutoModelForMultipleChoice,
      AutoModelForNextSentencePrediction,
      AutoModelForObjectDetection,
      AutoModelForPreTraining,
      AutoModelForQuestionAnswering,
      AutoModelForSemanticSegmentation,
      AutoModelForSeqaSeqLM,
      AutoModelForSequenceClassification,
      AutoModelForSpeechSeqaSeq,
      AutoModelForTableQuestionAnswering,
      AutoModelForTextEncoding,
      AutoModelForTokenClassification,
      AutoModelForUniversalSegmentation,
      AutoModelForVideoClassification,
      AutoModelForVisionaSeq,
      AutoModelForVisualQuestionAnswering,
      AutoModelForZeroShotImageClassification,
      AutoModelForZeroShotObjectDetection,
      AutoModelWithLMHead,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_auto import (
      TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING,
      TF_MODEL_FOR_CAUSAL_LM_MAPPING,
      TF_MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING,
      TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING,
      TF_MODEL_FOR_MASK_GENERATION_MAPPING,
      TF_MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING,
      TF_MODEL_FOR_MASKED_LM_MAPPING,
      TF_MODEL_FOR_MULTIPLE_CHOICE_MAPPING,
      TF_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING,
      TF_MODEL_FOR_PRETRAINING_MAPPING,
      TF_MODEL_FOR_QUESTION_ANSWERING_MAPPING,
      TF_MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING,
      TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
      TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
      TF_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING,
      TF_MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING,
      TF_MODEL_FOR_TEXT_ENCODING_MAPPING,
      TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING,
      TF_MODEL_FOR_VISION_2_SEQ_MAPPING,
      TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING,
      TF_MODEL_MAPPING,
      TF_MODEL_WITH_LM_HEAD_MAPPING,
      TFAutoModel,
      TFAutoModelForAudioClassification,
      TFAutoModelForCausalLM,
      TFAutoModelForDocumentQuestionAnswering,
      TFAutoModelForImageClassification,
      TFAutoModelForMaskedImageModeling,
      TFAutoModelForMaskedLM,
      TFAutoModelForMaskGeneration,
      TFAutoModelForMultipleChoice,
      TFAutoModelForNextSentencePrediction,
      TFAutoModelForPreTraining,
      TFAutoModelForQuestionAnswering,
      TFAutoModelForSemanticSegmentation,
      TFAutoModelForSeqaSeqLM,
      TFAutoModelForSequenceClassification,
      TFAutoModelForSpeechSeqaSeq,
      TFAutoModelForTableQuestionAnswering,
      TFAutoModelForTextEncoding,
      TFAutoModelForTokenClassification,
      TFAutoModelForVisionaSeq,
      TFAutoModelForZeroShotImageClassification,
      TFAutoModelWithLMHead,
  )

 try:
  if not is_flax_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_flax_auto import (
      FLAX_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING,
      FLAX_MODEL_FOR_CAUSAL_LM_MAPPING,
      FLAX_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING,
      FLAX_MODEL_FOR_MASKED_LM_MAPPING,
      FLAX_MODEL_FOR_MULTIPLE_CHOICE_MAPPING,
      FLAX_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING,
      FLAX_MODEL_FOR_PRETRAINING_MAPPING,
      FLAX_MODEL_FOR_QUESTION_ANSWERING_MAPPING,
      FLAX_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
      FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
      FLAX_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING,
      FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING,
      FLAX_MODEL_FOR_VISION_2_SEQ_MAPPING,
      FLAX_MODEL_MAPPING,
      FlaxAutoModel,
      FlaxAutoModelForCausalLM,
      FlaxAutoModelForImageClassification,
      FlaxAutoModelForMaskedLM,
      FlaxAutoModelForMultipleChoice,
      FlaxAutoModelForNextSentencePrediction,
      FlaxAutoModelForPreTraining,
      FlaxAutoModelForQuestionAnswering,
      FlaxAutoModelForSeqaSeqLM,
      FlaxAutoModelForSequenceClassification,
      FlaxAutoModelForSpeechSeqaSeq,
      FlaxAutoModelForTokenClassification,
      FlaxAutoModelForVisionaSeq,
  )

else:
 import sys

 lowerCAmelCase_		:			List[Any]				   =					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)








"""simple docstring"""







import unittest

import numpy as np

from transformers import ElectraConfig, 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():
 from transformers.models.electra.modeling_flax_electra import (
     FlaxElectraForCausalLM,
     FlaxElectraForMaskedLM,
     FlaxElectraForMultipleChoice,
     FlaxElectraForPreTraining,
     FlaxElectraForQuestionAnswering,
     FlaxElectraForSequenceClassification,
     FlaxElectraForTokenClassification,
     FlaxElectraModel,
 )





class      UpperCamelCase_       (				unittest.TestCase     ):



  def __init__(					self       ,						snake_case__       ,						snake_case__=13       ,						snake_case__=7       ,						snake_case__=True       ,						snake_case__=True       ,						snake_case__=True       ,						snake_case__=True       ,						snake_case__=99       ,						snake_case__=24       ,						snake_case__=32       ,						snake_case__=5       ,						snake_case__=4       ,						snake_case__=37       ,						snake_case__="gelu"       ,						snake_case__=0.1       ,						snake_case__=0.1       ,						snake_case__=5_12       ,						snake_case__=16       ,						snake_case__=2       ,						snake_case__=0.02       ,						snake_case__=4       ,						)	->	int:



         """simple docstring"""





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



  def 						UpperCamelCase_ (					self )	->	Optional[Any]:



         """simple docstring"""





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

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

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

         UpperCAmelCase					=	ElectraConfig(
             vocab_size=self.vocab_size       ,						hidden_size=self.hidden_size       ,						embedding_size=self.embedding_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       ,						)

         return config, input_ids, token_type_ids, attention_mask



  def 						UpperCamelCase_ (					self )	->	List[str]:



         """simple docstring"""





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





@require_flax
class      UpperCamelCase_       (				a_      ,    unittest.TestCase     ):
  _A				:    str =		True

  _A				:    List[Any] =		(
      (
          FlaxElectraModel,
          FlaxElectraForCausalLM,
          FlaxElectraForMaskedLM,
          FlaxElectraForPreTraining,
          FlaxElectraForTokenClassification,
          FlaxElectraForQuestionAnswering,
          FlaxElectraForMultipleChoice,
          FlaxElectraForSequenceClassification,
      )
      if is_flax_available()
      else ()
  )



  def 						UpperCamelCase_ (					self )	->	str:



         """simple docstring"""





         UpperCAmelCase					=	FlaxElectraModelTester(self )



  @slow
  def 						UpperCamelCase_ (					self )	->	Tuple:



         """simple docstring"""





         for model_class_name in self.all_model_classes:
                if model_class_name == FlaxElectraForMaskedLM:
                       UpperCAmelCase					=	model_class_name.from_pretrained("""google/electra-small-generator""" )
                else:
                       UpperCAmelCase					=	model_class_name.from_pretrained("""google/electra-small-discriminator""" )
                UpperCAmelCase					=	model(np.ones((1, 1) ) )
                self.assertIsNotNone(snake_case__ )
