






from typing import Callable, Optional, Union

from ...configuration_utils import PretrainedConfig
from ...utils import logging


_UpperCAmelCase			:		str   				=    logging.get_logger(__name__)

_UpperCAmelCase			:		str   				=    {
    "microsoft/xprophetnet-large-wiki100-cased": (
        "https://huggingface.co/microsoft/xprophetnet-large-wiki100-cased/resolve/main/config.json"
    ),
}
class  lowerCAmelCase_       (				snake_case__					):
							UpperCamelCase_		:int		      =    'xlm-prophetnet'
							UpperCamelCase_		:List[str]		      =    ['past_key_values']
							UpperCamelCase_		:Dict		      =    {
							    'num_attention_heads': 'num_encoder_attention_heads',
							}




							def __init__(   self     :   Optional[Any] ,							SCREAMING_SNAKE_CASE_     :   Optional[float] = 0.1 ,							SCREAMING_SNAKE_CASE_     :   Optional[Union[str, Callable]] = "gelu" ,							SCREAMING_SNAKE_CASE_     :   Optional[int] = 30_522 ,							SCREAMING_SNAKE_CASE_     :   Optional[int] = 1_024 ,							SCREAMING_SNAKE_CASE_     :   Optional[int] = 4_096 ,							SCREAMING_SNAKE_CASE_     :   Optional[int] = 12 ,							SCREAMING_SNAKE_CASE_     :   Optional[int] = 16 ,							SCREAMING_SNAKE_CASE_     :   Optional[int] = 4_096 ,							SCREAMING_SNAKE_CASE_     :   Optional[int] = 12 ,							SCREAMING_SNAKE_CASE_     :   Optional[int] = 16 ,							SCREAMING_SNAKE_CASE_     :   Optional[float] = 0.1 ,							SCREAMING_SNAKE_CASE_     :   Optional[float] = 0.1 ,							SCREAMING_SNAKE_CASE_     :   Optional[int] = 512 ,							SCREAMING_SNAKE_CASE_     :   Optional[float] = 0.02 ,							SCREAMING_SNAKE_CASE_     :   Optional[bool] = True ,							SCREAMING_SNAKE_CASE_     :   Optional[bool] = True ,							SCREAMING_SNAKE_CASE_     :   Optional[int] = 0 ,							SCREAMING_SNAKE_CASE_     :   Optional[int] = 2 ,							SCREAMING_SNAKE_CASE_     :   Optional[int] = 32 ,							SCREAMING_SNAKE_CASE_     :   Optional[int] = 128 ,							SCREAMING_SNAKE_CASE_     :   Optional[bool] = False ,							SCREAMING_SNAKE_CASE_     :   Optional[float] = 0.0 ,							SCREAMING_SNAKE_CASE_     :   Optional[bool] = True ,							SCREAMING_SNAKE_CASE_     :   Optional[int] = 0 ,							SCREAMING_SNAKE_CASE_     :   Optional[int] = 1 ,							SCREAMING_SNAKE_CASE_     :   Optional[int] = 2 ,							**SCREAMING_SNAKE_CASE_     :   List[Any] ,							):
											lowerCAmelCase__      			=						vocab_size
											lowerCAmelCase__      			=						hidden_size
											lowerCAmelCase__      			=						encoder_ffn_dim
											lowerCAmelCase__      			=						num_encoder_layers
											lowerCAmelCase__      			=						num_encoder_attention_heads
											lowerCAmelCase__      			=						decoder_ffn_dim
											lowerCAmelCase__      			=						num_decoder_layers
											lowerCAmelCase__      			=						num_decoder_attention_heads
											lowerCAmelCase__      			=						max_position_embeddings
											lowerCAmelCase__      			=						init_std  # Normal(0, this parameter)
											lowerCAmelCase__      			=						activation_function

											# parameters for xlmprophetnet
											lowerCAmelCase__      			=						ngram
											lowerCAmelCase__      			=						num_buckets
											lowerCAmelCase__      			=						relative_max_distance
											lowerCAmelCase__      			=						disable_ngram_loss
											lowerCAmelCase__      			=						eps

											# 3 Types of Dropout
											lowerCAmelCase__      			=						attention_dropout
											lowerCAmelCase__      			=						activation_dropout
											lowerCAmelCase__      			=						dropout

											lowerCAmelCase__      			=						use_cache

											super().__init__(
											    pad_token_id=SCREAMING_SNAKE_CASE_ ,							bos_token_id=SCREAMING_SNAKE_CASE_ ,							eos_token_id=SCREAMING_SNAKE_CASE_ ,							is_encoder_decoder=SCREAMING_SNAKE_CASE_ ,							add_cross_attention=SCREAMING_SNAKE_CASE_ ,							decoder_start_token_id=SCREAMING_SNAKE_CASE_ ,							**SCREAMING_SNAKE_CASE_ ,							)




							@property
							def 						__snake_case					(   self     :   Dict	):
											return self.num_encoder_layers + self.num_decoder_layers




							@num_hidden_layers.setter
							def 						__snake_case					(   self     :   Any ,							SCREAMING_SNAKE_CASE_     :   int	):
											raise NotImplementedError(
											    '''This model does not support the setting of `num_hidden_layers`. Please set `num_encoder_layers` and'''
											    ''' `num_decoder_layers`.'''	)













from __future__ import annotations

import unittest

from transformers import FunnelConfig, is_tf_available
from transformers.testing_utils import require_tf

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 (
			    TFFunnelBaseModel,
			    TFFunnelForMaskedLM,
			    TFFunnelForMultipleChoice,
			    TFFunnelForPreTraining,
			    TFFunnelForQuestionAnswering,
			    TFFunnelForSequenceClassification,
			    TFFunnelForTokenClassification,
			    TFFunnelModel,
			)
class  lowerCAmelCase_       :




							def __init__(   self     :   Dict ,							SCREAMING_SNAKE_CASE_     :   str ,							SCREAMING_SNAKE_CASE_     :   Union[str, Any]=13 ,							SCREAMING_SNAKE_CASE_     :   str=7 ,							SCREAMING_SNAKE_CASE_     :   Tuple=True ,							SCREAMING_SNAKE_CASE_     :   Union[str, Any]=True ,							SCREAMING_SNAKE_CASE_     :   List[Any]=True ,							SCREAMING_SNAKE_CASE_     :   Optional[int]=True ,							SCREAMING_SNAKE_CASE_     :   Optional[int]=99 ,							SCREAMING_SNAKE_CASE_     :   Optional[Any]=[1, 1, 2] ,							SCREAMING_SNAKE_CASE_     :   List[str]=1 ,							SCREAMING_SNAKE_CASE_     :   str=32 ,							SCREAMING_SNAKE_CASE_     :   Dict=4 ,							SCREAMING_SNAKE_CASE_     :   Optional[Any]=8 ,							SCREAMING_SNAKE_CASE_     :   Dict=37 ,							SCREAMING_SNAKE_CASE_     :   Tuple="gelu_new" ,							SCREAMING_SNAKE_CASE_     :   Dict=0.1 ,							SCREAMING_SNAKE_CASE_     :   Any=0.1 ,							SCREAMING_SNAKE_CASE_     :   Any=0.0 ,							SCREAMING_SNAKE_CASE_     :   Tuple=512 ,							SCREAMING_SNAKE_CASE_     :   str=3 ,							SCREAMING_SNAKE_CASE_     :   int=0.02 ,							SCREAMING_SNAKE_CASE_     :   Optional[int]=3 ,							SCREAMING_SNAKE_CASE_     :   Any=4 ,							SCREAMING_SNAKE_CASE_     :   Optional[int]=None ,							SCREAMING_SNAKE_CASE_     :   Optional[Any]=False ,							):
											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__      			=						block_sizes
											lowerCAmelCase__      			=						num_decoder_layers
											lowerCAmelCase__      			=						d_model
											lowerCAmelCase__      			=						n_head
											lowerCAmelCase__      			=						d_head
											lowerCAmelCase__      			=						d_inner
											lowerCAmelCase__      			=						hidden_act
											lowerCAmelCase__      			=						hidden_dropout
											lowerCAmelCase__      			=						attention_dropout
											lowerCAmelCase__      			=						activation_dropout
											lowerCAmelCase__      			=						max_position_embeddings
											lowerCAmelCase__      			=						type_vocab_size
											lowerCAmelCase__      			=						2
											lowerCAmelCase__      			=						num_labels
											lowerCAmelCase__      			=						num_choices
											lowerCAmelCase__      			=						scope
											lowerCAmelCase__      			=						initializer_std

											# Used in the tests to check the size of the first attention layer
											lowerCAmelCase__      			=						n_head
											# Used in the tests to check the size of the first hidden state
											lowerCAmelCase__      			=						self.d_model
											# Used in the tests to check the number of output hidden states/attentions
											lowerCAmelCase__      			=						sum(self.block_sizes	) + (0 if base else self.num_decoder_layers)
											# FunnelModel adds two hidden layers: input embeddings and the sum of the upsampled encoder hidden state with
											# the last hidden state of the first block (which is the first hidden state of the decoder).
											if not base:
															lowerCAmelCase__      			=						self.num_hidden_layers + 2




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

											lowerCAmelCase__      			=						None
											if self.use_input_mask:
															lowerCAmelCase__      			=						random_attention_mask([self.batch_size, self.seq_length]	)

											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__      			=						FunnelConfig(
											    vocab_size=self.vocab_size ,							block_sizes=self.block_sizes ,							num_decoder_layers=self.num_decoder_layers ,							d_model=self.d_model ,							n_head=self.n_head ,							d_head=self.d_head ,							d_inner=self.d_inner ,							hidden_act=self.hidden_act ,							hidden_dropout=self.hidden_dropout ,							attention_dropout=self.attention_dropout ,							activation_dropout=self.activation_dropout ,							max_position_embeddings=self.max_position_embeddings ,							type_vocab_size=self.type_vocab_size ,							initializer_std=self.initializer_std ,							)

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




							def 						__snake_case					(   self     :   List[str] ,							SCREAMING_SNAKE_CASE_     :   str ,							SCREAMING_SNAKE_CASE_     :   int ,							SCREAMING_SNAKE_CASE_     :   int ,							SCREAMING_SNAKE_CASE_     :   int ,							SCREAMING_SNAKE_CASE_     :   int ,							SCREAMING_SNAKE_CASE_     :   List[Any] ,							SCREAMING_SNAKE_CASE_     :   Dict ,							):
											lowerCAmelCase__      			=						TFFunnelModel(config=SCREAMING_SNAKE_CASE_	)
											lowerCAmelCase__      			=						{'''input_ids''': input_ids, '''attention_mask''': input_mask, '''token_type_ids''': token_type_ids}
											lowerCAmelCase__      			=						model(SCREAMING_SNAKE_CASE_	)

											lowerCAmelCase__      			=						[input_ids, input_mask]
											lowerCAmelCase__      			=						model(SCREAMING_SNAKE_CASE_	)

											lowerCAmelCase__      			=						model(SCREAMING_SNAKE_CASE_	)
											self.parent.assertEqual(result.last_hidden_state.shape ,							(self.batch_size, self.seq_length, self.d_model)	)

											lowerCAmelCase__      			=						False
											lowerCAmelCase__      			=						TFFunnelModel(config=SCREAMING_SNAKE_CASE_	)
											lowerCAmelCase__      			=						model(SCREAMING_SNAKE_CASE_	)
											self.parent.assertEqual(result.last_hidden_state.shape ,							(self.batch_size, self.seq_length, self.d_model)	)

											lowerCAmelCase__      			=						False
											lowerCAmelCase__      			=						TFFunnelModel(config=SCREAMING_SNAKE_CASE_	)
											lowerCAmelCase__      			=						model(SCREAMING_SNAKE_CASE_	)
											self.parent.assertEqual(result.last_hidden_state.shape ,							(self.batch_size, self.seq_length, self.d_model)	)




							def 						__snake_case					(   self     :   Any ,							SCREAMING_SNAKE_CASE_     :   str ,							SCREAMING_SNAKE_CASE_     :   Optional[int] ,							SCREAMING_SNAKE_CASE_     :   Tuple ,							SCREAMING_SNAKE_CASE_     :   List[Any] ,							SCREAMING_SNAKE_CASE_     :   Union[str, Any] ,							SCREAMING_SNAKE_CASE_     :   Any ,							SCREAMING_SNAKE_CASE_     :   Optional[int] ,							):
											lowerCAmelCase__      			=						TFFunnelBaseModel(config=SCREAMING_SNAKE_CASE_	)
											lowerCAmelCase__      			=						{'''input_ids''': input_ids, '''attention_mask''': input_mask, '''token_type_ids''': token_type_ids}
											lowerCAmelCase__      			=						model(SCREAMING_SNAKE_CASE_	)

											lowerCAmelCase__      			=						[input_ids, input_mask]
											lowerCAmelCase__      			=						model(SCREAMING_SNAKE_CASE_	)

											lowerCAmelCase__      			=						model(SCREAMING_SNAKE_CASE_	)
											self.parent.assertEqual(result.last_hidden_state.shape ,							(self.batch_size, 2, self.d_model)	)

											lowerCAmelCase__      			=						False
											lowerCAmelCase__      			=						TFFunnelBaseModel(config=SCREAMING_SNAKE_CASE_	)
											lowerCAmelCase__      			=						model(SCREAMING_SNAKE_CASE_	)
											self.parent.assertEqual(result.last_hidden_state.shape ,							(self.batch_size, 3, self.d_model)	)

											lowerCAmelCase__      			=						False
											lowerCAmelCase__      			=						TFFunnelBaseModel(config=SCREAMING_SNAKE_CASE_	)
											lowerCAmelCase__      			=						model(SCREAMING_SNAKE_CASE_	)
											self.parent.assertEqual(result.last_hidden_state.shape ,							(self.batch_size, 2, self.d_model)	)




							def 						__snake_case					(   self     :   Union[str, Any] ,							SCREAMING_SNAKE_CASE_     :   Optional[int] ,							SCREAMING_SNAKE_CASE_     :   List[str] ,							SCREAMING_SNAKE_CASE_     :   Union[str, Any] ,							SCREAMING_SNAKE_CASE_     :   str ,							SCREAMING_SNAKE_CASE_     :   Optional[int] ,							SCREAMING_SNAKE_CASE_     :   Any ,							SCREAMING_SNAKE_CASE_     :   Any ,							):
											lowerCAmelCase__      			=						TFFunnelForPreTraining(config=SCREAMING_SNAKE_CASE_	)
											lowerCAmelCase__      			=						{'''input_ids''': input_ids, '''attention_mask''': input_mask, '''token_type_ids''': token_type_ids}
											lowerCAmelCase__      			=						model(SCREAMING_SNAKE_CASE_	)
											self.parent.assertEqual(result.logits.shape ,							(self.batch_size, self.seq_length)	)




							def 						__snake_case					(   self     :   Tuple ,							SCREAMING_SNAKE_CASE_     :   Tuple ,							SCREAMING_SNAKE_CASE_     :   Optional[Any] ,							SCREAMING_SNAKE_CASE_     :   Tuple ,							SCREAMING_SNAKE_CASE_     :   List[str] ,							SCREAMING_SNAKE_CASE_     :   Tuple ,							SCREAMING_SNAKE_CASE_     :   List[str] ,							SCREAMING_SNAKE_CASE_     :   int ,							):
											lowerCAmelCase__      			=						TFFunnelForMaskedLM(config=SCREAMING_SNAKE_CASE_	)
											lowerCAmelCase__      			=						{'''input_ids''': input_ids, '''attention_mask''': input_mask, '''token_type_ids''': token_type_ids}
											lowerCAmelCase__      			=						model(SCREAMING_SNAKE_CASE_	)
											self.parent.assertEqual(result.logits.shape ,							(self.batch_size, self.seq_length, self.vocab_size)	)




							def 						__snake_case					(   self     :   List[str] ,							SCREAMING_SNAKE_CASE_     :   Tuple ,							SCREAMING_SNAKE_CASE_     :   int ,							SCREAMING_SNAKE_CASE_     :   Any ,							SCREAMING_SNAKE_CASE_     :   Optional[int] ,							SCREAMING_SNAKE_CASE_     :   List[Any] ,							SCREAMING_SNAKE_CASE_     :   Optional[int] ,							SCREAMING_SNAKE_CASE_     :   Any ,							):
											lowerCAmelCase__      			=						self.num_labels
											lowerCAmelCase__      			=						TFFunnelForSequenceClassification(config=SCREAMING_SNAKE_CASE_	)
											lowerCAmelCase__      			=						{'''input_ids''': input_ids, '''attention_mask''': input_mask, '''token_type_ids''': token_type_ids}
											lowerCAmelCase__      			=						model(SCREAMING_SNAKE_CASE_	)
											self.parent.assertEqual(result.logits.shape ,							(self.batch_size, self.num_labels)	)




							def 						__snake_case					(   self     :   int ,							SCREAMING_SNAKE_CASE_     :   Any ,							SCREAMING_SNAKE_CASE_     :   Tuple ,							SCREAMING_SNAKE_CASE_     :   str ,							SCREAMING_SNAKE_CASE_     :   List[Any] ,							SCREAMING_SNAKE_CASE_     :   Any ,							SCREAMING_SNAKE_CASE_     :   Union[str, Any] ,							SCREAMING_SNAKE_CASE_     :   Tuple ,							):
											lowerCAmelCase__      			=						self.num_choices
											lowerCAmelCase__      			=						TFFunnelForMultipleChoice(config=SCREAMING_SNAKE_CASE_	)
											lowerCAmelCase__      			=						tf.tile(tf.expand_dims(SCREAMING_SNAKE_CASE_ ,							1	) ,							(1, self.num_choices, 1)	)
											lowerCAmelCase__      			=						tf.tile(tf.expand_dims(SCREAMING_SNAKE_CASE_ ,							1	) ,							(1, self.num_choices, 1)	)
											lowerCAmelCase__      			=						tf.tile(tf.expand_dims(SCREAMING_SNAKE_CASE_ ,							1	) ,							(1, self.num_choices, 1)	)
											lowerCAmelCase__      			=						{
											    '''input_ids''': multiple_choice_inputs_ids,
											    '''attention_mask''': multiple_choice_input_mask,
											    '''token_type_ids''': multiple_choice_token_type_ids,
											}
											lowerCAmelCase__      			=						model(SCREAMING_SNAKE_CASE_	)
											self.parent.assertEqual(result.logits.shape ,							(self.batch_size, self.num_choices)	)




							def 						__snake_case					(   self     :   Optional[Any] ,							SCREAMING_SNAKE_CASE_     :   List[Any] ,							SCREAMING_SNAKE_CASE_     :   Optional[Any] ,							SCREAMING_SNAKE_CASE_     :   List[str] ,							SCREAMING_SNAKE_CASE_     :   Tuple ,							SCREAMING_SNAKE_CASE_     :   Tuple ,							SCREAMING_SNAKE_CASE_     :   Tuple ,							SCREAMING_SNAKE_CASE_     :   Optional[int] ,							):
											lowerCAmelCase__      			=						self.num_labels
											lowerCAmelCase__      			=						TFFunnelForTokenClassification(config=SCREAMING_SNAKE_CASE_	)
											lowerCAmelCase__      			=						{'''input_ids''': input_ids, '''attention_mask''': input_mask, '''token_type_ids''': token_type_ids}
											lowerCAmelCase__      			=						model(SCREAMING_SNAKE_CASE_	)
											self.parent.assertEqual(result.logits.shape ,							(self.batch_size, self.seq_length, self.num_labels)	)




							def 						__snake_case					(   self     :   str ,							SCREAMING_SNAKE_CASE_     :   Union[str, Any] ,							SCREAMING_SNAKE_CASE_     :   str ,							SCREAMING_SNAKE_CASE_     :   List[str] ,							SCREAMING_SNAKE_CASE_     :   Optional[Any] ,							SCREAMING_SNAKE_CASE_     :   Any ,							SCREAMING_SNAKE_CASE_     :   Optional[Any] ,							SCREAMING_SNAKE_CASE_     :   Any ,							):
											lowerCAmelCase__      			=						TFFunnelForQuestionAnswering(config=SCREAMING_SNAKE_CASE_	)
											lowerCAmelCase__      			=						{'''input_ids''': input_ids, '''attention_mask''': input_mask, '''token_type_ids''': token_type_ids}
											lowerCAmelCase__      			=						model(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     :   List[str]	):
											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_tf
class  lowerCAmelCase_       (				snake_case__     ,    snake_case__     ,    unittest.TestCase					):
							UpperCamelCase_		:Dict		      =    (
							    (
							        TFFunnelModel,
							        TFFunnelForMaskedLM,
							        TFFunnelForPreTraining,
							        TFFunnelForQuestionAnswering,
							        TFFunnelForTokenClassification,
							    )
							    if is_tf_available()
							    else ()
							)
							UpperCamelCase_		:Dict		      =    (
							    {
							        'feature-extraction': (TFFunnelBaseModel, TFFunnelModel),
							        'fill-mask': TFFunnelForMaskedLM,
							        'question-answering': TFFunnelForQuestionAnswering,
							        'text-classification': TFFunnelForSequenceClassification,
							        'token-classification': TFFunnelForTokenClassification,
							        'zero-shot': TFFunnelForSequenceClassification,
							    }
							    if is_tf_available()
							    else {}
							)
							UpperCamelCase_		:Tuple		      =    False
							UpperCamelCase_		:Tuple		      =    False




							def 						__snake_case					(   self     :   str	):
											lowerCAmelCase__      			=						TFFunnelModelTester(self	)
											lowerCAmelCase__      			=						ConfigTester(self ,							config_class=SCREAMING_SNAKE_CASE_	)




							def 						__snake_case					(   self     :   Dict	):
											self.config_tester.run_common_tests()




							def 						__snake_case					(   self     :   Union[str, Any]	):
											lowerCAmelCase__      			=						self.model_tester.prepare_config_and_inputs()
											self.model_tester.create_and_check_model(*SCREAMING_SNAKE_CASE_	)




							def 						__snake_case					(   self     :   Union[str, Any]	):
											lowerCAmelCase__      			=						self.model_tester.prepare_config_and_inputs()
											self.model_tester.create_and_check_for_pretraining(*SCREAMING_SNAKE_CASE_	)




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




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




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



@require_tf
class  lowerCAmelCase_       (				snake_case__     ,    unittest.TestCase					):
							UpperCamelCase_		:Optional[Any]		      =    (
							    (TFFunnelBaseModel, TFFunnelForMultipleChoice, TFFunnelForSequenceClassification) if is_tf_available() else ()
							)
							UpperCamelCase_		:int		      =    False
							UpperCamelCase_		:Any		      =    False




							def 						__snake_case					(   self     :   List[str]	):
											lowerCAmelCase__      			=						TFFunnelModelTester(self ,							base=SCREAMING_SNAKE_CASE_	)
											lowerCAmelCase__      			=						ConfigTester(self ,							config_class=SCREAMING_SNAKE_CASE_	)




							def 						__snake_case					(   self     :   Tuple	):
											self.config_tester.run_common_tests()




							def 						__snake_case					(   self     :   Union[str, Any]	):
											lowerCAmelCase__      			=						self.model_tester.prepare_config_and_inputs()
											self.model_tester.create_and_check_base_model(*SCREAMING_SNAKE_CASE_	)




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




							def 						__snake_case					(   self     :   List[str]	):
											lowerCAmelCase__      			=						self.model_tester.prepare_config_and_inputs()
											self.model_tester.create_and_check_for_multiple_choice(*SCREAMING_SNAKE_CASE_	)





