



import pickle
import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


a__      :				Any   	=			get_tests_dir("fixtures/test_sentencepiece.model")



@require_sentencepiece
@require_tokenizers
class       UpperCAmelCase__(							lowerCamelCase     ,							unittest.TestCase	):

   '''simple docstring'''




   A    :  str       				=    XGLMTokenizer
   A    :  List[Any]       				=    XGLMTokenizerFast
   A    :  int       				=    True
   A    :  Optional[Any]       				=    True


   def 			UpperCAmelCase		(						self  :			Optional[int])	->				Optional[Any]:




         """simple docstring"""

         super().setUp()

         # We have a SentencePiece fixture for testing
         lowercase__     =  XGLMTokenizer(lowerCAmelCase			,				keep_accents=lowerCAmelCase)
         tokenizer.save_pretrained(self.tmpdirname)


   def 			UpperCAmelCase		(						self  :			Union[str, Any])	->				str:




         """simple docstring"""

         lowercase__     =  '<pad>'
         lowercase__     =  1

         self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowerCAmelCase)			,				lowerCAmelCase)
         self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowerCAmelCase)			,				lowerCAmelCase)


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




         """simple docstring"""

         lowercase__     =  list(self.get_tokenizer().get_vocab().keys())

         self.assertEqual(vocab_keys[0]			,				'<s>')
         self.assertEqual(vocab_keys[1]			,				'<pad>')
         self.assertEqual(len(lowerCAmelCase)			,				10_08)


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




         """simple docstring"""

         self.assertEqual(self.get_tokenizer().vocab_size			,				10_08)


   def 			UpperCAmelCase		(						self  :			Optional[Any])	->				List[str]:




         """simple docstring"""

         lowercase__     =  XGLMTokenizer(lowerCAmelCase			,				keep_accents=lowerCAmelCase)

         lowercase__     =  tokenizer.tokenize('This is a test')
         self.assertListEqual(lowerCAmelCase			,				['▁This', '▁is', '▁a', '▁t', 'est'])

         self.assertListEqual(
             tokenizer.convert_tokens_to_ids(lowerCAmelCase)			,				[value + tokenizer.fairseq_offset for value in [2_85, 46, 10, 1_70, 3_82]]			,				)

         lowercase__     =  tokenizer.tokenize('I was born in 92000, and this is falsé.')
         self.assertListEqual(
             lowerCAmelCase			,				[
                 SPIECE_UNDERLINE + 'I',
                 SPIECE_UNDERLINE + 'was',
                 SPIECE_UNDERLINE + 'b',
                 'or',
                 'n',
                 SPIECE_UNDERLINE + 'in',
                 SPIECE_UNDERLINE + '',
                 '9',
                 '2',
                 '0',
                 '0',
                 '0',
                 ',',
                 SPIECE_UNDERLINE + 'and',
                 SPIECE_UNDERLINE + 'this',
                 SPIECE_UNDERLINE + 'is',
                 SPIECE_UNDERLINE + 'f',
                 'al',
                 's',
                 'é',
                 '.',
             ]			,				)
         lowercase__     =  tokenizer.convert_tokens_to_ids(lowerCAmelCase)
         self.assertListEqual(
             lowerCAmelCase			,				[
                 value + tokenizer.fairseq_offset
                 for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
             ]			,				)

         lowercase__     =  tokenizer.convert_ids_to_tokens(lowerCAmelCase)
         self.assertListEqual(
             lowerCAmelCase			,				[
                 SPIECE_UNDERLINE + 'I',
                 SPIECE_UNDERLINE + 'was',
                 SPIECE_UNDERLINE + 'b',
                 'or',
                 'n',
                 SPIECE_UNDERLINE + 'in',
                 SPIECE_UNDERLINE + '',
                 '<unk>',
                 '2',
                 '0',
                 '0',
                 '0',
                 ',',
                 SPIECE_UNDERLINE + 'and',
                 SPIECE_UNDERLINE + 'this',
                 SPIECE_UNDERLINE + 'is',
                 SPIECE_UNDERLINE + 'f',
                 'al',
                 's',
                 '<unk>',
                 '.',
             ]			,				)


   @cached_property
   def 			UpperCAmelCase		(						self  :			int)	->				Dict:




         """simple docstring"""

         return XGLMTokenizer.from_pretrained('facebook/xglm-564M')


   def 			UpperCAmelCase		(						self  :			Optional[int])	->				Dict:




         """simple docstring"""

         with tempfile.NamedTemporaryFile() as f:
               shutil.copyfile(lowerCAmelCase			,				f.name)
               lowercase__     =  XGLMTokenizer(f.name			,				keep_accents=lowerCAmelCase)
               lowercase__     =  pickle.dumps(lowerCAmelCase)
         pickle.loads(lowerCAmelCase)


   def 			UpperCAmelCase		(						self  :			Optional[Any])	->				str:




         """simple docstring"""

         if not self.test_rust_tokenizer:
               return

         lowercase__     =  self.get_tokenizer()
         lowercase__     =  self.get_rust_tokenizer()

         lowercase__     =  'I was born in 92000, and this is falsé.'

         lowercase__     =  tokenizer.tokenize(lowerCAmelCase)
         lowercase__     =  rust_tokenizer.tokenize(lowerCAmelCase)
         self.assertListEqual(lowerCAmelCase			,				lowerCAmelCase)

         lowercase__     =  tokenizer.encode(lowerCAmelCase			,				add_special_tokens=lowerCAmelCase)
         lowercase__     =  rust_tokenizer.encode(lowerCAmelCase			,				add_special_tokens=lowerCAmelCase)
         self.assertListEqual(lowerCAmelCase			,				lowerCAmelCase)

         lowercase__     =  self.get_rust_tokenizer()
         lowercase__     =  tokenizer.encode(lowerCAmelCase)
         lowercase__     =  rust_tokenizer.encode(lowerCAmelCase)
         self.assertListEqual(lowerCAmelCase			,				lowerCAmelCase)


   @slow
   def 			UpperCAmelCase		(						self  :			List[str])	->				List[str]:




         """simple docstring"""

         lowercase__     =  'Hello World!'
         lowercase__     =  [2, 3_12_27, 44_47, 35]

         self.assertListEqual(lowerCAmelCase			,				self.big_tokenizer.encode(lowerCAmelCase))


   @slow
   def 			UpperCAmelCase		(						self  :			List[str])	->				Union[str, Any]:




         """simple docstring"""

         lowercase__     =  (
             'This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) " [ ] ! : - . Also we will'
             ' add words that should not exsist and be tokenized to unk, such as saoneuhaoesuth'
         )
         # fmt: off
         lowercase__     =  [2, 10_18, 67, 11, 19_88, 26_17, 56_31, 2_78, 11, 34_07, 48, 7_16_30, 2_80_85, 4, 32_34, 1_57, 13, 6, 5, 6, 4, 35_26, 7_68, 15, 6_59, 57, 2_98, 39_83, 8_64, 1_29, 21, 6, 5, 1_36_75, 3_77, 6_52, 75_80, 1_03_41, 1_55, 28_17, 4_22, 16_66, 7, 16_74, 53, 1_13, 20_22_77, 1_78_92, 33, 60, 87, 4, 32_34, 1_57, 61, 26_67, 5_23_76, 19, 88, 23, 7_35]
         # fmt: on

         self.assertListEqual(lowerCAmelCase			,				self.big_tokenizer.encode(lowerCAmelCase))



   @slow
   def 			UpperCAmelCase		(						self  :			str)	->				Dict:




         """simple docstring"""

         lowercase__     =  {
             'input_ids': [[2, 10_88_25, 11_63, 15, 8_80_10, 4_73, 1_58_98, 1_57, 1_36_72, 18_57, 3_12, 8, 23_80_21, 11_63, 53, 1_36_72, 18_57, 3_12, 8, 5_32_83, 18_23_96, 8, 1_85_66, 16, 3_67_33, 41_01, 8, 2_30, 24_40_17, 12_25_53, 7, 15, 13_25_97, 4, 2_93, 1_25_11, 76_10, 4, 34_14, 13_25_97, 9, 4, 3_23_61, 3_62, 4, 7_34, 2_85_12, 3_25_69, 18, 4, 3_23_61, 2_60_96, 1_49_82, 73, 1_87_15, 2_14_33, 23_52_61, 15, 4_92, 1_24_27, 16, 53, 1_87_15, 2_14_33, 6_54_54, 15, 2_36_59, 5_63, 16, 2_78, 5_97, 28_43, 5_95, 79_31, 18_23_96, 6_41_86, 22, 8_86, 5_95, 13_29_81, 53, 2_55_40, 34_49, 4_39_82, 3_99_01, 59_51, 8_78, 3_30, 4, 2_76_94, 8_02_69, 3_12, 53, 65_17, 1_17_80, 6_11, 2_04_08, 5], [2, 6, 13_25_97, 67, 4_28_97, 33, 5_92, 8, 16_37_29, 2_55_40, 3_61, 13_69_97, 10_95_14, 17_32_30, 7, 5_01, 60, 10_29_13, 1_96, 56_31, 2_35, 6_32_43, 4_73, 6, 23_17_57, 74, 52_77, 79_05, 53, 30_95, 3_73_17, 22, 4_54, 18_38_74, 5], [2, 2_68, 3_12_98, 4_65_30, 6, 13_29_35, 4_38_31, 7, 5_97, 32, 24, 36_88, 98_65, 5]],
             'attention_mask': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]
         }  # noqa: E501
         # fmt: on

         self.tokenizer_integration_test_util(
             expected_encoding=lowerCAmelCase			,				model_name='facebook/xglm-564M'			,				padding=lowerCAmelCase			,				)





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       UpperCAmelCase__:

   '''simple docstring'''




   def __init__(						self  :			Tuple			,				lowerCAmelCase  :			str			,				lowerCAmelCase  :			Dict=13			,				lowerCAmelCase  :			Dict=7			,				lowerCAmelCase  :			int=True			,				lowerCAmelCase  :			Optional[Any]=True			,				lowerCAmelCase  :			str=True			,				lowerCAmelCase  :			int=True			,				lowerCAmelCase  :			List[Any]=99			,				lowerCAmelCase  :			List[Any]=[1, 1, 2]			,				lowerCAmelCase  :			Optional[Any]=1			,				lowerCAmelCase  :			int=32			,				lowerCAmelCase  :			Union[str, Any]=4			,				lowerCAmelCase  :			Tuple=8			,				lowerCAmelCase  :			int=37			,				lowerCAmelCase  :			Any="gelu_new"			,				lowerCAmelCase  :			str=0.1			,				lowerCAmelCase  :			List[str]=0.1			,				lowerCAmelCase  :			Dict=0.0			,				lowerCAmelCase  :			str=5_12			,				lowerCAmelCase  :			str=3			,				lowerCAmelCase  :			List[Any]=0.02			,				lowerCAmelCase  :			Union[str, Any]=3			,				lowerCAmelCase  :			Any=4			,				lowerCAmelCase  :			List[Any]=None			,				lowerCAmelCase  :			Optional[int]=False			,				)	->				List[Any]:




         """simple docstring"""

         lowercase__     =  parent
         lowercase__     =  batch_size
         lowercase__     =  seq_length
         lowercase__     =  is_training
         lowercase__     =  use_input_mask
         lowercase__     =  use_token_type_ids
         lowercase__     =  use_labels
         lowercase__     =  vocab_size
         lowercase__     =  block_sizes
         lowercase__     =  num_decoder_layers
         lowercase__     =  d_model
         lowercase__     =  n_head
         lowercase__     =  d_head
         lowercase__     =  d_inner
         lowercase__     =  hidden_act
         lowercase__     =  hidden_dropout
         lowercase__     =  attention_dropout
         lowercase__     =  activation_dropout
         lowercase__     =  max_position_embeddings
         lowercase__     =  type_vocab_size
         lowercase__     =  2
         lowercase__     =  num_labels
         lowercase__     =  num_choices
         lowercase__     =  scope
         lowercase__     =  initializer_std

         # Used in the tests to check the size of the first attention layer
         lowercase__     =  n_head
         # Used in the tests to check the size of the first hidden state
         lowercase__     =  self.d_model
         # Used in the tests to check the number of output hidden states/attentions
         lowercase__     =  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:
               lowercase__     =  self.num_hidden_layers + 2


   def 			UpperCAmelCase		(						self  :			Union[str, Any])	->				str:




         """simple docstring"""

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

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

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

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

         lowercase__     =  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 			UpperCAmelCase		(						self  :			Dict			,				lowerCAmelCase  :			List[Any]			,				lowerCAmelCase  :			Dict			,				lowerCAmelCase  :			Tuple			,				lowerCAmelCase  :			Union[str, Any]			,				lowerCAmelCase  :			Any			,				lowerCAmelCase  :			Optional[Any]			,				lowerCAmelCase  :			Union[str, Any]			,				)	->				int:




         """simple docstring"""

         lowercase__     =  TFFunnelModel(config=lowerCAmelCase)
         lowercase__     =  {'input_ids': input_ids, 'attention_mask': input_mask, 'token_type_ids': token_type_ids}
         lowercase__     =  model(lowerCAmelCase)

         lowercase__     =  [input_ids, input_mask]
         lowercase__     =  model(lowerCAmelCase)

         lowercase__     =  model(lowerCAmelCase)
         self.parent.assertEqual(result.last_hidden_state.shape			,				(self.batch_size, self.seq_length, self.d_model))

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

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


   def 			UpperCAmelCase		(						self  :			List[str]			,				lowerCAmelCase  :			List[Any]			,				lowerCAmelCase  :			Tuple			,				lowerCAmelCase  :			Optional[int]			,				lowerCAmelCase  :			Any			,				lowerCAmelCase  :			List[str]			,				lowerCAmelCase  :			int			,				lowerCAmelCase  :			Optional[Any]			,				)	->				Optional[Any]:




         """simple docstring"""

         lowercase__     =  TFFunnelBaseModel(config=lowerCAmelCase)
         lowercase__     =  {'input_ids': input_ids, 'attention_mask': input_mask, 'token_type_ids': token_type_ids}
         lowercase__     =  model(lowerCAmelCase)

         lowercase__     =  [input_ids, input_mask]
         lowercase__     =  model(lowerCAmelCase)

         lowercase__     =  model(lowerCAmelCase)
         self.parent.assertEqual(result.last_hidden_state.shape			,				(self.batch_size, 2, self.d_model))

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

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


   def 			UpperCAmelCase		(						self  :			Tuple			,				lowerCAmelCase  :			Optional[int]			,				lowerCAmelCase  :			Optional[Any]			,				lowerCAmelCase  :			Dict			,				lowerCAmelCase  :			List[str]			,				lowerCAmelCase  :			List[str]			,				lowerCAmelCase  :			str			,				lowerCAmelCase  :			Tuple			,				)	->				str:




         """simple docstring"""

         lowercase__     =  TFFunnelForPreTraining(config=lowerCAmelCase)
         lowercase__     =  {'input_ids': input_ids, 'attention_mask': input_mask, 'token_type_ids': token_type_ids}
         lowercase__     =  model(lowerCAmelCase)
         self.parent.assertEqual(result.logits.shape			,				(self.batch_size, self.seq_length))


   def 			UpperCAmelCase		(						self  :			List[Any]			,				lowerCAmelCase  :			Any			,				lowerCAmelCase  :			str			,				lowerCAmelCase  :			Union[str, Any]			,				lowerCAmelCase  :			List[str]			,				lowerCAmelCase  :			Optional[Any]			,				lowerCAmelCase  :			Tuple			,				lowerCAmelCase  :			Tuple			,				)	->				Optional[int]:




         """simple docstring"""

         lowercase__     =  TFFunnelForMaskedLM(config=lowerCAmelCase)
         lowercase__     =  {'input_ids': input_ids, 'attention_mask': input_mask, 'token_type_ids': token_type_ids}
         lowercase__     =  model(lowerCAmelCase)
         self.parent.assertEqual(result.logits.shape			,				(self.batch_size, self.seq_length, self.vocab_size))


   def 			UpperCAmelCase		(						self  :			Union[str, Any]			,				lowerCAmelCase  :			int			,				lowerCAmelCase  :			Tuple			,				lowerCAmelCase  :			Union[str, Any]			,				lowerCAmelCase  :			Optional[int]			,				lowerCAmelCase  :			Dict			,				lowerCAmelCase  :			Optional[int]			,				lowerCAmelCase  :			List[Any]			,				)	->				Optional[int]:




         """simple docstring"""

         lowercase__     =  self.num_labels
         lowercase__     =  TFFunnelForSequenceClassification(config=lowerCAmelCase)
         lowercase__     =  {'input_ids': input_ids, 'attention_mask': input_mask, 'token_type_ids': token_type_ids}
         lowercase__     =  model(lowerCAmelCase)
         self.parent.assertEqual(result.logits.shape			,				(self.batch_size, self.num_labels))


   def 			UpperCAmelCase		(						self  :			List[Any]			,				lowerCAmelCase  :			str			,				lowerCAmelCase  :			Optional[int]			,				lowerCAmelCase  :			int			,				lowerCAmelCase  :			Optional[int]			,				lowerCAmelCase  :			List[str]			,				lowerCAmelCase  :			Union[str, Any]			,				lowerCAmelCase  :			List[Any]			,				)	->				Optional[Any]:




         """simple docstring"""

         lowercase__     =  self.num_choices
         lowercase__     =  TFFunnelForMultipleChoice(config=lowerCAmelCase)
         lowercase__     =  tf.tile(tf.expand_dims(lowerCAmelCase			,				1)			,				(1, self.num_choices, 1))
         lowercase__     =  tf.tile(tf.expand_dims(lowerCAmelCase			,				1)			,				(1, self.num_choices, 1))
         lowercase__     =  tf.tile(tf.expand_dims(lowerCAmelCase			,				1)			,				(1, self.num_choices, 1))
         lowercase__     =  {
             'input_ids': multiple_choice_inputs_ids,
             'attention_mask': multiple_choice_input_mask,
             'token_type_ids': multiple_choice_token_type_ids,
         }
         lowercase__     =  model(lowerCAmelCase)
         self.parent.assertEqual(result.logits.shape			,				(self.batch_size, self.num_choices))


   def 			UpperCAmelCase		(						self  :			List[str]			,				lowerCAmelCase  :			str			,				lowerCAmelCase  :			List[Any]			,				lowerCAmelCase  :			Tuple			,				lowerCAmelCase  :			Union[str, Any]			,				lowerCAmelCase  :			int			,				lowerCAmelCase  :			Optional[int]			,				lowerCAmelCase  :			Any			,				)	->				Union[str, Any]:




         """simple docstring"""

         lowercase__     =  self.num_labels
         lowercase__     =  TFFunnelForTokenClassification(config=lowerCAmelCase)
         lowercase__     =  {'input_ids': input_ids, 'attention_mask': input_mask, 'token_type_ids': token_type_ids}
         lowercase__     =  model(lowerCAmelCase)
         self.parent.assertEqual(result.logits.shape			,				(self.batch_size, self.seq_length, self.num_labels))


   def 			UpperCAmelCase		(						self  :			int			,				lowerCAmelCase  :			List[str]			,				lowerCAmelCase  :			int			,				lowerCAmelCase  :			Optional[int]			,				lowerCAmelCase  :			List[str]			,				lowerCAmelCase  :			str			,				lowerCAmelCase  :			Tuple			,				lowerCAmelCase  :			Tuple			,				)	->				Optional[int]:




         """simple docstring"""

         lowercase__     =  TFFunnelForQuestionAnswering(config=lowerCAmelCase)
         lowercase__     =  {'input_ids': input_ids, 'attention_mask': input_mask, 'token_type_ids': token_type_ids}
         lowercase__     =  model(lowerCAmelCase)
         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  :			Union[str, Any])	->				str:




         """simple docstring"""

         lowercase__     =  self.prepare_config_and_inputs()
         (
             (
             lowercase__
         ),	(
             lowercase__
         ),	(
             lowercase__
         ),	(
             lowercase__
         ),	(
             lowercase__
         ),	(
             lowercase__
         ),	(
             lowercase__
         ),	
         )     =  config_and_inputs
         lowercase__     =  {'input_ids': input_ids, 'token_type_ids': token_type_ids, 'attention_mask': input_mask}
         return config, inputs_dict



@require_tf
class       UpperCAmelCase__(							lowerCamelCase     ,							lowerCamelCase     ,							unittest.TestCase	):

   '''simple docstring'''




   A    :  int       				=    (
       (
           TFFunnelModel,
           TFFunnelForMaskedLM,
           TFFunnelForPreTraining,
           TFFunnelForQuestionAnswering,
           TFFunnelForTokenClassification,
       )
       if is_tf_available()
       else ()
   )
   A    :  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 {}
   )
   A    :  Optional[int]       				=    False
   A    :  Optional[int]       				=    False


   def 			UpperCAmelCase		(						self  :			Tuple)	->				str:




         """simple docstring"""

         lowercase__     =  TFFunnelModelTester(self)
         lowercase__     =  ConfigTester(self			,				config_class=lowerCAmelCase)


   def 			UpperCAmelCase		(						self  :			int)	->				Optional[int]:




         """simple docstring"""

         self.config_tester.run_common_tests()


   def 			UpperCAmelCase		(						self  :			Union[str, Any])	->				Union[str, Any]:




         """simple docstring"""

         lowercase__     =  self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_model(*lowerCAmelCase)


   def 			UpperCAmelCase		(						self  :			Union[str, Any])	->				Union[str, Any]:




         """simple docstring"""

         lowercase__     =  self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_for_pretraining(*lowerCAmelCase)


   def 			UpperCAmelCase		(						self  :			int)	->				Union[str, Any]:




         """simple docstring"""

         lowercase__     =  self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_for_masked_lm(*lowerCAmelCase)


   def 			UpperCAmelCase		(						self  :			List[str])	->				Union[str, Any]:




         """simple docstring"""

         lowercase__     =  self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_for_token_classification(*lowerCAmelCase)



   def 			UpperCAmelCase		(						self  :			Dict)	->				Dict:




         """simple docstring"""

         lowercase__     =  self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_for_question_answering(*lowerCAmelCase)



@require_tf
class       UpperCAmelCase__(							lowerCamelCase     ,							unittest.TestCase	):

   '''simple docstring'''




   A    :  Tuple       				=    (
       (TFFunnelBaseModel, TFFunnelForMultipleChoice, TFFunnelForSequenceClassification) if is_tf_available() else ()
   )
   A    :  List[str]       				=    False
   A    :  int       				=    False


   def 			UpperCAmelCase		(						self  :			Any)	->				List[Any]:




         """simple docstring"""

         lowercase__     =  TFFunnelModelTester(self			,				base=lowerCAmelCase)
         lowercase__     =  ConfigTester(self			,				config_class=lowerCAmelCase)


   def 			UpperCAmelCase		(						self  :			Union[str, Any])	->				Optional[int]:




         """simple docstring"""

         self.config_tester.run_common_tests()


   def 			UpperCAmelCase		(						self  :			Tuple)	->				int:




         """simple docstring"""

         lowercase__     =  self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_base_model(*lowerCAmelCase)


   def 			UpperCAmelCase		(						self  :			int)	->				str:




         """simple docstring"""

         lowercase__     =  self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_for_sequence_classification(*lowerCAmelCase)



   def 			UpperCAmelCase		(						self  :			List[str])	->				Optional[Any]:




         """simple docstring"""

         lowercase__     =  self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_for_multiple_choice(*lowerCAmelCase)
