
import json
import os
import re
import unittest

from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin





@require_tokenizers
class    __A(					UpperCAmelCase  ,		unittest.TestCase							):
					SCREAMING_SNAKE_CASE           =     CodeGenTokenizer
					SCREAMING_SNAKE_CASE           =     CodeGenTokenizerFast
					SCREAMING_SNAKE_CASE           =     True
					SCREAMING_SNAKE_CASE           =     {'''add_prefix_space''': True}
					SCREAMING_SNAKE_CASE           =     False

					def  lowercase__   (						self       :  Tuple ):
												super().setUp()

												# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
												lowerCamelCase_					=       [
												    """l""",
												    """o""",
												    """w""",
												    """e""",
												    """r""",
												    """s""",
												    """t""",
												    """i""",
												    """d""",
												    """n""",
												    """\u0120""",
												    """\u0120l""",
												    """\u0120n""",
												    """\u0120lo""",
												    """\u0120low""",
												    """er""",
												    """\u0120lowest""",
												    """\u0120newer""",
												    """\u0120wider""",
												    """<unk>""",
												    """<|endoftext|>""",
												]
												lowerCamelCase_					=       dict(zip(__UpperCamelCase ,       range(len(__UpperCamelCase ) ) ) )
												lowerCamelCase_					=       ["""#version: 0.2""", """\u0120 l""", """\u0120l o""", """\u0120lo w""", """e r""", """"""]
												lowerCamelCase_					=       {"""unk_token""": """<unk>"""}

												lowerCamelCase_					=       os.path.join(self.tmpdirname ,       VOCAB_FILES_NAMES["""vocab_file"""] )
												lowerCamelCase_					=       os.path.join(self.tmpdirname ,       VOCAB_FILES_NAMES["""merges_file"""] )
												with open(self.vocab_file ,       """w""" ,       encoding="""utf-8""" ) as fp:
																			fp.write(json.dumps(__UpperCamelCase ) + """\n""" )
												with open(self.merges_file ,       """w""" ,       encoding="""utf-8""" ) as fp:
																			fp.write("""\n""".join(__UpperCamelCase ) )

					def  lowercase__   (						self       :  List[Any] ,       **__UpperCamelCase       :  Dict ):
												kwargs.update(self.special_tokens_map )
												return CodeGenTokenizer.from_pretrained(self.tmpdirname ,       **__UpperCamelCase )

					def  lowercase__   (						self       :  Dict ,       **__UpperCamelCase       :  List[str] ):
												kwargs.update(self.special_tokens_map )
												return CodeGenTokenizerFast.from_pretrained(self.tmpdirname ,       **__UpperCamelCase )

					def  lowercase__   (						self       :  Any ,       __UpperCamelCase       :  Any ):
												lowerCamelCase_					=       """lower newer"""
												lowerCamelCase_					=       """lower newer"""
												return input_text, output_text

					def  lowercase__   (						self       :  str ):
												lowerCamelCase_					=       CodeGenTokenizer(self.vocab_file ,       self.merges_file ,       **self.special_tokens_map )
												lowerCamelCase_					=       """lower newer"""
												lowerCamelCase_					=       ["""\u0120low""", """er""", """\u0120""", """n""", """e""", """w""", """er"""]
												lowerCamelCase_					=       tokenizer.tokenize(__UpperCamelCase ,       add_prefix_space=__UpperCamelCase )
												self.assertListEqual(__UpperCamelCase ,       __UpperCamelCase )

												lowerCamelCase_					=       tokens + [tokenizer.unk_token]
												lowerCamelCase_					=       [1_4, 1_5, 1_0, 9, 3, 2, 1_5, 1_9]
												self.assertListEqual(tokenizer.convert_tokens_to_ids(__UpperCamelCase ) ,       __UpperCamelCase )

					def  lowercase__   (						self       :  List[str] ):
												if not self.test_rust_tokenizer:
																			return

												lowerCamelCase_					=       self.get_tokenizer()
												lowerCamelCase_					=       self.get_rust_tokenizer(add_prefix_space=__UpperCamelCase )

												lowerCamelCase_					=       """lower newer"""

												# Testing tokenization
												lowerCamelCase_					=       tokenizer.tokenize(__UpperCamelCase ,       add_prefix_space=__UpperCamelCase )
												lowerCamelCase_					=       rust_tokenizer.tokenize(__UpperCamelCase )
												self.assertListEqual(__UpperCamelCase ,       __UpperCamelCase )

												# Testing conversion to ids without special tokens
												lowerCamelCase_					=       tokenizer.encode(__UpperCamelCase ,       add_special_tokens=__UpperCamelCase ,       add_prefix_space=__UpperCamelCase )
												lowerCamelCase_					=       rust_tokenizer.encode(__UpperCamelCase ,       add_special_tokens=__UpperCamelCase )
												self.assertListEqual(__UpperCamelCase ,       __UpperCamelCase )

												# Testing conversion to ids with special tokens
												lowerCamelCase_					=       self.get_rust_tokenizer(add_prefix_space=__UpperCamelCase )
												lowerCamelCase_					=       tokenizer.encode(__UpperCamelCase ,       add_prefix_space=__UpperCamelCase )
												lowerCamelCase_					=       rust_tokenizer.encode(__UpperCamelCase )
												self.assertListEqual(__UpperCamelCase ,       __UpperCamelCase )

												# Testing the unknown token
												lowerCamelCase_					=       tokens + [rust_tokenizer.unk_token]
												lowerCamelCase_					=       [1_4, 1_5, 1_0, 9, 3, 2, 1_5, 1_9]
												self.assertListEqual(rust_tokenizer.convert_tokens_to_ids(__UpperCamelCase ) ,       __UpperCamelCase )

					def  lowercase__   (						self       :  Optional[Any] ,       *__UpperCamelCase       :  Tuple ,       **__UpperCamelCase       :  List[Any] ):
												# It's very difficult to mix/test pretokenization with byte-level
												# And get both CodeGen and Roberta to work at the same time (mostly an issue of adding a space before the string)
												pass

					def  lowercase__   (						self       :  List[str] ,       __UpperCamelCase       :  Optional[Any]=1_5 ):
												for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																			with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})''' ):
																										lowerCamelCase_					=       self.rust_tokenizer_class.from_pretrained(__UpperCamelCase ,       **__UpperCamelCase )

																										# Simple input
																										lowerCamelCase_					=       """This is a simple input"""
																										lowerCamelCase_					=       ["""This is a simple input 1""", """This is a simple input 2"""]
																										lowerCamelCase_					=       ("""This is a simple input""", """This is a pair""")
																										lowerCamelCase_					=       [
																										    ("""This is a simple input 1""", """This is a simple input 2"""),
																										    ("""This is a simple pair 1""", """This is a simple pair 2"""),
																										]

																										# Simple input tests
																										self.assertRaises(__UpperCamelCase ,       tokenizer_r.encode ,       __UpperCamelCase ,       max_length=__UpperCamelCase ,       padding="""max_length""" )

																										# Simple input
																										self.assertRaises(__UpperCamelCase ,       tokenizer_r.encode_plus ,       __UpperCamelCase ,       max_length=__UpperCamelCase ,       padding="""max_length""" )

																										# Simple input
																										self.assertRaises(
																										    __UpperCamelCase ,       tokenizer_r.batch_encode_plus ,       __UpperCamelCase ,       max_length=__UpperCamelCase ,       padding="""max_length""" ,       )

																										# Pair input
																										self.assertRaises(__UpperCamelCase ,       tokenizer_r.encode ,       __UpperCamelCase ,       max_length=__UpperCamelCase ,       padding="""max_length""" )

																										# Pair input
																										self.assertRaises(__UpperCamelCase ,       tokenizer_r.encode_plus ,       __UpperCamelCase ,       max_length=__UpperCamelCase ,       padding="""max_length""" )

																										# Pair input
																										self.assertRaises(
																										    __UpperCamelCase ,       tokenizer_r.batch_encode_plus ,       __UpperCamelCase ,       max_length=__UpperCamelCase ,       padding="""max_length""" ,       )

					def  lowercase__   (						self       :  Any ):
												lowerCamelCase_					=       CodeGenTokenizer.from_pretrained(self.tmpdirname ,       pad_token="""<pad>""" )

												# Simple input
												lowerCamelCase_					=       """This is a simple input"""
												lowerCamelCase_					=       ["""This is a simple input looooooooong""", """This is a simple input"""]
												lowerCamelCase_					=       ("""This is a simple input""", """This is a pair""")
												lowerCamelCase_					=       [
												    ("""This is a simple input loooooong""", """This is a simple input"""),
												    ("""This is a simple pair loooooong""", """This is a simple pair"""),
												]

												lowerCamelCase_					=       tokenizer.pad_token_id

												lowerCamelCase_					=       tokenizer(__UpperCamelCase ,       padding="""max_length""" ,       max_length=3_0 ,       return_tensors="""np""" )
												lowerCamelCase_					=       tokenizer(__UpperCamelCase ,       padding=__UpperCamelCase ,       truncate=__UpperCamelCase ,       return_tensors="""np""" )
												lowerCamelCase_					=       tokenizer(*__UpperCamelCase ,       padding="""max_length""" ,       max_length=6_0 ,       return_tensors="""np""" )
												lowerCamelCase_					=       tokenizer(__UpperCamelCase ,       padding=__UpperCamelCase ,       truncate=__UpperCamelCase ,       return_tensors="""np""" )

												# s
												# test single string max_length padding
												self.assertEqual(out_s["""input_ids"""].shape[-1] ,       3_0 )
												self.assertTrue(pad_token_id in out_s["""input_ids"""] )
												self.assertTrue(0 in out_s["""attention_mask"""] )

												# s2
												# test automatic padding
												self.assertEqual(out_sa["""input_ids"""].shape[-1] ,       3_3 )
												# long slice doesn't have padding
												self.assertFalse(pad_token_id in out_sa["""input_ids"""][0] )
												self.assertFalse(0 in out_sa["""attention_mask"""][0] )
												# short slice does have padding
												self.assertTrue(pad_token_id in out_sa["""input_ids"""][1] )
												self.assertTrue(0 in out_sa["""attention_mask"""][1] )

												# p
												# test single pair max_length padding
												self.assertEqual(out_p["""input_ids"""].shape[-1] ,       6_0 )
												self.assertTrue(pad_token_id in out_p["""input_ids"""] )
												self.assertTrue(0 in out_p["""attention_mask"""] )

												# p2
												# test automatic padding pair
												self.assertEqual(out_pa["""input_ids"""].shape[-1] ,       5_2 )
												# long slice pair doesn't have padding
												self.assertFalse(pad_token_id in out_pa["""input_ids"""][0] )
												self.assertFalse(0 in out_pa["""attention_mask"""][0] )
												# short slice pair does have padding
												self.assertTrue(pad_token_id in out_pa["""input_ids"""][1] )
												self.assertTrue(0 in out_pa["""attention_mask"""][1] )

					def  lowercase__   (						self       :  Optional[Any] ):
												lowerCamelCase_					=       """$$$"""
												lowerCamelCase_					=       CodeGenTokenizer.from_pretrained(self.tmpdirname ,       bos_token=__UpperCamelCase ,       add_bos_token=__UpperCamelCase )

												lowerCamelCase_					=       """This is a simple input"""
												lowerCamelCase_					=       ["""This is a simple input 1""", """This is a simple input 2"""]

												lowerCamelCase_					=       tokenizer.bos_token_id

												lowerCamelCase_					=       tokenizer(__UpperCamelCase )
												lowerCamelCase_					=       tokenizer(__UpperCamelCase )

												self.assertEqual(out_s.input_ids[0] ,       __UpperCamelCase )
												self.assertTrue(all(o[0] == bos_token_id for o in out_sa.input_ids ) )

												lowerCamelCase_					=       tokenizer.decode(out_s.input_ids )
												lowerCamelCase_					=       tokenizer.batch_decode(out_sa.input_ids )

												self.assertEqual(decode_s.split()[0] ,       __UpperCamelCase )
												self.assertTrue(all(d.split()[0] == bos_token for d in decode_sa ) )

					@slow
					def  lowercase__   (						self       :  Dict ):
												lowerCamelCase_					=       CodeGenTokenizer.from_pretrained("""Salesforce/codegen-350M-mono""" )

												lowerCamelCase_					=       """\nif len_a > len_b:\n    result = a\nelse:\n    result = b\n\n\n\n#"""
												lowerCamelCase_					=       """\nif len_a > len_b:      result = a\nelse:      result = b"""

												lowerCamelCase_					=       tokenizer.encode(__UpperCamelCase )
												lowerCamelCase_					=       ["""^#""", re.escape("""<|endoftext|>""" ), """^'''""", """^\"\"\"""", """\n\n\n"""]
												lowerCamelCase_					=       tokenizer.decode(__UpperCamelCase ,       truncate_before_pattern=__UpperCamelCase )
												self.assertEqual(__UpperCamelCase ,       __UpperCamelCase )



					def  lowercase__   (						self       :  Any ):
												pass







from __future__ import annotations

import unittest

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

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


if is_tf_available():
		import tensorflow as tf

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





class    __A:

					def __init__(						self       :  List[Any] ,       __UpperCamelCase       :  Tuple ,       __UpperCamelCase       :  Any=1_3 ,       __UpperCamelCase       :  Optional[int]=7 ,       __UpperCamelCase       :  Any=True ,       __UpperCamelCase       :  Dict=True ,       __UpperCamelCase       :  Optional[Any]=True ,       __UpperCamelCase       :  Dict=True ,       __UpperCamelCase       :  Union[str, Any]=9_9 ,       __UpperCamelCase       :  List[str]=3_2 ,       __UpperCamelCase       :  int=2 ,       __UpperCamelCase       :  Optional[Any]=4 ,       __UpperCamelCase       :  Optional[int]=3_7 ,       __UpperCamelCase       :  Optional[Any]="gelu" ,       __UpperCamelCase       :  int=0.1 ,       __UpperCamelCase       :  str=0.1 ,       __UpperCamelCase       :  Tuple=5_1_2 ,       __UpperCamelCase       :  Any=1_6 ,       __UpperCamelCase       :  Dict=2 ,       __UpperCamelCase       :  Optional[Any]=0.02 ,       __UpperCamelCase       :  Optional[Any]=False ,       __UpperCamelCase       :  Dict=True ,       __UpperCamelCase       :  Any="None" ,       __UpperCamelCase       :  List[Any]=3 ,       __UpperCamelCase       :  Optional[int]=4 ,       __UpperCamelCase       :  Dict=None ,       ):
												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_					=       hidden_size
												lowerCamelCase_					=       num_hidden_layers
												lowerCamelCase_					=       num_attention_heads
												lowerCamelCase_					=       intermediate_size
												lowerCamelCase_					=       hidden_act
												lowerCamelCase_					=       hidden_dropout_prob
												lowerCamelCase_					=       attention_probs_dropout_prob
												lowerCamelCase_					=       max_position_embeddings
												lowerCamelCase_					=       type_vocab_size
												lowerCamelCase_					=       type_sequence_label_size
												lowerCamelCase_					=       initializer_range
												lowerCamelCase_					=       num_labels
												lowerCamelCase_					=       num_choices
												lowerCamelCase_					=       relative_attention
												lowerCamelCase_					=       position_biased_input
												lowerCamelCase_					=       pos_att_type
												lowerCamelCase_					=       scope

					def  lowercase__   (						self       :  Optional[Any] ):
												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_					=       DebertaVaConfig(
												    vocab_size=self.vocab_size ,       hidden_size=self.hidden_size ,       num_hidden_layers=self.num_hidden_layers ,       num_attention_heads=self.num_attention_heads ,       intermediate_size=self.intermediate_size ,       hidden_act=self.hidden_act ,       hidden_dropout_prob=self.hidden_dropout_prob ,       attention_probs_dropout_prob=self.attention_probs_dropout_prob ,       max_position_embeddings=self.max_position_embeddings ,       type_vocab_size=self.type_vocab_size ,       relative_attention=self.relative_attention ,       position_biased_input=self.position_biased_input ,       initializer_range=self.initializer_range ,       return_dict=__UpperCamelCase ,       )

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

					def  lowercase__   (						self       :  str ,       __UpperCamelCase       :  Union[str, Any] ,       __UpperCamelCase       :  Optional[int] ,       __UpperCamelCase       :  Optional[Any] ,       __UpperCamelCase       :  Optional[int] ,       __UpperCamelCase       :  Any ,       __UpperCamelCase       :  int ,       __UpperCamelCase       :  List[str] ):
												lowerCamelCase_					=       TFDebertaVaModel(config=__UpperCamelCase )
												lowerCamelCase_					=       {"""input_ids""": input_ids, """attention_mask""": input_mask, """token_type_ids""": token_type_ids}

												lowerCamelCase_					=       [input_ids, input_mask]
												lowerCamelCase_					=       model(__UpperCamelCase )

												lowerCamelCase_					=       model(__UpperCamelCase )

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

					def  lowercase__   (						self       :  Optional[int] ,       __UpperCamelCase       :  List[str] ,       __UpperCamelCase       :  str ,       __UpperCamelCase       :  Dict ,       __UpperCamelCase       :  str ,       __UpperCamelCase       :  List[str] ,       __UpperCamelCase       :  Tuple ,       __UpperCamelCase       :  int ):
												lowerCamelCase_					=       TFDebertaVaForMaskedLM(config=__UpperCamelCase )
												lowerCamelCase_					=       {
												    """input_ids""": input_ids,
												    """attention_mask""": input_mask,
												    """token_type_ids""": token_type_ids,
												}
												lowerCamelCase_					=       model(__UpperCamelCase )
												self.parent.assertEqual(result.logits.shape ,       (self.batch_size, self.seq_length, self.vocab_size) )

					def  lowercase__   (						self       :  List[Any] ,       __UpperCamelCase       :  Union[str, Any] ,       __UpperCamelCase       :  str ,       __UpperCamelCase       :  int ,       __UpperCamelCase       :  Optional[int] ,       __UpperCamelCase       :  List[Any] ,       __UpperCamelCase       :  str ,       __UpperCamelCase       :  List[Any] ):
												lowerCamelCase_					=       self.num_labels
												lowerCamelCase_					=       TFDebertaVaForSequenceClassification(config=__UpperCamelCase )
												lowerCamelCase_					=       {
												    """input_ids""": input_ids,
												    """attention_mask""": input_mask,
												    """token_type_ids""": token_type_ids,
												}

												lowerCamelCase_					=       model(__UpperCamelCase )
												self.parent.assertEqual(result.logits.shape ,       (self.batch_size, self.num_labels) )

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

					def  lowercase__   (						self       :  List[Any] ,       __UpperCamelCase       :  Optional[int] ,       __UpperCamelCase       :  Optional[Any] ,       __UpperCamelCase       :  Optional[int] ,       __UpperCamelCase       :  str ,       __UpperCamelCase       :  Optional[Any] ,       __UpperCamelCase       :  List[str] ,       __UpperCamelCase       :  int ):
												lowerCamelCase_					=       TFDebertaVaForQuestionAnswering(config=__UpperCamelCase )
												lowerCamelCase_					=       {
												    """input_ids""": input_ids,
												    """attention_mask""": input_mask,
												    """token_type_ids""": token_type_ids,
												}

												lowerCamelCase_					=       model(__UpperCamelCase )
												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  lowercase__   (						self       :  Dict ):
												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    __A(					UpperCAmelCase  ,		UpperCAmelCase  ,		unittest.TestCase							):
					SCREAMING_SNAKE_CASE           =     (
					    (
					        TFDebertaVaModel,
					        TFDebertaVaForMaskedLM,
					        TFDebertaVaForQuestionAnswering,
					        TFDebertaVaForSequenceClassification,
					        TFDebertaVaForTokenClassification,
					    )
					    if is_tf_available()
					    else ()
					)
					SCREAMING_SNAKE_CASE           =     (
					    {
					        '''feature-extraction''': TFDebertaVaModel,
					        '''fill-mask''': TFDebertaVaForMaskedLM,
					        '''question-answering''': TFDebertaVaForQuestionAnswering,
					        '''text-classification''': TFDebertaVaForSequenceClassification,
					        '''token-classification''': TFDebertaVaForTokenClassification,
					        '''zero-shot''': TFDebertaVaForSequenceClassification,
					    }
					    if is_tf_available()
					    else {}
					)

					SCREAMING_SNAKE_CASE           =     False
					SCREAMING_SNAKE_CASE           =     False

					def  lowercase__   (						self       :  Dict ):
												lowerCamelCase_					=       TFDebertaVaModelTester(self )
												lowerCamelCase_					=       ConfigTester(self ,       config_class=__UpperCamelCase ,       hidden_size=3_7 )

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

					def  lowercase__   (						self       :  Optional[Any] ):
												lowerCamelCase_					=       self.model_tester.prepare_config_and_inputs()
												self.model_tester.create_and_check_model(*__UpperCamelCase )

					def  lowercase__   (						self       :  Dict ):
												lowerCamelCase_					=       self.model_tester.prepare_config_and_inputs()
												self.model_tester.create_and_check_for_masked_lm(*__UpperCamelCase )

					def  lowercase__   (						self       :  List[Any] ):
												lowerCamelCase_					=       self.model_tester.prepare_config_and_inputs()
												self.model_tester.create_and_check_for_question_answering(*__UpperCamelCase )

					def  lowercase__   (						self       :  Tuple ):
												lowerCamelCase_					=       self.model_tester.prepare_config_and_inputs()
												self.model_tester.create_and_check_for_sequence_classification(*__UpperCamelCase )

					def  lowercase__   (						self       :  Any ):
												lowerCamelCase_					=       self.model_tester.prepare_config_and_inputs()
												self.model_tester.create_and_check_for_token_classification(*__UpperCamelCase )



					@slow
					def  lowercase__   (						self       :  int ):
												lowerCamelCase_					=       TFDebertaVaModel.from_pretrained("""kamalkraj/deberta-v2-xlarge""" )
												self.assertIsNotNone(__UpperCamelCase )





@require_tf
class    __A(					unittest.TestCase							):

					@unittest.skip(reason="""Model not available yet""" )
					def  lowercase__   (						self       :  Optional[int] ):
												pass



					@slow
					def  lowercase__   (						self       :  Any ):
												lowerCamelCase_					=       TFDebertaVaModel.from_pretrained("""kamalkraj/deberta-v2-xlarge""" )
												lowerCamelCase_					=       tf.constant([[0, 3_1_4_1_4, 2_3_2, 3_2_8, 7_4_0, 1_1_4_0, 1_2_6_9_5, 6_9, 4_6_0_7_8, 1_5_8_8, 2]] )
												lowerCamelCase_					=       tf.constant([[0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]] )
												lowerCamelCase_					=       model(__UpperCamelCase ,       attention_mask=__UpperCamelCase )[0]

												lowerCamelCase_					=       tf.constant(
												    [[[0.2356, 0.1948, 0.0369], [-0.1063, 0.3586, -0.5152], [-0.6399, -0.0259, -0.2525]]] )
												tf.debugging.assert_near(output[:, 1:4, 1:4] ,       __UpperCamelCase ,       atol=1E-4 )





