
import unittest

from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


lowercase_ 				=			get_tests_dir("""fixtures/spiece.model""")





@require_sentencepiece
@require_tokenizers
class     __UpperCamelCase (							lowerCAmelCase__ ,						unittest.TestCase       ):






     """simple docstring"""







     lowerCAmelCase_							   =			DebertaVaTokenizer
     lowerCAmelCase_							   =			DebertaVaTokenizerFast
     lowerCAmelCase_							   =			True
     lowerCAmelCase_							   =			True



     def  UpperCAmelCase__							(				self							:							Dict ):







       """simple docstring"""




       super().setUp()

       # We have a SentencePiece fixture for testing
       __SCREAMING_SNAKE_CASE      :	str					=		DebertaVaTokenizer(_A     ,						unk_token='''<unk>''' )
       tokenizer.save_pretrained(self.tmpdirname )



     def  UpperCAmelCase__							(				self							:							Union[str, Any]     ,						_A							:							List[Any] ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	str					=		'''this is a test'''
       __SCREAMING_SNAKE_CASE      :	Dict					=		'''this is a test'''
       return input_text, output_text



     def  UpperCAmelCase__							(				self							:							Dict ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	Optional[int]					=		'''<pad>'''
       __SCREAMING_SNAKE_CASE      :	Optional[Any]					=		0

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



     def  UpperCAmelCase__							(				self							:							Tuple ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	Optional[Any]					=		list(self.get_tokenizer().get_vocab().keys() )
       self.assertEqual(vocab_keys[0]     ,						'''<pad>''' )
       self.assertEqual(vocab_keys[1]     ,						'''<unk>''' )
       self.assertEqual(vocab_keys[-1]     ,						'''[PAD]''' )
       self.assertEqual(len(_A )     ,						3_0001 )



     def  UpperCAmelCase__							(				self							:							List[Any] ):







       """simple docstring"""




       self.assertEqual(self.get_tokenizer().vocab_size     ,						3_0000 )



     def  UpperCAmelCase__							(				self							:							Any ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	List[Any]					=		''' \tHeLLo!how  \n Are yoU?  '''
       __SCREAMING_SNAKE_CASE      :	Union[str, Any]					=		['''▁hello''', '''!''', '''how''', '''▁are''', '''▁you''', '''?''']
       # fmt: on

       __SCREAMING_SNAKE_CASE      :	List[str]					=		DebertaVaTokenizer(_A     ,						do_lower_case=_A )
       __SCREAMING_SNAKE_CASE      :	Optional[Any]					=		tokenizer.convert_ids_to_tokens(tokenizer.encode(_A     ,						add_special_tokens=_A ) )

       self.assertListEqual(_A     ,						_A )

       __SCREAMING_SNAKE_CASE      :	Tuple					=		DebertaVaTokenizerFast(_A     ,						do_lower_case=_A )
       __SCREAMING_SNAKE_CASE      :	List[Any]					=		rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(_A     ,						add_special_tokens=_A ) )

       self.assertListEqual(_A     ,						_A )



     @unittest.skip('''There is an inconsistency between slow and fast tokenizer due to a bug in the fast one.''' )
     def  UpperCAmelCase__							(				self							:							Any ):







       """simple docstring"""




       pass



     @unittest.skip('''There is an inconsistency between slow and fast tokenizer due to a bug in the fast one.''' )
     def  UpperCAmelCase__							(				self							:							Union[str, Any] ):







       """simple docstring"""




       pass



     def  UpperCAmelCase__							(				self							:							List[str] ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	Optional[Any]					=		'''I was born in 92000, and this is falsé.'''
       __SCREAMING_SNAKE_CASE      :	Optional[int]					=		['''▁''', '''<unk>''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', '''▁''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''▁''', '''.''', ]
       # fmt: on

       __SCREAMING_SNAKE_CASE      :	Any					=		DebertaVaTokenizer(_A     ,						split_by_punct=_A )
       __SCREAMING_SNAKE_CASE      :	Dict					=		tokenizer.convert_ids_to_tokens(tokenizer.encode(_A     ,						add_special_tokens=_A ) )

       self.assertListEqual(_A     ,						_A )

       __SCREAMING_SNAKE_CASE      :	Tuple					=		DebertaVaTokenizerFast(_A     ,						split_by_punct=_A )
       __SCREAMING_SNAKE_CASE      :	Tuple					=		rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(_A     ,						add_special_tokens=_A ) )

       self.assertListEqual(_A     ,						_A )



     def  UpperCAmelCase__							(				self							:							Union[str, Any] ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	str					=		'''I was born in 92000, and this is falsé.'''
       __SCREAMING_SNAKE_CASE      :	Optional[Any]					=		['''▁i''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', '''▁''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''▁''', '''.''', ]
       # fmt: on

       __SCREAMING_SNAKE_CASE      :	List[str]					=		DebertaVaTokenizer(_A     ,						do_lower_case=_A     ,						split_by_punct=_A )
       __SCREAMING_SNAKE_CASE      :	int					=		tokenizer.convert_ids_to_tokens(tokenizer.encode(_A     ,						add_special_tokens=_A ) )
       self.assertListEqual(_A     ,						_A )

       __SCREAMING_SNAKE_CASE      :	str					=		DebertaVaTokenizerFast(_A     ,						do_lower_case=_A     ,						split_by_punct=_A )
       __SCREAMING_SNAKE_CASE      :	List[str]					=		rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(_A     ,						add_special_tokens=_A ) )
       self.assertListEqual(_A     ,						_A )



     def  UpperCAmelCase__							(				self							:							List[Any] ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	Tuple					=		'''I was born in 92000, and this is falsé.'''
       __SCREAMING_SNAKE_CASE      :	List[str]					=		['''▁i''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''.''', ]
       # fmt: on

       __SCREAMING_SNAKE_CASE      :	Union[str, Any]					=		DebertaVaTokenizer(_A     ,						do_lower_case=_A     ,						split_by_punct=_A )
       __SCREAMING_SNAKE_CASE      :	Optional[int]					=		tokenizer.convert_ids_to_tokens(tokenizer.encode(_A     ,						add_special_tokens=_A ) )

       self.assertListEqual(_A     ,						_A )

       __SCREAMING_SNAKE_CASE      :	Optional[int]					=		DebertaVaTokenizerFast(_A     ,						do_lower_case=_A     ,						split_by_punct=_A )
       __SCREAMING_SNAKE_CASE      :	List[Any]					=		rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(_A     ,						add_special_tokens=_A ) )

       self.assertListEqual(_A     ,						_A )



     def  UpperCAmelCase__							(				self							:							Optional[int] ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	Any					=		'''I was born in 92000, and this is falsé.'''
       __SCREAMING_SNAKE_CASE      :	Optional[int]					=		['''▁''', '''<unk>''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', '''▁''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''▁''', '''.''', ]
       # fmt: on

       __SCREAMING_SNAKE_CASE      :	Optional[int]					=		DebertaVaTokenizer(_A     ,						do_lower_case=_A     ,						split_by_punct=_A )
       __SCREAMING_SNAKE_CASE      :	Optional[int]					=		tokenizer.convert_ids_to_tokens(tokenizer.encode(_A     ,						add_special_tokens=_A ) )

       self.assertListEqual(_A     ,						_A )

       __SCREAMING_SNAKE_CASE      :	Union[str, Any]					=		DebertaVaTokenizerFast(_A     ,						do_lower_case=_A     ,						split_by_punct=_A )
       __SCREAMING_SNAKE_CASE      :	Any					=		rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(_A     ,						add_special_tokens=_A ) )

       self.assertListEqual(_A     ,						_A )



     def  UpperCAmelCase__							(				self							:							Any ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	Union[str, Any]					=		''' \tHeLLo!how  \n Are yoU?  '''
       __SCREAMING_SNAKE_CASE      :	Union[str, Any]					=		['''▁''', '''<unk>''', '''e''', '''<unk>''', '''o''', '''!''', '''how''', '''▁''', '''<unk>''', '''re''', '''▁yo''', '''<unk>''', '''?''']
       # fmt: on

       __SCREAMING_SNAKE_CASE      :	Tuple					=		DebertaVaTokenizer(_A     ,						do_lower_case=_A     ,						split_by_punct=_A )
       __SCREAMING_SNAKE_CASE      :	Tuple					=		tokenizer.convert_ids_to_tokens(tokenizer.encode(_A     ,						add_special_tokens=_A ) )

       self.assertListEqual(_A     ,						_A )

       __SCREAMING_SNAKE_CASE      :	Dict					=		DebertaVaTokenizerFast(_A     ,						do_lower_case=_A     ,						split_by_punct=_A )
       __SCREAMING_SNAKE_CASE      :	List[str]					=		rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(_A     ,						add_special_tokens=_A ) )

       self.assertListEqual(_A     ,						_A )



     def  UpperCAmelCase__							(				self							:							Union[str, Any] ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	Union[str, Any]					=		self.get_tokenizer()
       __SCREAMING_SNAKE_CASE      :	Any					=		self.get_rust_tokenizer()

       __SCREAMING_SNAKE_CASE      :	Dict					=		'''I was born in 92000, and this is falsé.'''

       __SCREAMING_SNAKE_CASE      :	Union[str, Any]					=		tokenizer.convert_ids_to_tokens(tokenizer.encode(_A     ,						add_special_tokens=_A ) )
       __SCREAMING_SNAKE_CASE      :	Optional[Any]					=		rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(_A     ,						add_special_tokens=_A ) )
       self.assertListEqual(_A     ,						_A )

       __SCREAMING_SNAKE_CASE      :	str					=		tokenizer.encode(_A     ,						add_special_tokens=_A )
       __SCREAMING_SNAKE_CASE      :	List[Any]					=		rust_tokenizer.encode(_A     ,						add_special_tokens=_A )
       self.assertListEqual(_A     ,						_A )

       __SCREAMING_SNAKE_CASE      :	Optional[Any]					=		self.get_rust_tokenizer()
       __SCREAMING_SNAKE_CASE      :	Tuple					=		tokenizer.encode(_A )
       __SCREAMING_SNAKE_CASE      :	List[str]					=		rust_tokenizer.encode(_A )
       self.assertListEqual(_A     ,						_A )



     def  UpperCAmelCase__							(				self							:							Any ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	Optional[int]					=		'''This is a test'''
       __SCREAMING_SNAKE_CASE      :	str					=		[13, 1, 4398, 25, 21, 1289]
       __SCREAMING_SNAKE_CASE      :	Any					=		['''▁''', '''T''', '''his''', '''▁is''', '''▁a''', '''▁test''']
       __SCREAMING_SNAKE_CASE      :	Optional[Any]					=		['''▁''', '''<unk>''', '''his''', '''▁is''', '''▁a''', '''▁test''']

       __SCREAMING_SNAKE_CASE      :	List[str]					=		DebertaVaTokenizer(_A     ,						keep_accents=_A )
       __SCREAMING_SNAKE_CASE      :	Dict					=		DebertaVaTokenizerFast(_A     ,						keep_accents=_A )

       __SCREAMING_SNAKE_CASE      :	int					=		tokenizer.encode(_A     ,						add_special_tokens=_A )
       self.assertListEqual(_A     ,						_A )
       __SCREAMING_SNAKE_CASE      :	Tuple					=		tokenizer.tokenize(_A )
       self.assertListEqual(_A     ,						_A )
       __SCREAMING_SNAKE_CASE      :	Union[str, Any]					=		tokenizer.convert_ids_to_tokens(_A )
       self.assertListEqual(_A     ,						_A )

       __SCREAMING_SNAKE_CASE      :	str					=		rust_tokenizer.encode(_A     ,						add_special_tokens=_A )
       self.assertListEqual(_A     ,						_A )
       __SCREAMING_SNAKE_CASE      :	Dict					=		rust_tokenizer.tokenize(_A )
       self.assertListEqual(_A     ,						_A )
       __SCREAMING_SNAKE_CASE      :	Any					=		rust_tokenizer.convert_ids_to_tokens(_A )
       self.assertListEqual(_A     ,						_A )

       # fmt: off
       __SCREAMING_SNAKE_CASE      :	int					=		'''I was born in 92000, and this is falsé.'''
       __SCREAMING_SNAKE_CASE      :	Union[str, Any]					=		[13, 1, 23, 386, 19, 561, 3050, 15, 17, 48, 25, 8256, 18, 1, 9]
       __SCREAMING_SNAKE_CASE      :	str					=		['''▁''', '''I''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''é''', '''.''', ]
       __SCREAMING_SNAKE_CASE      :	Tuple					=		['''▁''', '''<unk>''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''.''', ]
       # fmt: on

       __SCREAMING_SNAKE_CASE      :	Union[str, Any]					=		tokenizer.encode(_A     ,						add_special_tokens=_A )
       self.assertListEqual(_A     ,						_A )
       __SCREAMING_SNAKE_CASE      :	List[str]					=		tokenizer.tokenize(_A )
       self.assertListEqual(_A     ,						_A )
       __SCREAMING_SNAKE_CASE      :	str					=		tokenizer.convert_ids_to_tokens(_A )
       self.assertListEqual(_A     ,						_A )

       __SCREAMING_SNAKE_CASE      :	Union[str, Any]					=		rust_tokenizer.encode(_A     ,						add_special_tokens=_A )
       self.assertListEqual(_A     ,						_A )
       __SCREAMING_SNAKE_CASE      :	Optional[Any]					=		rust_tokenizer.tokenize(_A )
       self.assertListEqual(_A     ,						_A )
       __SCREAMING_SNAKE_CASE      :	List[Any]					=		rust_tokenizer.convert_ids_to_tokens(_A )
       self.assertListEqual(_A     ,						_A )



     def  UpperCAmelCase__							(				self							:							Optional[Any] ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	Dict					=		DebertaVaTokenizer(_A )

       __SCREAMING_SNAKE_CASE      :	Union[str, Any]					=		tokenizer.encode('''sequence builders''' )
       __SCREAMING_SNAKE_CASE      :	Any					=		tokenizer.encode('''multi-sequence build''' )

       __SCREAMING_SNAKE_CASE      :	Tuple					=		tokenizer.build_inputs_with_special_tokens(_A )
       __SCREAMING_SNAKE_CASE      :	Optional[Any]					=		tokenizer.build_inputs_with_special_tokens(_A     ,						_A )

       self.assertEqual([tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]     ,						_A )
       self.assertEqual(
           [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [tokenizer.sep_token_id]     ,						_A     ,						)




     @slow
     def  UpperCAmelCase__							(				self							:							Union[str, Any] ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	Any					=		{'''input_ids''': [[1, 3_9867, 36, 1_9390, 486, 27, 3_5052, 8_1436, 18, 6_0685, 1225, 7, 3_5052, 8_1436, 18, 9367, 1_6899, 18, 1_5937, 53, 594, 773, 18, 1_6287, 3_0465, 36, 1_5937, 6, 4_1139, 38, 3_6979, 6_0763, 191, 6, 3_4132, 99, 6, 5_0538, 390, 4_3230, 6, 3_4132, 2779, 2_0850, 14, 699, 1072, 1194, 36, 382, 1_0901, 53, 7, 699, 1072, 2084, 36, 2_0422, 630, 53, 19, 105, 3049, 1896, 1053, 1_6899, 1506, 11, 3_7978, 4243, 7, 1237, 3_1869, 200, 1_6566, 654, 6, 3_5052, 8_1436, 7, 5_5630, 1_3593, 4, 2], [1, 26, 1_5011, 13, 667, 8, 1053, 18, 2_3611, 1237, 7_2356, 1_2820, 34, 10_4134, 1209, 35, 1_3313, 6627, 21, 202, 347, 7, 164, 2399, 11, 46, 4485, 4, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 5, 1232, 2864, 1_5785, 1_4951, 105, 5, 8581, 1250, 4, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], '''token_type_ids''': [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], '''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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
       # fmt: on

       self.tokenizer_integration_test_util(
           expected_encoding=_A     ,						model_name='''microsoft/deberta-v2-xlarge'''     ,						revision='''ad6e42c1532ddf3a15c39246b63f5559d558b670'''     ,						)







from __future__ import annotations

import unittest

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

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


if is_tf_available():
 import numpy
 import tensorflow as tf

 from transformers.models.esm.modeling_tf_esm import (
     TF_ESM_PRETRAINED_MODEL_ARCHIVE_LIST,
     TFEsmForMaskedLM,
     TFEsmForSequenceClassification,
     TFEsmForTokenClassification,
     TFEsmModel,
 )







class      lowerCamelCase:
     '''simple docstring'''


     def __init__(    self				,     snake_case_				,     ):
         _A     =							parent
         _A     =							13
         _A     =							7
         _A     =							True
         _A     =							True
         _A     =							True
         _A     =							99
         _A     =							32
         _A     =							2
         _A     =							4
         _A     =							37
         _A     =							'gelu'
         _A     =							0.1
         _A     =							0.1
         _A     =							512
         _A     =							16
         _A     =							2
         _A     =							0.02
         _A     =							3
         _A     =							4
         _A     =							None




     def        lowerCAmelCase__		(    self							):
         _A     =							ids_tensor([self.batch_size, self.seq_length]				,     self.vocab_size							)

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

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

         _A     =							EsmConfig(
             vocab_size=self.vocab_size				,     hidden_size=self.hidden_size				,     num_hidden_layers=self.num_hidden_layers				,     pad_token_id=1				,     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, input_mask, sequence_labels, token_labels, choice_labels




     def        lowerCAmelCase__		(    self							):
         (
             (
             _A
         ),			(
             _A
         ),			(
             _A
         ),			(
             _A
         ),			(
             _A
         ),			(
             _A
         ),			
         )     =							self.prepare_config_and_inputs()

         _A     =							True
         _A     =							floats_tensor([self.batch_size, self.seq_length, self.hidden_size]							)
         _A     =							ids_tensor([self.batch_size, self.seq_length]				,     vocab_size=2							)

         return (
             config,
             input_ids,
             input_mask,
             sequence_labels,
             token_labels,
             choice_labels,
             encoder_hidden_states,
             encoder_attention_mask,
         )




     def        lowerCAmelCase__		(    self				,     snake_case_				,     snake_case_				,     snake_case_				,     snake_case_				,     snake_case_				,     snake_case_							):
         _A     =							TFEsmModel(config=snake_case_							)
         _A     =							{'input_ids': input_ids, 'attention_mask': input_mask}
         _A     =							model(snake_case_							)

         _A     =							[input_ids, input_mask]
         _A     =							model(snake_case_							)

         _A     =							model(snake_case_							)

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




     def        lowerCAmelCase__		(    self				,     snake_case_				,     snake_case_				,     snake_case_				,     snake_case_				,     snake_case_				,     snake_case_				,     snake_case_				,     snake_case_				,     ):
         _A     =							True

         _A     =							TFEsmModel(config=snake_case_							)
         _A     =							{
             'input_ids': input_ids,
             'attention_mask': input_mask,
             'encoder_hidden_states': encoder_hidden_states,
             'encoder_attention_mask': encoder_attention_mask,
         }
         _A     =							model(snake_case_							)

         _A     =							[input_ids, input_mask]
         _A     =							model(snake_case_				,     encoder_hidden_states=snake_case_							)

         # Also check the case where encoder outputs are not passed
         _A     =							model(snake_case_				,     attention_mask=snake_case_							)

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




     def        lowerCAmelCase__		(    self				,     snake_case_				,     snake_case_				,     snake_case_				,     snake_case_				,     snake_case_				,     snake_case_							):
         _A     =							TFEsmForMaskedLM(config=snake_case_							)
         _A     =							model([input_ids, input_mask]							)
         self.parent.assertEqual(result.logits.shape				,     (self.batch_size, self.seq_length, self.vocab_size)							)




     def        lowerCAmelCase__		(    self				,     snake_case_				,     snake_case_				,     snake_case_				,     snake_case_				,     snake_case_				,     snake_case_							):
         _A     =							self.num_labels
         _A     =							TFEsmForTokenClassification(config=snake_case_							)
         _A     =							{'input_ids': input_ids, 'attention_mask': input_mask}
         _A     =							model(snake_case_							)
         self.parent.assertEqual(result.logits.shape				,     (self.batch_size, self.seq_length, self.num_labels)							)




     def        lowerCAmelCase__		(    self							):
         _A     =							self.prepare_config_and_inputs()
         (
             (
             _A
         ),			(
             _A
         ),			(
             _A
         ),			(
             _A
         ),			(
             _A
         ),			(
             _A
         ),			
         )     =							config_and_inputs
         _A     =							{'input_ids': input_ids, 'attention_mask': input_mask}
         return config, inputs_dict







@require_tf
class      lowerCamelCase(						__snake_case			, __snake_case			, unittest.TestCase	):
     '''simple docstring'''


     __magic_name__   =			(
         (
             TFEsmModel,
             TFEsmForMaskedLM,
             TFEsmForSequenceClassification,
             TFEsmForTokenClassification,
         )
         if is_tf_available()
         else ()
     )
     __magic_name__   =			(
         {
             'feature-extraction': TFEsmModel,
             'fill-mask': TFEsmForMaskedLM,
             'text-classification': TFEsmForSequenceClassification,
             'token-classification': TFEsmForTokenClassification,
             'zero-shot': TFEsmForSequenceClassification,
         }
         if is_tf_available()
         else {}
     )
     __magic_name__   =			False
     __magic_name__   =			False




     def        lowerCAmelCase__		(    self							):
         _A     =							TFEsmModelTester(self							)
         _A     =							ConfigTester(self				,     config_class=snake_case_				,     hidden_size=37							)




     def        lowerCAmelCase__		(    self							):
         self.config_tester.run_common_tests()




     def        lowerCAmelCase__		(    self							):
         _A     =							self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_model(*snake_case_							)




     def        lowerCAmelCase__		(    self							):
         _A     =							self.model_tester.prepare_config_and_inputs_for_decoder()
         self.model_tester.create_and_check_model_as_decoder(*snake_case_							)




     def        lowerCAmelCase__		(    self							):
         _A     =							self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_for_masked_lm(*snake_case_							)




     def        lowerCAmelCase__		(    self							):
         _A     =							self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_for_token_classification(*snake_case_							)




     @slow
     def        lowerCAmelCase__		(    self							):
         for model_name in TF_ESM_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
             _A     =							TFEsmModel.from_pretrained(snake_case_							)
             self.assertIsNotNone(snake_case_							)




     @unittest.skip('Protein models do not support embedding resizing.'							)
     def        lowerCAmelCase__		(    self							):
         pass




     @unittest.skip('Protein models do not support embedding resizing.'							)
     def        lowerCAmelCase__		(    self							):
         pass




     def        lowerCAmelCase__		(    self							):
         _A,			_A     =							self.model_tester.prepare_config_and_inputs_for_common()

         for model_class in self.all_model_classes:
             _A     =							model_class(snake_case_							)
             assert isinstance(model.get_input_embeddings()				,     tf.keras.layers.Layer							)
             if model_class is TFEsmForMaskedLM:
                 # Output embedding test differs from the main test because they're a matrix, not a layer
                 _A     =							model.get_bias()
                 assert isinstance(snake_case_				,     snake_case_							)
                 for k, v in name.items():
                     assert isinstance(snake_case_				,     tf.Variable							)
             else:
                 _A     =							model.get_output_embeddings()
                 assert x is None
                 _A     =							model.get_bias()
                 assert name is None







@require_tf
class      lowerCamelCase(						unittest.TestCase	):
     '''simple docstring'''


     @slow
     def        lowerCAmelCase__		(    self							):
         _A     =							TFEsmForMaskedLM.from_pretrained('facebook/esm2_t6_8M_UR50D'							)

         _A     =							tf.constant([[0, 1, 2, 3, 4, 5]]							)
         _A     =							model(snake_case_							)[0]
         _A     =							[1, 6, 33]
         self.assertEqual(list(output.numpy().shape							)				,     snake_case_							)
         # compare the actual values for a slice.
         _A     =							tf.constant(
             [
                 [
                     [8.92_1518, -10.58_9814, -6.467_1307],
                     [-6.396_7156, -13.91_1377, -1.121_1915],
                     [-7.78_1247, -13.95_1557, -3.74_0592],
                 ]
             ]							)
         self.assertTrue(numpy.allclose(output[:, :3, :3].numpy()				,     expected_slice.numpy()				,     atol=1E-2							)							)




     @slow
     def        lowerCAmelCase__		(    self							):
         _A     =							TFEsmModel.from_pretrained('facebook/esm2_t6_8M_UR50D'							)

         _A     =							tf.constant([[0, 6, 4, 13, 5, 4, 16, 12, 11, 7, 2]]							)
         _A     =							model(snake_case_							)[0]
         # compare the actual values for a slice.
         _A     =							tf.constant(
             [
                 [
                     [0.1444_3092, 0.5412_5327, 0.324_7739],
                     [0.3034_0484, 0.0052_6676, 0.3107_7722],
                     [0.3227_8043, -0.2498_7096, 0.341_4628],
                 ]
             ]							)
         self.assertTrue(numpy.allclose(output[:, :3, :3].numpy()				,     expected_slice.numpy()				,     atol=1E-4							)							)





