


'''simple docstring'''
import unittest

from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


__SCREAMING_SNAKE_CASE					:				str									=		get_tests_dir('''fixtures/test_sentencepiece_with_bytefallback.model''')






@require_sentencepiece
@require_tokenizers
class 					__lowerCAmelCase   (   _UpperCAmelCase				,			unittest.TestCase						):

						"""simple docstring"""






						_UpperCAmelCase		:       int   						=GPTSwaTokenizer
						_UpperCAmelCase		:       List[str]   						=False
						_UpperCAmelCase		:       Optional[Any]   						=True
						_UpperCAmelCase		:       int   						=False






						def 				_UpperCAmelCase       (  self							:      List[str]	):
													super().setUp()

													# We have a SentencePiece fixture for testing
													A_			    =		GPTSwaTokenizer(SCREAMING_SNAKE_CASE_ ,  eos_token="<unk>" ,  bos_token="<unk>" ,  pad_token="<unk>"	)

													tokenizer.save_pretrained(self.tmpdirname	)






						def 				_UpperCAmelCase       (  self							:      List[str] ,  lowerCAmelCase							:      Optional[Any]	):
													A_			    =		'This is a test'
													A_			    =		'This is a test'
													return input_text, output_text






						def 				_UpperCAmelCase       (  self							:      Any	):
													A_			    =		'<s>'
													A_			    =		1

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






						def 				_UpperCAmelCase       (  self							:      Optional[int]	):
													A_			    =		list(self.get_tokenizer().get_vocab().keys()	)

													self.assertEqual(vocab_keys[0] ,  "<unk>"	)
													self.assertEqual(vocab_keys[1] ,  "<s>"	)
													self.assertEqual(vocab_keys[-1] ,  "j"	)
													self.assertEqual(len(SCREAMING_SNAKE_CASE_	) ,  20_00	)






						def 				_UpperCAmelCase       (  self							:      int	):
													self.assertEqual(self.get_tokenizer().vocab_size ,  20_00	)






						def 				_UpperCAmelCase       (  self							:      Dict	):
													A_			    =		GPTSwaTokenizer(SCREAMING_SNAKE_CASE_	)

													A_			    =		tokenizer.tokenize("This is a test"	)
													self.assertListEqual(SCREAMING_SNAKE_CASE_ ,  ["▁This", "▁is", "▁a", "▁t", "est"]	)

													self.assertListEqual(tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_	) ,  [4_65, 2_87, 2_65, 6_31, 8_42]	)

													A_			    =		tokenizer.tokenize("I was born in 92000, and this is falsé."	)
													# fmt: off
													self.assertListEqual(
													    SCREAMING_SNAKE_CASE_ ,  ["▁I", "▁was", "▁bor", "n", "▁in", "▁", "<0x39>", "2", "0", "0", "0", ",", "▁and", "▁this", "▁is", "▁f", "al", "s", "<0xC3>", "<0xA9>", "."] ,  )
													# fmt: on

													A_			    =		tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_	)
													self.assertListEqual(
													    SCREAMING_SNAKE_CASE_ ,  [2_62, 2_72, 15_25, 2_86, 2_71, 2_68, 60, 9_16, 6_33, 6_33, 6_33, 2_59, 2_66, 3_01, 2_87, 3_84, 3_67, 2_63, 1_98, 1_72, 2_60] ,  )

													A_			    =		tokenizer.convert_ids_to_tokens(SCREAMING_SNAKE_CASE_	)
													# fmt: off
													self.assertListEqual(
													    SCREAMING_SNAKE_CASE_ ,  ["▁I", "▁was", "▁bor", "n", "▁in", "▁", "<0x39>", "2", "0", "0", "0", ",", "▁and", "▁this", "▁is", "▁f", "al", "s", "<0xC3>", "<0xA9>", "."]	)
													# fmt: on






						def 				_UpperCAmelCase       (  self							:      Optional[int]	):
													A_			    =		GPTSwaTokenizer(SCREAMING_SNAKE_CASE_	)
													A_			    =		['This is a test', 'I was born in 92000, and this is falsé.']
													A_			    =		[
													    [4_65, 2_87, 2_65, 6_31, 8_42],
													    [2_62, 2_72, 15_25, 2_86, 2_71, 2_68, 60, 9_16, 6_33, 6_33, 6_33, 2_59, 2_66, 3_01, 2_87, 3_84, 3_67, 2_63, 1_98, 1_72, 2_60],
													]

													# Test that encode_fast returns the same as tokenize + convert_tokens_to_ids
													for text, expected_ids in zip(SCREAMING_SNAKE_CASE_ ,  SCREAMING_SNAKE_CASE_	):
																				self.assertListEqual(tokenizer.encode_fast(SCREAMING_SNAKE_CASE_	) ,  SCREAMING_SNAKE_CASE_	)

													# Test that decode_fast returns the input text
													for text, token_ids in zip(SCREAMING_SNAKE_CASE_ ,  SCREAMING_SNAKE_CASE_	):
																				self.assertEqual(tokenizer.decode_fast(SCREAMING_SNAKE_CASE_	) ,  SCREAMING_SNAKE_CASE_	)






						@slow
						def 				_UpperCAmelCase       (  self							:      Optional[Any]	):
													A_			    =		[
													    '<|python|>def fibonacci(n)\n    if n < 0:\n        print(\'Incorrect input\')',
													    'Hey there, how are you doing this fine day?',
													    'This is a text with a trailing spaces followed by a dot     .',
													    'Häj sväjs lillebrör! =)',
													    'Det är inget fel på Mr. Cool',
													]

													# fmt: off
													A_			    =		{'input_ids': [[6_34_23, 5, 68_11, 1_49_54, 2_82, 8_16, 38_21, 6_34_66, 6_34_25, 6_34_62, 18, 6_39_78, 6_78, 3_01, 13_20, 6_34_23, 6_34_55, 6_34_58, 18, 6_39_82, 42_46, 39_40, 19_01, 4_77_89, 55_47, 1_89_94], [1_96_30, 11_00, 6_34_46, 13_42, 6_33, 5_44, 44_88, 5_93, 51_02, 24_16, 6_34_95, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [16_52, 4_28, 2_68, 19_36, 5_15, 2_68, 5_85_93, 2_24_13, 91_06, 5_46, 2_68, 3_32_13, 6_39_79, 6_98, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [5_51_30, 6_34_50, 9_24, 6_34_49, 22_49, 40_62, 15_58, 3_18, 6_35_04, 2_14_98, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [5_09, 3_77, 28_27, 25_59, 3_32, 65_75, 6_34_43, 2_68_01, 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]], '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, 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, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [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], [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]]}
													# fmt: on
													self.tokenizer_integration_test_util(
													    expected_encoding=SCREAMING_SNAKE_CASE_ ,  model_name="AI-Sweden/gpt-sw3-126m" ,  sequences=SCREAMING_SNAKE_CASE_ ,  )









'''simple docstring'''



from dataclasses import asdict, dataclass
from typing import Optional

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


A__						:   List[str]				=    logging.get_logger(__name__)

# TODO Update this
A__						:   Tuple				=    {
    """facebook/esm-1b""": """https://huggingface.co/facebook/esm-1b/resolve/main/config.json""",
    # See all ESM models at https://huggingface.co/models?filter=esm
}





class   UpperCAmelCase_    (_UpperCAmelCase    ):





    """simple docstring"""






    lowerCamelCase    :   Tuple					=     'esm'







    def __init__(				self     ,	SCREAMING_SNAKE_CASE_=None     ,	SCREAMING_SNAKE_CASE_=None     ,	SCREAMING_SNAKE_CASE_=None     ,	SCREAMING_SNAKE_CASE_=7_68     ,	SCREAMING_SNAKE_CASE_=12     ,	SCREAMING_SNAKE_CASE_=12     ,	SCREAMING_SNAKE_CASE_=30_72     ,	SCREAMING_SNAKE_CASE_=0.1     ,	SCREAMING_SNAKE_CASE_=0.1     ,	SCREAMING_SNAKE_CASE_=10_26     ,	SCREAMING_SNAKE_CASE_=0.0_2     ,	SCREAMING_SNAKE_CASE_=1E-12     ,	SCREAMING_SNAKE_CASE_="absolute"     ,	SCREAMING_SNAKE_CASE_=True     ,	SCREAMING_SNAKE_CASE_=None     ,	SCREAMING_SNAKE_CASE_=False     ,	SCREAMING_SNAKE_CASE_=False     ,	SCREAMING_SNAKE_CASE_=None     ,	SCREAMING_SNAKE_CASE_=None     ,	**SCREAMING_SNAKE_CASE_     ,	)							->	List[str]:
         super().__init__(pad_token_id=SCREAMING_SNAKE_CASE_     ,	mask_token_id=SCREAMING_SNAKE_CASE_     ,	**SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      int														=						vocab_size
         __lowerCamelCase  :      List[Any]														=						hidden_size
         __lowerCamelCase  :      str														=						num_hidden_layers
         __lowerCamelCase  :      List[str]														=						num_attention_heads
         __lowerCamelCase  :      Any														=						intermediate_size
         __lowerCamelCase  :      Optional[Any]														=						hidden_dropout_prob
         __lowerCamelCase  :      Tuple														=						attention_probs_dropout_prob
         __lowerCamelCase  :      Optional[int]														=						max_position_embeddings
         __lowerCamelCase  :      str														=						initializer_range
         __lowerCamelCase  :      Optional[int]														=						layer_norm_eps
         __lowerCamelCase  :      List[str]														=						position_embedding_type
         __lowerCamelCase  :      int														=						use_cache
         __lowerCamelCase  :      Optional[Any]														=						emb_layer_norm_before
         __lowerCamelCase  :      Optional[Any]														=						token_dropout
         __lowerCamelCase  :      str														=						is_folding_model
         if is_folding_model:
              if esmfold_config is None:
                   logger.info('No esmfold_config supplied for folding model, using default values.'      )
                   __lowerCamelCase  :      Dict														=						EsmFoldConfig()
              elif isinstance(SCREAMING_SNAKE_CASE_     ,	SCREAMING_SNAKE_CASE_      ):
                   __lowerCamelCase  :      Optional[int]														=						EsmFoldConfig(**SCREAMING_SNAKE_CASE_      )
              __lowerCamelCase  :      List[Any]														=						esmfold_config
              if vocab_list is None:
                   logger.warning('No vocab_list supplied for folding model, assuming the ESM-2 vocabulary!'      )
                   __lowerCamelCase  :      List[str]														=						get_default_vocab_list()
              else:
                   __lowerCamelCase  :      Optional[Any]														=						vocab_list
         else:
              __lowerCamelCase  :      Dict														=						None
              __lowerCamelCase  :      Optional[Any]														=						None
         if self.esmfold_config is not None and getattr(self.esmfold_config     ,	'use_esm_attn_map'     ,	SCREAMING_SNAKE_CASE_      ):
              raise ValueError('The HuggingFace port of ESMFold does not support use_esm_attn_map at this time!'      )







    def  lowercase_							(				self      )							->	Any:
         __lowerCamelCase  :      Any														=						super().to_dict()
         if isinstance(self.esmfold_config     ,	SCREAMING_SNAKE_CASE_      ):
              __lowerCamelCase  :      int														=						self.esmfold_config.to_dict()
         return output







@dataclass
class   UpperCAmelCase_    :





    """simple docstring"""






    lowerCamelCase    :   str					=     None
    lowerCamelCase    :   bool					=     True
    lowerCamelCase    :   bool					=     False
    lowerCamelCase    :   bool					=     False
    lowerCamelCase    :   bool					=     False
    lowerCamelCase    :   float					=     0

    lowerCamelCase    :   bool					=     True
    lowerCamelCase    :   bool					=     False

    lowerCamelCase    :   int					=     1_2_8
    lowerCamelCase    :   "TrunkConfig"					=     None







    def  lowercase_							(				self      )							->	Any:
         if self.trunk is None:
              __lowerCamelCase  :      List[str]														=						TrunkConfig()
         elif isinstance(self.trunk     ,	SCREAMING_SNAKE_CASE_      ):
              __lowerCamelCase  :      Any														=						TrunkConfig(**self.trunk      )







    def  lowercase_							(				self      )							->	int:
         __lowerCamelCase  :      Optional[int]														=						asdict(self      )
         __lowerCamelCase  :      str														=						self.trunk.to_dict()
         return output







@dataclass
class   UpperCAmelCase_    :





    """simple docstring"""






    lowerCamelCase    :   int					=     4_8
    lowerCamelCase    :   int					=     1_0_2_4
    lowerCamelCase    :   int					=     1_2_8
    lowerCamelCase    :   int					=     3_2
    lowerCamelCase    :   int					=     3_2
    lowerCamelCase    :   int					=     3_2
    lowerCamelCase    :   float					=     0
    lowerCamelCase    :   float					=     0
    lowerCamelCase    :   bool					=     False
    lowerCamelCase    :   int					=     4
    lowerCamelCase    :   Optional[int]					=     1_2_8
    lowerCamelCase    :   "StructureModuleConfig"					=     None







    def  lowercase_							(				self      )							->	Optional[int]:
         if self.structure_module is None:
              __lowerCamelCase  :      Dict														=						StructureModuleConfig()
         elif isinstance(self.structure_module     ,	SCREAMING_SNAKE_CASE_      ):
              __lowerCamelCase  :      Optional[Any]														=						StructureModuleConfig(**self.structure_module      )

         if self.max_recycles <= 0:
              raise ValueError(f'`max_recycles` should be positive, got {self.max_recycles}.'      )
         if self.sequence_state_dim % self.sequence_state_dim != 0:
              raise ValueError(
                  '`sequence_state_dim` should be a round multiple of `sequence_state_dim`, got'
                  f' {self.sequence_state_dim} and {self.sequence_state_dim}.'      )
         if self.pairwise_state_dim % self.pairwise_state_dim != 0:
              raise ValueError(
                  '`pairwise_state_dim` should be a round multiple of `pairwise_state_dim`, got'
                  f' {self.pairwise_state_dim} and {self.pairwise_state_dim}.'      )

         __lowerCamelCase  :      Tuple														=						self.sequence_state_dim // self.sequence_head_width
         __lowerCamelCase  :      str														=						self.pairwise_state_dim // self.pairwise_head_width

         if self.sequence_state_dim != sequence_num_heads * self.sequence_head_width:
              raise ValueError(
                  '`sequence_state_dim` should be equal to `sequence_num_heads * sequence_head_width, got'
                  f' {self.sequence_state_dim} != {sequence_num_heads} * {self.sequence_head_width}.'      )
         if self.pairwise_state_dim != pairwise_num_heads * self.pairwise_head_width:
              raise ValueError(
                  '`pairwise_state_dim` should be equal to `pairwise_num_heads * pairwise_head_width, got'
                  f' {self.pairwise_state_dim} != {pairwise_num_heads} * {self.pairwise_head_width}.'      )
         if self.pairwise_state_dim % 2 != 0:
              raise ValueError(f'`pairwise_state_dim` should be even, got {self.pairwise_state_dim}.'      )

         if self.dropout >= 0.4:
              raise ValueError(f'`dropout` should not be greater than 0.4, got {self.dropout}.'      )







    def  lowercase_							(				self      )							->	List[Any]:
         __lowerCamelCase  :      List[str]														=						asdict(self      )
         __lowerCamelCase  :      int														=						self.structure_module.to_dict()
         return output







@dataclass
class   UpperCAmelCase_    :





    """simple docstring"""






    lowerCamelCase    :   int					=     3_8_4
    lowerCamelCase    :   int					=     1_2_8
    lowerCamelCase    :   int					=     1_6
    lowerCamelCase    :   int					=     1_2_8
    lowerCamelCase    :   int					=     1_2
    lowerCamelCase    :   int					=     4
    lowerCamelCase    :   int					=     8
    lowerCamelCase    :   float					=     0.1
    lowerCamelCase    :   int					=     8
    lowerCamelCase    :   int					=     1
    lowerCamelCase    :   int					=     2
    lowerCamelCase    :   int					=     7
    lowerCamelCase    :   int					=     1_0
    lowerCamelCase    :   float					=     1e-8
    lowerCamelCase    :   float					=     1e5







    def  lowercase_							(				self      )							->	Any:
         return asdict(self      )







def      UpperCAmelCase__   (      )	->						Optional[Any]:
     return (
         "<cls>",
         "<pad>",
         "<eos>",
         "<unk>",
         "L",
         "A",
         "G",
         "V",
         "S",
         "E",
         "R",
         "T",
         "I",
         "D",
         "P",
         "K",
         "Q",
         "N",
         "F",
         "Y",
         "M",
         "H",
         "W",
         "C",
         "X",
         "B",
         "U",
         "Z",
         "O",
         ".",
         "-",
         "<null_1>",
         "<mask>",
     )






