import os
import tempfile
import unittest
from typing import List

from transformers.models.esm.tokenization_esm import VOCAB_FILES_NAMES, EsmTokenizer
from transformers.testing_utils import require_tokenizers
from transformers.tokenization_utils import PreTrainedTokenizer
from transformers.tokenization_utils_base import PreTrainedTokenizerBase






@require_tokenizers
class 		a__						( unittest.TestCase ):
					A     	=							EsmTokenizer

					def     __UpperCamelCase       (   self				:	List[str]   ):







							"""simple docstring"""






							super().setUp()
							SCREAMING_SNAKE_CASE_  :		Tuple    				=   tempfile.mkdtemp()
							# fmt: off
							SCREAMING_SNAKE_CASE_  :		List[str]    				=   ["<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>"]  # noqa: E501
							# fmt: on
							SCREAMING_SNAKE_CASE_  :		Union[str, Any]    				=   os.path.join(self.tmpdirname,VOCAB_FILES_NAMES["vocab_file"]   )
							with open(self.vocab_file,"w",encoding="utf-8"   ) as vocab_writer:
									vocab_writer.write("".join([x + "\n" for x in vocab_tokens]   )   )

					def     __UpperCamelCase       (   self				:	Tuple,**_A				:	str   ):







							"""simple docstring"""






							return [self.get_tokenizer(**_A   )]

					def     __UpperCamelCase       (   self				:	List[str],**_A				:	List[str]   ):







							"""simple docstring"""






							return self.tokenizer_class.from_pretrained(self.tmpdirname,**_A   )

					def     __UpperCamelCase       (   self				:	str   ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		Optional[int]    				=   self.tokenizer_class(self.vocab_file   )

							SCREAMING_SNAKE_CASE_  :		List[Any]    				=   tokenizer.tokenize("LAGVS"   )
							self.assertListEqual(_A,["L", "A", "G", "V", "S"]   )
							self.assertListEqual(tokenizer.convert_tokens_to_ids(_A   ),[4, 5, 6, 7, 8]   )

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







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		Any    				=   self.tokenizer_class(self.vocab_file   )

							SCREAMING_SNAKE_CASE_  :		Dict    				=   "LAGVS"
							self.assertListEqual(tokenizer.encode(_A   ),[0, 4, 5, 6, 7, 8, 2]   )

					def     __UpperCamelCase       (   self				:	Dict   ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		Tuple    				=   self.tokenizer_class(self.vocab_file   )

							SCREAMING_SNAKE_CASE_  :		List[str]    				=   ["LAGVS", "WCB"]
							SCREAMING_SNAKE_CASE_  :		Union[str, Any]    				=   tokenizer(_A,padding=_A   )["input_ids"]

							self.assertListEqual(_A,[[0, 4, 5, 6, 7, 8, 2], [0, 22, 23, 25, 2]]   )

					def     __UpperCamelCase       (   self				:	Any   ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		Union[str, Any]    				=   self.tokenizer_class(self.vocab_file   )

							SCREAMING_SNAKE_CASE_  :		str    				=   ["LAGVS", "WCB"]
							SCREAMING_SNAKE_CASE_  :		Optional[Any]    				=   tokenizer(_A,padding=_A   )["input_ids"]

							self.assertListEqual(_A,[[0, 4, 5, 6, 7, 8, 2], [0, 22, 23, 25, 2, 1, 1]]   )






					def     __UpperCamelCase       (   self				:	Tuple   ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		List[str]    				=   self.get_tokenizers(fast=_A   )
							for tokenizer in tokenizers:
									with self.subTest(F'{tokenizer.__class__.__name__}'   ):
											SCREAMING_SNAKE_CASE_  :		Optional[Any]    				=   "<unk>"
											SCREAMING_SNAKE_CASE_  :		List[str]    				=   "<mask>"

											SCREAMING_SNAKE_CASE_  :		str    				=   tokenizer.tokenize(_A   )
											SCREAMING_SNAKE_CASE_  :		Tuple    				=   tokenizer.tokenize(_A   )

											self.assertEqual(len(_A   ),1   )
											self.assertEqual(len(_A   ),1   )
											self.assertEqual(token_a[0],_A   )
											self.assertEqual(token_a[0],_A   )

from ..utils import DummyObject, requires_backends






class 		a__						( metaclass=A__ ):
					A     	=							['tensorflow_text']

					def __init__(   self				:	List[str],*_A				:	Optional[Any],**_A				:	int   ):







							"""simple docstring"""






							requires_backends(self,["tensorflow_text"]   )
