
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      _lowerCAmelCase (     unittest.TestCase	):
				_lowercase      		=EsmTokenizer




				def 					__a						( self					)    ->				Optional[int]:
							super().setUp()
							lowerCAmelCase_      =     tempfile.mkdtemp()
							# fmt: off
							lowerCAmelCase_      =     ["<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
							lowerCAmelCase_      =     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 					__a						( self    ,    **_UpperCamelCase					)    ->				List[PreTrainedTokenizerBase]:
							return [self.get_tokenizer(**lowercase__					)]




				def 					__a						( self    ,    **_UpperCamelCase					)    ->				PreTrainedTokenizer:
							return self.tokenizer_class.from_pretrained(self.tmpdirname    ,    **lowercase__					)




				def 					__a						( self					)    ->				Tuple:
							lowerCAmelCase_      =     self.tokenizer_class(self.vocab_file					)

							lowerCAmelCase_      =     tokenizer.tokenize("LAGVS"					)
							self.assertListEqual(lowercase__    ,    ["L", "A", "G", "V", "S"]					)
							self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase__					)    ,    [4, 5, 6, 7, 8]					)




				def 					__a						( self					)    ->				Union[str, Any]:
							lowerCAmelCase_      =     self.tokenizer_class(self.vocab_file					)

							lowerCAmelCase_      =     "LAGVS"
							self.assertListEqual(tokenizer.encode(lowercase__					)    ,    [0, 4, 5, 6, 7, 8, 2]					)




				def 					__a						( self					)    ->				str:
							lowerCAmelCase_      =     self.tokenizer_class(self.vocab_file					)

							lowerCAmelCase_      =     ["LAGVS", "WCB"]
							lowerCAmelCase_      =     tokenizer(lowercase__    ,    padding=lowercase__					)["input_ids"]

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




				def 					__a						( self					)    ->				List[str]:
							lowerCAmelCase_      =     self.tokenizer_class(self.vocab_file					)

							lowerCAmelCase_      =     ["LAGVS", "WCB"]
							lowerCAmelCase_      =     tokenizer(lowercase__    ,    padding=lowercase__					)["input_ids"]

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




				def 					__a						( self					)    ->				Optional[Any]:
							lowerCAmelCase_      =     self.get_tokenizers(fast=lowercase__					)
							for tokenizer in tokenizers:
										with self.subTest(f"""{tokenizer.__class__.__name__}"""					):
													lowerCAmelCase_      =     "<unk>"
													lowerCAmelCase_      =     "<mask>"

													lowerCAmelCase_      =     tokenizer.tokenize(lowercase__					)
													lowerCAmelCase_      =     tokenizer.tokenize(lowercase__					)

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





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_torch_available


_A       =					{
    "configuration_xlm_prophetnet": ["XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMProphetNetConfig"],
}

try:
			if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_A       =					["XLMProphetNetTokenizer"]

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_A       =					[
			    "XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST",
			    "XLMProphetNetDecoder",
			    "XLMProphetNetEncoder",
			    "XLMProphetNetForCausalLM",
			    "XLMProphetNetForConditionalGeneration",
			    "XLMProphetNetModel",
			    "XLMProphetNetPreTrainedModel",
			]


if TYPE_CHECKING:
			from .configuration_xlm_prophetnet import XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMProphetNetConfig

			try:
						if not is_sentencepiece_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_xlm_prophetnet import XLMProphetNetTokenizer

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_xlm_prophetnet import (
						    XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST,
						    XLMProphetNetDecoder,
						    XLMProphetNetEncoder,
						    XLMProphetNetForCausalLM,
						    XLMProphetNetForConditionalGeneration,
						    XLMProphetNetModel,
						    XLMProphetNetPreTrainedModel,
						)

else:
			import sys

			_A       =					_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



