"""simple docstring"""


import os
import unittest

from transformers import MPNetTokenizerFast
from transformers.models.mpnet.tokenization_mpnet import VOCAB_FILES_NAMES, MPNetTokenizer
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin






@require_tokenizers
class    __UpperCAmelCase						(	__lowerCAmelCase      ,      unittest.TestCase	):
				A__      :   List[Any]  							=       MPNetTokenizer
				A__      :   Dict  							=       MPNetTokenizerFast
				A__      :   str  							=       True
				A__      :   Any  							=       True

				def 		_a	(      self      ):
										super().setUp()

										lowerCamelCase__					=[
										    "[UNK]",
										    "[CLS]",
										    "[SEP]",
										    "[PAD]",
										    "[MASK]",
										    "want",
										    "##want",
										    "##ed",
										    "wa",
										    "un",
										    "runn",
										    "##ing",
										    ",",
										    "low",
										    "lowest",
										]
										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	, _lowerCamelCase      ):
										lowerCamelCase__					="UNwant\u00E9d,running"
										lowerCamelCase__					="unwanted, running"
										return input_text, output_text

				def 		_a	(      self      ):
										lowerCamelCase__					=self.tokenizer_class(self.vocab_file      )

										lowerCamelCase__					=tokenizer.tokenize("UNwant\u00E9d,running"      )
										self.assertListEqual(_lowerCamelCase	, ["un", "##want", "##ed", ",", "runn", "##ing"]      )
										self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCamelCase      )	, [9, 6, 7, 12, 10, 11]      )






				@slow
				def 		_a	(      self      ):
										lowerCamelCase__					=self.tokenizer_class.from_pretrained("microsoft/mpnet-base"      )

										lowerCamelCase__					=tokenizer.encode("sequence builders"	, add_special_tokens=_lowerCamelCase      )
										lowerCamelCase__					=tokenizer.encode("multi-sequence build"	, add_special_tokens=_lowerCamelCase      )

										lowerCamelCase__					=tokenizer.build_inputs_with_special_tokens(_lowerCamelCase      )
										lowerCamelCase__					=tokenizer.build_inputs_with_special_tokens(_lowerCamelCase	, _lowerCamelCase      )

										assert encoded_sentence == [0] + text + [2]
										assert encoded_pair == [0] + text + [2] + [2] + text_a + [2]



"""simple docstring"""


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


a							=logging.get_logger(__name__)

a							={
    'microsoft/mpnet-base': 'https://huggingface.co/microsoft/mpnet-base/resolve/main/config.json',
}






class    __UpperCAmelCase						(	__lowerCAmelCase	):
				A__      :   Optional[int]  							=       '''mpnet'''

				def __init__(      self	, _lowerCamelCase=30527	, _lowerCamelCase=768	, _lowerCamelCase=12	, _lowerCamelCase=12	, _lowerCamelCase=3072	, _lowerCamelCase="gelu"	, _lowerCamelCase=0.1	, _lowerCamelCase=0.1	, _lowerCamelCase=512	, _lowerCamelCase=0.0_2	, _lowerCamelCase=1E-12	, _lowerCamelCase=32	, _lowerCamelCase=1	, _lowerCamelCase=0	, _lowerCamelCase=2	, **_lowerCamelCase	, ):
										super().__init__(pad_token_id=_lowerCamelCase	, bos_token_id=_lowerCamelCase	, eos_token_id=_lowerCamelCase	, **_lowerCamelCase      )

										lowerCamelCase__					=vocab_size
										lowerCamelCase__					=hidden_size
										lowerCamelCase__					=num_hidden_layers
										lowerCamelCase__					=num_attention_heads
										lowerCamelCase__					=hidden_act
										lowerCamelCase__					=intermediate_size
										lowerCamelCase__					=hidden_dropout_prob
										lowerCamelCase__					=attention_probs_dropout_prob
										lowerCamelCase__					=max_position_embeddings
										lowerCamelCase__					=initializer_range
										lowerCamelCase__					=layer_norm_eps
										lowerCamelCase__					=relative_attention_num_buckets


