



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       _lowercase				(  lowerCAmelCase, unittest.TestCase      ):





	"""simple docstring"""
	__A		      =				MPNetTokenizer
	__A		      =				MPNetTokenizerFast
	__A		      =				True
	__A		      =				True




	def 	UpperCamelCase_			(self						):
						"""simple docstring"""

						super().setUp()

						a   	=  [
						    "[UNK]",
						    "[CLS]",
						    "[SEP]",
						    "[PAD]",
						    "[MASK]",
						    "want",
						    "##want",
						    "##ed",
						    "wa",
						    "un",
						    "runn",
						    "##ing",
						    ",",
						    "low",
						    "lowest",
						]
						a   	=  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						,			lowerCamelCase_						):
						"""simple docstring"""

						a   	=  "UNwant\u00E9d,running"
						a   	=  "unwanted, running"
						return input_text, output_text




	def 	UpperCamelCase_			(self						):
						"""simple docstring"""

						a   	=  self.tokenizer_class(self.vocab_file						)

						a   	=  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 	UpperCamelCase_			(self						):
						"""simple docstring"""

						a   	=  self.tokenizer_class.from_pretrained("microsoft/mpnet-base"						)

						a   	=  tokenizer.encode("sequence builders"						,			add_special_tokens=lowerCamelCase_						)
						a   	=  tokenizer.encode("multi-sequence build"						,			add_special_tokens=lowerCamelCase_						)

						a   	=  tokenizer.build_inputs_with_special_tokens(lowerCamelCase_						)
						a   	=  tokenizer.build_inputs_with_special_tokens(lowerCamelCase_						,			lowerCamelCase_						)

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





import platform
from argparse import ArgumentParser

import huggingface_hub
import pandas
import pyarrow

from datasets import __version__ as version
from datasets.commands import BaseDatasetsCLICommand






def        a( A			:       Dict			)						->			Optional[int]:
					"""simple docstring"""





					return EnvironmentCommand()







class       _lowercase				(  lowerCAmelCase      ):





	"""simple docstring"""




	@staticmethod
	def 	UpperCamelCase_			(lowerCamelCase_						):
						"""simple docstring"""

						a   	=  parser.add_parser("env"						,			help="Print relevant system environment info."						)
						download_parser.set_defaults(func=lowerCamelCase_						)




	def 	UpperCamelCase_			(self						):
						"""simple docstring"""

						a   	=  {
						    "`datasets` version": version,
						    "Platform": platform.platform(),
						    "Python version": platform.python_version(),
						    "Huggingface_hub version": huggingface_hub.__version__,
						    "PyArrow version": pyarrow.__version__,
						    "Pandas version": pandas.__version__,
						}

						print("\nCopy-and-paste the text below in your GitHub issue.\n"						)
						print(self.format_dict(lowerCamelCase_						)						)

						return info




	@staticmethod
	def 	UpperCamelCase_			(lowerCamelCase_						):
						"""simple docstring"""

						return "\n".join([F'''- {prop}: {val}''' for prop, val in d.items()]						) + "\n"
