






"""simple docstring"""


import platform
from argparse import ArgumentParser

import huggingface_hub

from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand




def       snake_case  (A_				:Optional[Any]				):







  '''simple docstring'''

  return EnvironmentCommand()






class 						snake_case  (  UpperCAmelCase	):





    @staticmethod
    def     lowerCamelCase__				(							A     : ArgumentParser      ):


      '''simple docstring'''




      a					:      Any    =       parser.add_parser('env'      )
      download_parser.set_defaults(func=A      )





    def     lowerCamelCase__				(							self     : str      ):


      '''simple docstring'''




      a					:      Union[str, Any]    =       huggingface_hub.__version__

      a					:      str    =       'not installed'
      a					:      Union[str, Any]    =       'NA'
      if is_torch_available():
        import torch

        a					:      Any    =       torch.__version__
        a					:      Optional[int]    =       torch.cuda.is_available()

      a					:      int    =       'not installed'
      if is_transformers_available():
        import transformers

        a					:      Union[str, Any]    =       transformers.__version__

      a					:      int    =       'not installed'
      if is_accelerate_available():
        import accelerate

        a					:      Tuple    =       accelerate.__version__

      a					:      Any    =       'not installed'
      if is_xformers_available():
        import xformers

        a					:      Dict    =       xformers.__version__

      a					:      Optional[Any]    =       {
          '`diffusers` version': version,
          'Platform': platform.platform(),
          'Python version': platform.python_version(),
          'PyTorch version (GPU?)': F'''{pt_version} ({pt_cuda_available})''',
          'Huggingface_hub version': hub_version,
          'Transformers version': transformers_version,
          'Accelerate version': accelerate_version,
          'xFormers version': xformers_version,
          'Using GPU in script?': '<fill in>',
          'Using distributed or parallel set-up in script?': '<fill in>',
      }

      print('\nCopy-and-paste the text below in your GitHub issue and FILL OUT the two last points.\n'      )
      print(self.format_dict(A      )      )

      return info





    @staticmethod
    def     lowerCamelCase__				(							A     : int      ):


      '''simple docstring'''




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












"""simple docstring"""


import os
import unittest

from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir

from ...test_tokenization_common import TokenizerTesterMixin


_UpperCamelCase    :   int   			=						get_tests_dir('fixtures/test_sentencepiece_bpe.model')






class 						snake_case  (  UpperCAmelCase       ,			unittest.TestCase	):
    __magic_name__   					=					BartphoTokenizer
    __magic_name__   					=					False
    __magic_name__   					=					True





    def     lowerCamelCase__				(							self     : List[Any]      ):


      '''simple docstring'''




      super().setUp()

      a					:      Any    =       ['▁This', '▁is', '▁a', '▁t', 'est']
      a					:      List[Any]    =       dict(zip(A    ,		range(len(A      )      )      )      )
      a					:      int    =       {'unk_token': '<unk>'}

      a					:      Tuple    =       os.path.join(self.tmpdirname    ,		VOCAB_FILES_NAMES['monolingual_vocab_file']      )
      with open(self.monolingual_vocab_file    ,		'w'    ,		encoding='utf-8'      ) as fp:
        for token in vocab_tokens:
          fp.write(F'''{token} {vocab_tokens[token]}\n'''      )

      a					:      Optional[int]    =       BartphoTokenizer(A    ,		self.monolingual_vocab_file    ,		**self.special_tokens_map      )
      tokenizer.save_pretrained(self.tmpdirname      )





    def     lowerCamelCase__				(							self     : Dict    ,		**A     : str      ):


      '''simple docstring'''




      kwargs.update(self.special_tokens_map      )
      return BartphoTokenizer.from_pretrained(self.tmpdirname    ,		**A      )





    def     lowerCamelCase__				(							self     : Optional[int]    ,		A     : Dict      ):


      '''simple docstring'''




      a					:      Tuple    =       'This is a là test'
      a					:      List[Any]    =       'This is a<unk><unk> test'
      return input_text, output_text





    def     lowerCamelCase__				(							self     : Optional[Any]      ):


      '''simple docstring'''




      a					:      Tuple    =       BartphoTokenizer(A    ,		self.monolingual_vocab_file    ,		**self.special_tokens_map      )
      a					:      int    =       'This is a là test'
      a					:      int    =       '▁This ▁is ▁a ▁l à ▁t est'.split()
      a					:      str    =       tokenizer.tokenize(A      )
      self.assertListEqual(A    ,		A      )

      a					:      Union[str, Any]    =       tokens + [tokenizer.unk_token]
      a					:      Dict    =       [4, 5, 6, 3, 3, 7, 8, 3]
      self.assertListEqual(tokenizer.convert_tokens_to_ids(A      )    ,		A      )




