



'''simple docstring'''






import json
import os
import unittest

from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin

class 							a__(      lowerCamelCase__	,				unittest.TestCase			):
    lowercase__				=					XLMTokenizer
    lowercase__				=					False







    def     lowercase_ (   self				:						List[str]			):
      super().setUp()

      # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
      a		:      Dict       =  [
          'l',
          'o',
          'w',
          'e',
          'r',
          's',
          't',
          'i',
          'd',
          'n',
          'w</w>',
          'r</w>',
          't</w>',
          'lo',
          'low',
          'er</w>',
          'low</w>',
          'lowest</w>',
          'newer</w>',
          'wider</w>',
          '<unk>',
      ]
      a		:      List[Any]       =  dict(zip(__snake_case		,    range(len(__snake_case			)			)			)			)
      a		:      Any       =  ['l o 123', 'lo w 1456', 'e r</w> 1789', '']

      a		:      Tuple       =  os.path.join(self.tmpdirname		,    VOCAB_FILES_NAMES['vocab_file']			)
      a		:      Union[str, Any]       =  os.path.join(self.tmpdirname		,    VOCAB_FILES_NAMES['merges_file']			)
      with open(self.vocab_file		,    'w'			) as fp:
        fp.write(json.dumps(__snake_case			)			)
      with open(self.merges_file		,    'w'			) as fp:
        fp.write('\n'.join(__snake_case			)			)







    def     lowercase_ (   self				:						int		,    __snake_case				:						str			):
      a		:      Dict       =  'lower newer'
      a		:      Optional[int]       =  'lower newer'
      return input_text, output_text







    def     lowercase_ (   self				:						Optional[int]			):
      a		:      Dict       =  XLMTokenizer(self.vocab_file		,    self.merges_file			)

      a		:      Union[str, Any]       =  'lower'
      a		:      Any       =  ['low', 'er</w>']
      a		:      str       =  tokenizer.tokenize(__snake_case			)
      self.assertListEqual(__snake_case		,    __snake_case			)

      a		:      List[str]       =  tokens + ['<unk>']
      a		:      Optional[Any]       =  [14, 15, 20]
      self.assertListEqual(tokenizer.convert_tokens_to_ids(__snake_case			)		,    __snake_case			)







    @slow
    def     lowercase_ (   self				:						Any			):
      a		:      Optional[Any]       =  XLMTokenizer.from_pretrained('xlm-mlm-en-2048'			)

      a		:      Tuple       =  tokenizer.encode('sequence builders'		,    add_special_tokens=__snake_case			)
      a		:      Dict       =  tokenizer.encode('multi-sequence build'		,    add_special_tokens=__snake_case			)

      a		:      Any       =  tokenizer.build_inputs_with_special_tokens(__snake_case			)
      a		:      Tuple       =  tokenizer.build_inputs_with_special_tokens(__snake_case		,    __snake_case			)

      assert encoded_sentence == [0] + text + [1]
      assert encoded_pair == [0] + text + [1] + text_a + [1]




'''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    lowerCamelCase__ (		_A       ):
  return EnvironmentCommand()

class 							a__(      lowerCamelCase__			):







    @staticmethod
    def     lowercase_ (   __snake_case				:						ArgumentParser			):
      a		:      Tuple       =  parser.add_parser('env'			)
      download_parser.set_defaults(func=__snake_case			)







    def     lowercase_ (   self				:						List[str]			):
      a		:      str       =  huggingface_hub.__version__

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

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

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

        a		:      Tuple       =  transformers.__version__

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

        a		:      int       =  accelerate.__version__

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

        a		:      Optional[int]       =  xformers.__version__

      a		:      List[str]       =  {
          '`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(__snake_case			)			)

      return info







    @staticmethod
    def     lowercase_ (   __snake_case				:						Union[str, Any]			):
      return "\n".join([F"""- {prop}: {val}""" for prop, val in d.items()]			) + "\n"