





'''simple docstring'''






import unittest

from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin







@require_rjieba
@require_tokenizers
class 		UpperCAmelCase   (				lowercase_   ,     unittest.TestCase):


  """simple docstring"""







  lowerCAmelCase_					=				RoFormerTokenizer
  lowerCAmelCase_					=				RoFormerTokenizerFast
  lowerCAmelCase_					=				True
  lowerCAmelCase_					=				True


  def   UpperCamelCase__      (				self    :					int  )     ->						Union[str, Any]:
    super().setUp()


  def   UpperCamelCase__      (				self    :					Any							,	**UpperCamelCase__    :					Union[str, Any]  )     ->						Union[str, Any]:
    return self.tokenizer_class.from_pretrained('''junnyu/roformer_chinese_base'''							,	**UpperCamelCase__  )


  def   UpperCamelCase__      (				self    :					str							,	**UpperCamelCase__    :					Optional[int]  )     ->						Dict:
    return self.rust_tokenizer_class.from_pretrained('''junnyu/roformer_chinese_base'''							,	**UpperCamelCase__  )


  def   UpperCamelCase__      (				self    :					Optional[Any]  )     ->						List[str]:
    _UpperCamelCase       			='''永和服装饰品有限公司,今天天气非常好'''
    _UpperCamelCase       			='''永和 服装 饰品 有限公司 , 今 天 天 气 非常 好'''
    return input_text, output_text


  def   UpperCamelCase__      (				self    :					Tuple  )     ->						Optional[int]:
    _UpperCamelCase       			=self.get_tokenizer()
    _UpperCamelCase			,     _UpperCamelCase       			=self.get_chinese_input_output_texts()
    _UpperCamelCase       			=tokenizer.tokenize(UpperCamelCase__  )

    self.assertListEqual(UpperCamelCase__							,	output_text.split()  )

    _UpperCamelCase       			=tokens + [tokenizer.unk_token]
    _UpperCamelCase       			=[2_2943, 2_1332, 3_4431, 4_5904, 117, 306, 1231, 1231, 2653, 3_3994, 1266, 100]
    self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCamelCase__  )							,	UpperCamelCase__  )


  def   UpperCamelCase__      (				self    :					List[str]  )     ->						List[str]:
    _UpperCamelCase       			=self.get_rust_tokenizer()
    _UpperCamelCase			,     _UpperCamelCase       			=self.get_chinese_input_output_texts()
    _UpperCamelCase       			=tokenizer.tokenize(UpperCamelCase__  )
    self.assertListEqual(UpperCamelCase__							,	output_text.split()  )
    _UpperCamelCase       			=tokens + [tokenizer.unk_token]
    _UpperCamelCase       			=[2_2943, 2_1332, 3_4431, 4_5904, 117, 306, 1231, 1231, 2653, 3_3994, 1266, 100]
    self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCamelCase__  )							,	UpperCamelCase__  )


  def   UpperCamelCase__      (				self    :					Optional[int]  )     ->						Tuple:
    pass


  def   UpperCamelCase__      (				self    :					Any  )     ->						List[Any]:
    pass




  def   UpperCamelCase__      (				self    :					List[Any]  )     ->						str:
    pass













'''simple docstring'''






import importlib.util
import os
import platform
from argparse import ArgumentParser

import huggingface_hub

from .. import __version__ as version
from ..utils import (
    is_accelerate_available,
    is_flax_available,
    is_safetensors_available,
    is_tf_available,
    is_torch_available,
)
from . import BaseTransformersCLICommand


def 					_a   (__SCREAMING_SNAKE_CASE   ):


  """simple docstring"""

  return EnvironmentCommand()


def 					_a   (__SCREAMING_SNAKE_CASE   ):


  """simple docstring"""

  return EnvironmentCommand(args.accelerate_config_file   )







class 		UpperCAmelCase   (				lowercase_):


  """simple docstring"""







  @staticmethod
  def   UpperCamelCase__      (				UpperCamelCase__    :					ArgumentParser  )     ->						Union[str, Any]:
    _UpperCamelCase       			=parser.add_parser('''env'''  )
    download_parser.set_defaults(func=UpperCamelCase__  )
    download_parser.add_argument(
        '''--accelerate-config_file'''							,	default=UpperCamelCase__							,	help='''The accelerate config file to use for the default values in the launching script.'''							,	)
    download_parser.set_defaults(func=UpperCamelCase__  )


  def __init__(				self    :					Tuple							,	UpperCamelCase__    :					Dict							,	*UpperCamelCase__    :					str  )     ->						None:
    _UpperCamelCase       			=accelerate_config_file


  def   UpperCamelCase__      (				self    :					str  )     ->						int:
    _UpperCamelCase       			='''not installed'''
    if is_safetensors_available():
      import safetensors

      _UpperCamelCase       			=safetensors.__version__
    elif importlib.util.find_spec('''safetensors'''  ) is not None:
      import safetensors

      _UpperCamelCase       			=F'''{safetensors.__version__} but is ignored because of PyTorch version too old.'''

    _UpperCamelCase       			='''not installed'''
    _UpperCamelCase       			=_UpperCamelCase       			='''not found'''
    if is_accelerate_available():
      import accelerate
      from accelerate.commands.config import default_config_file, load_config_from_file

      _UpperCamelCase       			=accelerate.__version__
      # Get the default from the config file.
      if self._accelerate_config_file is not None or os.path.isfile(UpperCamelCase__  ):
        _UpperCamelCase       			=load_config_from_file(self._accelerate_config_file  ).to_dict()

      _UpperCamelCase       			=(
          '''\n'''.join([F'''\t- {prop}: {val}''' for prop, val in accelerate_config.items()]  )
          if isinstance(UpperCamelCase__							,	UpperCamelCase__  )
          else F'''\t{accelerate_config}'''
      )

    _UpperCamelCase       			='''not installed'''
    _UpperCamelCase       			='''NA'''
    if is_torch_available():
      import torch

      _UpperCamelCase       			=torch.__version__
      _UpperCamelCase       			=torch.cuda.is_available()

    _UpperCamelCase       			='''not installed'''
    _UpperCamelCase       			='''NA'''
    if is_tf_available():
      import tensorflow as tf

      _UpperCamelCase       			=tf.__version__
      try:
        # deprecated in v2.1
        _UpperCamelCase       			=tf.test.is_gpu_available()
      except AttributeError:
        # returns list of devices, convert to bool
        _UpperCamelCase       			=bool(tf.config.list_physical_devices('''GPU'''  )  )

    _UpperCamelCase       			='''not installed'''
    _UpperCamelCase       			='''not installed'''
    _UpperCamelCase       			='''not installed'''
    _UpperCamelCase       			='''NA'''
    if is_flax_available():
      import flax
      import jax
      import jaxlib

      _UpperCamelCase       			=flax.__version__
      _UpperCamelCase       			=jax.__version__
      _UpperCamelCase       			=jaxlib.__version__
      _UpperCamelCase       			=jax.lib.xla_bridge.get_backend().platform

    _UpperCamelCase       			={
        '''`transformers` version''': version,
        '''Platform''': platform.platform(),
        '''Python version''': platform.python_version(),
        '''Huggingface_hub version''': huggingface_hub.__version__,
        '''Safetensors version''': F'''{safetensors_version}''',
        '''Accelerate version''': F'''{accelerate_version}''',
        '''Accelerate config''': F'''{accelerate_config_str}''',
        '''PyTorch version (GPU?)''': F'''{pt_version} ({pt_cuda_available})''',
        '''Tensorflow version (GPU?)''': F'''{tf_version} ({tf_cuda_available})''',
        '''Flax version (CPU?/GPU?/TPU?)''': F'''{flax_version} ({jax_backend})''',
        '''Jax version''': F'''{jax_version}''',
        '''JaxLib version''': F'''{jaxlib_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(UpperCamelCase__  )  )

    return info




  @staticmethod
  def   UpperCamelCase__      (				UpperCamelCase__    :					Optional[Any]  )     ->						Dict:
    return "\n".join([F'''- {prop}: {val}''' for prop, val in d.items()]  ) + "\n"






