






"""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 						_SCREAMING_SNAKE_CASE (    __snake_case			:  Union[str, Any]    ):





  '''simple docstring'''





  return EnvironmentCommand()
def 						_SCREAMING_SNAKE_CASE (    __snake_case			:  Optional[int]    ):





  '''simple docstring'''





  return EnvironmentCommand(args.accelerate_config_file    )



class        a     (   a_	):







    @staticmethod
    def 			UpperCamelCase_      (			_lowerCamelCase       ):
      lowercase							    =       parser.add_parser('env'       )
      download_parser.set_defaults(func=_lowerCamelCase       )
      download_parser.add_argument(
          '--accelerate-config_file'							,		default=_lowerCamelCase							,		help='The accelerate config file to use for the default values in the launching script.'							,		)
      download_parser.set_defaults(func=_lowerCamelCase       )







    def __init__(			self							,		_lowerCamelCase							,		*_lowerCamelCase       ):
      lowercase							    =       accelerate_config_file







    def 			UpperCamelCase_      (			self       ):
      lowercase							    =       'not installed'
      if is_safetensors_available():
        import safetensors

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

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

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

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

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

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

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

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

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

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

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

      lowercase							    =       {
          '`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(_lowerCamelCase       )       )

      return info







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










"""simple docstring"""



import logging
import os
import sys
from pathlib import Path
from unittest.mock import patch

from parameterized import parameterized
from run_eval import run_generate
from run_eval_search import run_search

from transformers.testing_utils import CaptureStdout, TestCasePlus, slow
from utils import ROUGE_KEYS


logging.basicConfig(level=logging.DEBUG)
_UpperCamelCase		:  Tuple						=		logging.getLogger()
def 						_SCREAMING_SNAKE_CASE (    __snake_case			:  Path		,					__snake_case			:  list    ):





  '''simple docstring'''





  lowercase							    =       '\n'.join(__snake_case    )
  Path(__snake_case    ).open('w'    ).writelines(__snake_case    )


_UpperCamelCase		:  Union[str, Any]						=		'patrickvonplaten/t5-tiny-random'
_UpperCamelCase		:  Union[str, Any]						=		'sshleifer/bart-tiny-random'
_UpperCamelCase		:  Tuple						=		'sshleifer/tiny-mbart'

_UpperCamelCase		:  Union[str, Any]						=		logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)
logging.disable(logging.CRITICAL)  # remove noisy download output from tracebacks



class        a     (   a_	):







    def 			UpperCamelCase_      (			self							,		_lowerCamelCase       ):
      lowercase							    =       Path(self.get_auto_remove_tmp_dir()       ) / 'utest_input.source'
      lowercase							    =       input_file_name.parent / 'utest_output.txt'
      assert not output_file_name.exists()
      lowercase							    =       [' New York (CNN)When Liana Barrientos was 23 years old, she got married in Westchester County.']
      _dump_articles(_lowerCamelCase							,		_lowerCamelCase       )

      lowercase							    =       str(Path(self.get_auto_remove_tmp_dir()       ) / 'scores.json'       )
      lowercase							    =       'translation_en_to_de' if model == T5_TINY else 'summarization'
      lowercase							    =       F'\n            run_eval_search.py\n            {model}\n            {input_file_name}\n            {output_file_name}\n            --score_path {score_path}\n            --task {task}\n            --num_beams 2\n            --length_penalty 2.0\n            '.split()

      with patch.object(_lowerCamelCase							,		'argv'							,		_lowerCamelCase       ):
        run_generate()
        assert Path(_lowerCamelCase       ).exists()
        # os.remove(Path(output_file_name))







    def 			UpperCamelCase_      (			self       ):
      self.run_eval_tester(_lowerCamelCase       )







    @parameterized.expand([BART_TINY, MBART_TINY]       )
    @slow
    def 			UpperCamelCase_      (			self							,		_lowerCamelCase       ):
      self.run_eval_tester(_lowerCamelCase       )







    @parameterized.expand([T5_TINY, MBART_TINY]       )
    @slow
    def 			UpperCamelCase_      (			self							,		_lowerCamelCase       ):
      lowercase							    =       Path(self.get_auto_remove_tmp_dir()       ) / 'utest_input.source'
      lowercase							    =       input_file_name.parent / 'utest_output.txt'
      assert not output_file_name.exists()

      lowercase							    =       {
          'en': ['Machine learning is great, isn\'t it?', 'I like to eat bananas', 'Tomorrow is another great day!'],
          'de': [
              'Maschinelles Lernen ist großartig, oder?',
              'Ich esse gerne Bananen',
              'Morgen ist wieder ein toller Tag!',
          ],
      }

      lowercase							    =       Path(self.get_auto_remove_tmp_dir()       )
      lowercase							    =       str(tmp_dir / 'scores.json'       )
      lowercase							    =       str(tmp_dir / 'val.target'       )
      _dump_articles(_lowerCamelCase							,		text['en']       )
      _dump_articles(_lowerCamelCase							,		text['de']       )
      lowercase							    =       'translation_en_to_de' if model == T5_TINY else 'summarization'
      lowercase							    =       F'\n            run_eval_search.py\n            {model}\n            {str(_lowerCamelCase       )}\n            {str(_lowerCamelCase       )}\n            --score_path {score_path}\n            --reference_path {reference_path}\n            --task {task}\n            '.split()
      testargs.extend(['--search', 'num_beams=1:2 length_penalty=0.9:1.0']       )

      with patch.object(_lowerCamelCase							,		'argv'							,		_lowerCamelCase       ):
        with CaptureStdout() as cs:
          run_search()
        lowercase							    =       [' num_beams | length_penalty', model, 'Best score args']
        lowercase							    =       ['Info']
        if "translation" in task:
          expected_strings.append('bleu'       )
        else:
          expected_strings.extend(_lowerCamelCase       )
        for w in expected_strings:
          assert w in cs.out
        for w in un_expected_strings:
          assert w not in cs.out
        assert Path(_lowerCamelCase       ).exists()
        os.remove(Path(_lowerCamelCase       )       )


