





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_      :		Tuple       ):






       """simple docstring"""





       return EnvironmentCommand()


def      a	(							SCREAMING_SNAKE_CASE_      :		List[Any]       ):






       """simple docstring"""





       return EnvironmentCommand(args.accelerate_config_file       )



class    UpperCAmelCase_	(							_a):
       '''simple docstring'''






       @staticmethod
       def  _lowercase   (     __SCREAMING_SNAKE_CASE						):




              """simple docstring"""




              UpperCamelCase    :	Any   	=		parser.add_parser('''env'''						)
              download_parser.set_defaults(func=_SCREAMING_SNAKE_CASE						)
              download_parser.add_argument(
                  '''--accelerate-config_file''' ,					default=_SCREAMING_SNAKE_CASE ,					help='''The accelerate config file to use for the default values in the launching script.''' ,					)
              download_parser.set_defaults(func=_SCREAMING_SNAKE_CASE						)






       def __init__(     self ,					__SCREAMING_SNAKE_CASE ,					*__SCREAMING_SNAKE_CASE						):




              """simple docstring"""




              UpperCamelCase    :	Dict   	=		accelerate_config_file






       def  _lowercase   (     self						):




              """simple docstring"""




              UpperCamelCase    :	Dict   	=		'''not installed'''
              if is_safetensors_available():
                     import safetensors

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

                     UpperCamelCase    :	List[str]   	=		f"""{safetensors.__version__} but is ignored because of PyTorch version too old."""

              UpperCamelCase    :	List[Any]   	=		'''not installed'''
              UpperCamelCase    :	Optional[Any]   	=		'''not found'''
              if is_accelerate_available():
                     import accelerate
                     from accelerate.commands.config import default_config_file, load_config_from_file

                     UpperCamelCase    :	Optional[Any]   	=		accelerate.__version__
                     # Get the default from the config file.
                     if self._accelerate_config_file is not None or os.path.isfile(_SCREAMING_SNAKE_CASE						):
                            UpperCamelCase    :	Optional[int]   	=		load_config_from_file(self._accelerate_config_file						).to_dict()

                     UpperCamelCase    :	List[str]   	=		(
                         '''\n'''.join([f"""\t- {prop}: {val}""" for prop, val in accelerate_config.items()]						)
                         if isinstance(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE						)
                         else f"""\t{accelerate_config}"""
                     )

              UpperCamelCase    :	str   	=		'''not installed'''
              UpperCamelCase    :	Optional[int]   	=		'''NA'''
              if is_torch_available():
                     import torch

                     UpperCamelCase    :	int   	=		torch.__version__
                     UpperCamelCase    :	str   	=		torch.cuda.is_available()

              UpperCamelCase    :	List[Any]   	=		'''not installed'''
              UpperCamelCase    :	Union[str, Any]   	=		'''NA'''
              if is_tf_available():
                     import tensorflow as tf

                     UpperCamelCase    :	Optional[Any]   	=		tf.__version__
                     try:
                            # deprecated in v2.1
                            UpperCamelCase    :	Union[str, Any]   	=		tf.test.is_gpu_available()
                     except AttributeError:
                            # returns list of devices, convert to bool
                            UpperCamelCase    :	Union[str, Any]   	=		bool(tf.config.list_physical_devices('''GPU'''						)						)

              UpperCamelCase    :	Any   	=		'''not installed'''
              UpperCamelCase    :	List[str]   	=		'''not installed'''
              UpperCamelCase    :	Dict   	=		'''not installed'''
              UpperCamelCase    :	List[str]   	=		'''NA'''
              if is_flax_available():
                     import flax
                     import jax
                     import jaxlib

                     UpperCamelCase    :	Optional[Any]   	=		flax.__version__
                     UpperCamelCase    :	Any   	=		jax.__version__
                     UpperCamelCase    :	Union[str, Any]   	=		jaxlib.__version__
                     UpperCamelCase    :	Union[str, Any]   	=		jax.lib.xla_bridge.get_backend().platform

              UpperCamelCase    :	int   	=		{
                  '''`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(_SCREAMING_SNAKE_CASE						)						)

              return info






       @staticmethod
       def  _lowercase   (     __SCREAMING_SNAKE_CASE						):




              """simple docstring"""




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





import re
from pathlib import Path
from unittest import TestCase

import pytest



@pytest.mark.integration
class    UpperCAmelCase_	(							_a):
       '''simple docstring'''






       def  _lowercase   (     self ,					__SCREAMING_SNAKE_CASE						):




              """simple docstring"""




              with open(__SCREAMING_SNAKE_CASE ,					encoding='''utf-8'''						) as input_file:
                     UpperCamelCase    :	str   	=		re.compile(R'''(?!.*\b(?:encoding|rb|w|wb|w+|wb+|ab|ab+)\b)(?<=\s)(open)\((.*)\)'''						)
                     UpperCamelCase    :	Optional[int]   	=		input_file.read()
                     UpperCamelCase    :	Union[str, Any]   	=		regexp.search(__SCREAMING_SNAKE_CASE						)

              return match






       def  _lowercase   (     self ,					__SCREAMING_SNAKE_CASE						):




              """simple docstring"""




              with open(__SCREAMING_SNAKE_CASE ,					encoding='''utf-8'''						) as input_file:
                     UpperCamelCase    :	Optional[int]   	=		re.compile(R'''#[^\r\n]*print\(|\"[^\r\n]*print\(|\"\"\".*?print\(.*?\"\"\"|(print\()''' ,					re.DOTALL						)
                     UpperCamelCase    :	Tuple   	=		input_file.read()
                     # use `re.finditer` to handle the case where the ignored groups would be matched first by `re.search`
                     UpperCamelCase    :	Dict   	=		regexp.finditer(__SCREAMING_SNAKE_CASE						)

              UpperCamelCase    :	int   	=		[match for match in matches if match is not None and match.group(1						) is not None]
              return matches[0] if matches else None






       def  _lowercase   (     self						):




              """simple docstring"""




              UpperCamelCase    :	int   	=		Path('''./datasets'''						)
              UpperCamelCase    :	Tuple   	=		list(dataset_paths.absolute().glob('''**/*.py'''						)						)

              for dataset in dataset_files:
                     if self._no_encoding_on_file_open(str(__SCREAMING_SNAKE_CASE						)						):
                            raise AssertionError(f"""open(...) must use utf-8 encoding in {dataset}"""						)






       def  _lowercase   (     self						):




              """simple docstring"""




              UpperCamelCase    :	Optional[int]   	=		Path('''./datasets'''						)
              UpperCamelCase    :	Tuple   	=		list(dataset_paths.absolute().glob('''**/*.py'''						)						)

              for dataset in dataset_files:
                     if self._no_print_statements(str(__SCREAMING_SNAKE_CASE						)						):
                            raise AssertionError(f"""print statement found in {dataset}. Use datasets.logger/logging instead."""						)

