


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      UpperCAmelCase__		(UpperCamelCase_							):



     """simple docstring"""






     return EnvironmentCommand()
def      UpperCAmelCase__		(UpperCamelCase_							):



     """simple docstring"""






     return EnvironmentCommand(args.accelerate_config_file							)

class     A__   (       snake_case__      ):







    """simple docstring"""

    @staticmethod
    def 						a_     (			__snake_case       ):
         snake_case											=							parser.add_parser('''env'''       )
         download_parser.set_defaults(func=__snake_case       )
         download_parser.add_argument(
             '''--accelerate-config_file'''     ,   default=__snake_case     ,   help='''The accelerate config file to use for the default values in the launching script.'''     ,   )
         download_parser.set_defaults(func=__snake_case       )
    def __init__(			self     ,   __snake_case     ,   *__snake_case       ):
         snake_case											=							accelerate_config_file
    def 						a_     (			self       ):
         snake_case											=							"not installed"
         if is_safetensors_available():
              import safetensors

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

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

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

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

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

         snake_case											=							"not installed"
         snake_case											=							"NA"
         if is_torch_available():
              import torch

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

         snake_case											=							"not installed"
         snake_case											=							"NA"
         if is_tf_available():
              import tensorflow as tf

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

         snake_case											=							"not installed"
         snake_case											=							"not installed"
         snake_case											=							"not installed"
         snake_case											=							"NA"
         if is_flax_available():
              import flax
              import jax
              import jaxlib

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

         snake_case											=							{
             "`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(__snake_case       )       )

         return info




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












'''simple docstring'''
import warnings

from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline  # noqa F401


warnings.warn(
    'The `inpainting.py` script is outdated. Please use directly `from diffusers import'
    ' StableDiffusionInpaintPipeline` instead.'
)




