
import warnings

from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor


__magic_name__            =  logging.get_logger(__name__)




class 					_SCREAMING_SNAKE_CASE  (      __UpperCamelCase ):
      def __init__(			self		,	*lowerCamelCase		,	**lowerCamelCase ):
          warnings.warn(
              "The class MobileViTFeatureExtractor is deprecated and will be removed in version 5 of Transformers."
              " Please use MobileViTImageProcessor instead."		,	lowerCamelCase		,	)
          super().__init__(*lowerCamelCase		,	**lowerCamelCase )








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__    (      __lowerCAmelCase							):
    return EnvironmentCommand()





def 	SCREAMING_SNAKE_CASE__    (      __lowerCAmelCase							):
    return EnvironmentCommand(args.accelerate_config_file							)





class 					_SCREAMING_SNAKE_CASE  (      __UpperCamelCase ):
      @staticmethod
      def A_			(			lowerCamelCase ):
          snake_case__						=				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 ):
          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__						=				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(lowerCamelCase ):
                  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(lowerCamelCase		,	lowerCamelCase )
                  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(lowerCamelCase ) )

          return info



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



