





'''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 							UpperCAmelCase_    (	lowerCAmelCase_							):

				"""simple docstring"""






				return EnvironmentCommand()







def 							UpperCAmelCase_    (	lowerCAmelCase_							):

				"""simple docstring"""






				return EnvironmentCommand(args.accelerate_config_file							)


class       UpperCAmelCase (						_lowercase  ):




		@staticmethod
		def 				UpperCAmelCase__   (A__      :	ArgumentParser				)					-> Tuple:
						lowercase         = parser.add_parser("env"				)
						download_parser.set_defaults(func=A__				)
						download_parser.add_argument(
						    "--accelerate-config_file"							,			default=A__							,			help="The accelerate config file to use for the default values in the launching script."							,			)
						download_parser.set_defaults(func=A__				)




		def __init__(self      :	List[str]							,			A__      :	Union[str, Any]							,			*A__      :	Dict				)					-> None:
						lowercase         = accelerate_config_file




		def 				UpperCAmelCase__   (self      :	Tuple				)					-> Tuple:
						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(A__				):
														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(A__							,			A__				)
										    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(A__				)				)

						return info





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











'''simple docstring'''

import warnings

from ...utils import logging
from .image_processing_clip import CLIPImageProcessor


__lowerCamelCase : Union[str, Any]											=			logging.get_logger(__name__)

class       UpperCAmelCase (						_lowercase  ):




		def __init__(self      :	Tuple							,			*A__      :	Union[str, Any]							,			**A__      :	Optional[Any]				)					-> None:
						warnings.warn(
						    "The class CLIPFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"
						    " use CLIPImageProcessor instead."							,			A__							,			)
						super().__init__(*A__							,			**A__				)




