





import warnings

from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor


__lowercase	: List[Any]       =logging.get_logger(__name__)

class   A							(						__lowercase    ):



      def __init__(						self:    List[Any]		,	*_lowerCAmelCase:    Optional[Any]		,	**_lowerCAmelCase:    List[str]							)    ->     None:
         '''simple docstring'''

         warnings.warn(
             "The class GLPNFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"
             " use GLPNImageProcessor instead."		,	_lowerCAmelCase		,	)
         super().__init__(*_lowerCAmelCase		,	**_lowerCAmelCase							)








'''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from pathlib import Path

import torch

from ...utils import is_npu_available, is_xpu_available
from .config_args import ClusterConfig, default_json_config_file
from .config_utils import SubcommandHelpFormatter


lowerCAmelCase						=					"""Create a default config file for Accelerate with only a few flags set."""

def 					lowerCamelCase_ ( __UpperCamelCase					:       Union[str, Any]="no"							,    __UpperCamelCase					:       str = default_json_config_file							,    __UpperCamelCase					:       bool = False		)					->	Tuple:







     """simple docstring"""
     _A				=							Path(__UpperCamelCase		)
     path.parent.mkdir(parents=__UpperCamelCase							,    exist_ok=__UpperCamelCase		)
     if path.exists():
          print(
              F'Configuration already exists at {save_location}, will not override. Run `accelerate config` manually or pass a different `save_location`.'		)
          return False
     _A				=							mixed_precision.lower()
     if mixed_precision not in ["no", "fp16", "bf16", "fp8"]:
          raise ValueError(
              F'`mixed_precision` should be one of \'no\', \'fp16\', \'bf16\', or \'fp8\'. Received {mixed_precision}'		)
     _A				=							{
         'compute_environment': 'LOCAL_MACHINE',
         'mixed_precision': mixed_precision,
     }
     if torch.cuda.is_available():
          _A				=							torch.cuda.device_count()
          _A				=							num_gpus
          _A				=							False
          if num_gpus > 1:
               _A				=							'MULTI_GPU'
          else:
               _A				=							'NO'
     elif is_xpu_available() and use_xpu:
          _A				=							torch.xpu.device_count()
          _A				=							num_xpus
          _A				=							False
          if num_xpus > 1:
               _A				=							'MULTI_XPU'
          else:
               _A				=							'NO'
     elif is_npu_available():
          _A				=							torch.npu.device_count()
          _A				=							num_npus
          _A				=							False
          if num_npus > 1:
               _A				=							'MULTI_NPU'
          else:
               _A				=							'NO'
     else:
          _A				=							0
          _A				=							True
          _A				=							1
          _A				=							'NO'
     _A				=							ClusterConfig(**__UpperCamelCase		)
     config.to_json_file(__UpperCamelCase		)
     return path

def 					lowerCamelCase_ ( __UpperCamelCase					:       List[Any]							,    __UpperCamelCase					:       str		)					->	Any:







     """simple docstring"""
     _A				=							parser.add_parser('default'							,    parents=__UpperCamelCase							,    help=__UpperCamelCase							,    formatter_class=__UpperCamelCase		)
     parser.add_argument(
         '--config_file'							,    default=__UpperCamelCase							,    help=(
             'The path to use to store the config file. Will default to a file named default_config.yaml in the cache '
             'location, which is the content of the environment `HF_HOME` suffixed with \'accelerate\', or if you don\'t have '
             'such an environment variable, your cache directory (\'~/.cache\' or the content of `XDG_CACHE_HOME`) suffixed '
             'with \'huggingface\'.'
         )							,    dest='save_location'							,    )

     parser.add_argument(
         '--mixed_precision'							,    choices=['no', 'fp16', 'bf16']							,    type=__UpperCamelCase							,    help='Whether or not to use mixed precision training. '
         'Choose between FP16 and BF16 (bfloat16) training. '
         'BF16 training is only supported on Nvidia Ampere GPUs and PyTorch 1.10 or later.'							,    default='no'							,    )
     parser.set_defaults(func=__UpperCamelCase		)
     return parser

def 					lowerCamelCase_ ( __UpperCamelCase					:       Any		)					->	Union[str, Any]:







     """simple docstring"""
     _A				=							write_basic_config(args.mixed_precision							,    args.save_location		)
     if config_file:
          print(F'accelerate configuration saved at {config_file}'		)





