



# 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


snake_case__					:     List[str]    		=   """Create a default config file for Accelerate with only a few flags set."""



def    snake_case_				(    _SCREAMING_SNAKE_CASE="no"  ,	_SCREAMING_SNAKE_CASE = default_json_config_file  ,	_SCREAMING_SNAKE_CASE = False   ):
	__lowercase		       =			Path(_SCREAMING_SNAKE_CASE   )
	path.parent.mkdir(parents=_SCREAMING_SNAKE_CASE  ,	exist_ok=_SCREAMING_SNAKE_CASE   )
	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
	__lowercase		       =			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}"""   )
	__lowercase		       =			{
	    "compute_environment": "LOCAL_MACHINE",
	    "mixed_precision": mixed_precision,
	}
	if torch.cuda.is_available():
		__lowercase		       =			torch.cuda.device_count()
		__lowercase		       =			num_gpus
		__lowercase		       =			False
		if num_gpus > 1:
			__lowercase		       =			"MULTI_GPU"
		else:
			__lowercase		       =			"NO"
	elif is_xpu_available() and use_xpu:
		__lowercase		       =			torch.xpu.device_count()
		__lowercase		       =			num_xpus
		__lowercase		       =			False
		if num_xpus > 1:
			__lowercase		       =			"MULTI_XPU"
		else:
			__lowercase		       =			"NO"
	elif is_npu_available():
		__lowercase		       =			torch.npu.device_count()
		__lowercase		       =			num_npus
		__lowercase		       =			False
		if num_npus > 1:
			__lowercase		       =			"MULTI_NPU"
		else:
			__lowercase		       =			"NO"
	else:
		__lowercase		       =			0
		__lowercase		       =			True
		__lowercase		       =			1
		__lowercase		       =			"NO"
	__lowercase		       =			ClusterConfig(**_SCREAMING_SNAKE_CASE   )
	config.to_json_file(_SCREAMING_SNAKE_CASE   )
	return path



def    snake_case_				(    _SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE   ):
	__lowercase		       =			parser.add_parser("default"  ,	parents=_SCREAMING_SNAKE_CASE  ,	help=_SCREAMING_SNAKE_CASE  ,	formatter_class=_SCREAMING_SNAKE_CASE   )
	parser.add_argument(
	    "--config_file"  ,	default=_SCREAMING_SNAKE_CASE  ,	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=_SCREAMING_SNAKE_CASE  ,	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=_SCREAMING_SNAKE_CASE   )
	return parser



def    snake_case_				(    _SCREAMING_SNAKE_CASE   ):
	__lowercase		       =			write_basic_config(args.mixed_precision  ,	args.save_location   )
	if config_file:
		print(F"""accelerate configuration saved at {config_file}"""   )








from ....utils import logging


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

class   _A   ( _lowercase	):


						'''simple docstring'''





						def __init__(	self	:							List[str]							,      lowerCamelCase	:							Any							,      lowerCamelCase	:							Dict=None							,      lowerCamelCase	:							Dict=2_048	):






							'''simple docstring'''



							__lowercase		       =			config.__dict__
							__lowercase		       =			modal_hidden_size
							if num_labels:
								__lowercase		       =			num_labels



