

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_							:     int="no"							,       UpperCAmelCase_							:     Dict = default_json_config_file							,       UpperCAmelCase_							:     Optional[Any] = False	)						->				List[Any]:




	'''simple docstring'''




	_UpperCamelCase   :		int			=						Path(__lowerCAmelCase	)
	path.parent.mkdir(parents=__lowerCAmelCase							,       exist_ok=__lowerCAmelCase	)
	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
	_UpperCamelCase   :		Dict			=						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}'''	)
	_UpperCamelCase   :		Union[str, Any]			=						{
	    """compute_environment""": """LOCAL_MACHINE""",
	    """mixed_precision""": mixed_precision,
	}
	if torch.cuda.is_available():
		_UpperCamelCase   :		str			=						torch.cuda.device_count()
		_UpperCamelCase   :		str			=						num_gpus
		_UpperCamelCase   :		str			=						False
		if num_gpus > 1:
			_UpperCamelCase   :		str			=						"""MULTI_GPU"""
		else:
			_UpperCamelCase   :		int			=						"""NO"""
	elif is_xpu_available() and use_xpu:
		_UpperCamelCase   :		Dict			=						torch.xpu.device_count()
		_UpperCamelCase   :		Optional[int]			=						num_xpus
		_UpperCamelCase   :		Optional[int]			=						False
		if num_xpus > 1:
			_UpperCamelCase   :		List[Any]			=						"""MULTI_XPU"""
		else:
			_UpperCamelCase   :		Dict			=						"""NO"""
	elif is_npu_available():
		_UpperCamelCase   :		Union[str, Any]			=						torch.npu.device_count()
		_UpperCamelCase   :		Any			=						num_npus
		_UpperCamelCase   :		Optional[int]			=						False
		if num_npus > 1:
			_UpperCamelCase   :		Union[str, Any]			=						"""MULTI_NPU"""
		else:
			_UpperCamelCase   :		int			=						"""NO"""
	else:
		_UpperCamelCase   :		List[Any]			=						0
		_UpperCamelCase   :		int			=						True
		_UpperCamelCase   :		Any			=						1
		_UpperCamelCase   :		Optional[Any]			=						"""NO"""
	_UpperCamelCase   :		Optional[int]			=						ClusterConfig(**__lowerCAmelCase	)
	config.to_json_file(__lowerCAmelCase	)
	return path






def 					lowerCamelCase_     (							UpperCAmelCase_							:     str							,       UpperCAmelCase_							:     int	)						->				Optional[Any]:




	'''simple docstring'''




	_UpperCamelCase   :		Any			=						parser.add_parser('default'							,       parents=__lowerCAmelCase							,       help=__lowerCAmelCase							,       formatter_class=__lowerCAmelCase	)
	parser.add_argument(
	    '--config_file'							,       default=__lowerCAmelCase							,       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=__lowerCAmelCase							,       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=__lowerCAmelCase	)
	return parser







def 					lowerCamelCase_     (							UpperCAmelCase_							:     int	)						->				str:




	'''simple docstring'''




	_UpperCamelCase   :		str			=						write_basic_config(args.mixed_precision							,       args.save_location	)
	if config_file:
		print(F'''accelerate configuration saved at {config_file}'''	)







from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase__								=		logging.get_logger(__name__)

lowerCAmelCase__								=		{
    """facebook/vit-mae-base""": """https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json""",
    # See all ViT MAE models at https://huggingface.co/models?filter=vit-mae
}







class 	lowercase    (				_lowercase							):


		"""simple docstring"""




		a__					       =  "vit_mae"


		def __init__(				self	,       __snake_case=7_68	,       __snake_case=12	,       __snake_case=12	,       __snake_case=30_72	,       __snake_case="gelu"	,       __snake_case=0.0	,       __snake_case=0.0	,       __snake_case=0.0_2	,       __snake_case=1e-12	,       __snake_case=2_24	,       __snake_case=16	,       __snake_case=3	,       __snake_case=True	,       __snake_case=16	,       __snake_case=5_12	,       __snake_case=8	,       __snake_case=20_48	,       __snake_case=0.7_5	,       __snake_case=False	,       **__snake_case	,       ):
			super().__init__(**__snake_case)

			_UpperCamelCase   :		Optional[int]			=						hidden_size
			_UpperCamelCase   :		Optional[int]			=						num_hidden_layers
			_UpperCamelCase   :		Tuple			=						num_attention_heads
			_UpperCamelCase   :		List[str]			=						intermediate_size
			_UpperCamelCase   :		str			=						hidden_act
			_UpperCamelCase   :		List[str]			=						hidden_dropout_prob
			_UpperCamelCase   :		List[Any]			=						attention_probs_dropout_prob
			_UpperCamelCase   :		str			=						initializer_range
			_UpperCamelCase   :		Any			=						layer_norm_eps
			_UpperCamelCase   :		int			=						image_size
			_UpperCamelCase   :		Any			=						patch_size
			_UpperCamelCase   :		List[Any]			=						num_channels
			_UpperCamelCase   :		Union[str, Any]			=						qkv_bias
			_UpperCamelCase   :		str			=						decoder_num_attention_heads
			_UpperCamelCase   :		Union[str, Any]			=						decoder_hidden_size
			_UpperCamelCase   :		Union[str, Any]			=						decoder_num_hidden_layers
			_UpperCamelCase   :		Any			=						decoder_intermediate_size
			_UpperCamelCase   :		int			=						mask_ratio
			_UpperCamelCase   :		List[Any]			=						norm_pix_loss




