






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





def 				lowercase__		(					lowerCamelCase,						lowerCamelCase       ):
				_SCREAMING_SNAKE_CASE   :		List[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 				lowercase__		(					lowerCamelCase       ):
				_SCREAMING_SNAKE_CASE   :		Dict       		=    write_basic_config(args.mixed_precision,						args.save_location       )
				if config_file:
								print(f"""accelerate configuration saved at {config_file}"""       )









"""simple docstring"""
from ...utils import is_torch_available, is_transformers_available


if is_transformers_available() and is_torch_available():
			from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline

