



# 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


SCREAMING_SNAKE_CASE     				=						"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 )		->							Optional[Any]:
		UpperCAmelCase_						=				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
		UpperCAmelCase_						=				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_						=				{
		    "compute_environment": "LOCAL_MACHINE",
		    "mixed_precision": mixed_precision,
		}
		if torch.cuda.is_available():
				UpperCAmelCase_						=				torch.cuda.device_count()
				UpperCAmelCase_						=				num_gpus
				UpperCAmelCase_						=				False
				if num_gpus > 1:
						UpperCAmelCase_						=				"MULTI_GPU"
				else:
						UpperCAmelCase_						=				"NO"
		elif is_xpu_available() and use_xpu:
				UpperCAmelCase_						=				torch.xpu.device_count()
				UpperCAmelCase_						=				num_xpus
				UpperCAmelCase_						=				False
				if num_xpus > 1:
						UpperCAmelCase_						=				"MULTI_XPU"
				else:
						UpperCAmelCase_						=				"NO"
		elif is_npu_available():
				UpperCAmelCase_						=				torch.npu.device_count()
				UpperCAmelCase_						=				num_npus
				UpperCAmelCase_						=				False
				if num_npus > 1:
						UpperCAmelCase_						=				"MULTI_NPU"
				else:
						UpperCAmelCase_						=				"NO"
		else:
				UpperCAmelCase_						=				0
				UpperCAmelCase_						=				True
				UpperCAmelCase_						=				1
				UpperCAmelCase_						=				"NO"
		UpperCAmelCase_						=				ClusterConfig(**__SCREAMING_SNAKE_CASE )
		config.to_json_file(__SCREAMING_SNAKE_CASE )
		return path







def snake_case__  (			__SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE )		->							str:
		UpperCAmelCase_						=				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 )		->							Union[str, Any]:
		UpperCAmelCase_						=				write_basic_config(args.mixed_precision			,     args.save_location )
		if config_file:
				print(f'''accelerate configuration saved at {config_file}''' )






from typing import Optional, Union

import torch
from torch import nn

from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin



class 	lowerCamelCase      (						lowercase__,     lowercase__  ):







					'''simple docstring'''







					@register_to_config
					def __init__(			self    ,	lowerCAmelCase = 768    ,	):
							super().__init__()

							UpperCAmelCase_						=				nn.Parameter(torch.zeros(1    ,	lowerCAmelCase     )     )
							UpperCAmelCase_						=				nn.Parameter(torch.ones(1    ,	lowerCAmelCase     )     )



					def    A__		(			self    ,	lowerCAmelCase = None    ,	lowerCAmelCase = None    ,	):
							UpperCAmelCase_						=				nn.Parameter(self.mean.to(lowerCAmelCase     ).to(lowerCAmelCase     )     )
							UpperCAmelCase_						=				nn.Parameter(self.std.to(lowerCAmelCase     ).to(lowerCAmelCase     )     )
							return self



					def    A__		(			self    ,	lowerCAmelCase     ):
							UpperCAmelCase_						=				(embeds - self.mean) * 1.0 / self.std
							return embeds



					def    A__		(			self    ,	lowerCAmelCase     ):
							UpperCAmelCase_						=				(embeds * self.std) + self.mean
							return embeds

