



# Copyright 2022 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.

import argparse
import os
import platform

import numpy as np
import psutil
import torch

from accelerate import __version__ as version
from accelerate.commands.config import default_config_file, load_config_from_file

from ..utils import is_npu_available, is_xpu_available






def      _A				(UpperCamelCase		:      str=None )  ->str:



			'''simple docstring'''







			if subparsers is not None:
						lowerCamelCase__ :      Any								=		subparsers.add_parser("""env""" )
			else:
						lowerCamelCase__ :      int								=		argparse.ArgumentParser("""Accelerate env command""" )

			parser.add_argument(
			    """--config_file"""      ,			default=UpperCamelCase      ,			help="""The config file to use for the default values in the launching script.""" )

			if subparsers is not None:
						parser.set_defaults(func=UpperCamelCase )
			return parser






def      _A				(UpperCamelCase		:      Dict )  ->List[Any]:



			'''simple docstring'''







			lowerCamelCase__ :      List[str]								=		torch.__version__
			lowerCamelCase__ :      List[Any]								=		torch.cuda.is_available()
			lowerCamelCase__ :      List[Any]								=		is_xpu_available()
			lowerCamelCase__ :      int								=		is_npu_available()

			lowerCamelCase__ :      Optional[int]								=		"""Not found"""
			# Get the default from the config file.
			if args.config_file is not None or os.path.isfile(UpperCamelCase ):
						lowerCamelCase__ :      List[str]								=		load_config_from_file(args.config_file ).to_dict()

			lowerCamelCase__ :      Optional[int]								=		{
			    """`Accelerate` version""": version,
			    """Platform""": platform.platform(),
			    """Python version""": platform.python_version(),
			    """Numpy version""": np.__version__,
			    """PyTorch version (GPU?)""": f"{pt_version} ({pt_cuda_available})",
			    """PyTorch XPU available""": str(UpperCamelCase ),
			    """PyTorch NPU available""": str(UpperCamelCase ),
			    """System RAM""": f"{psutil.virtual_memory().total / 1024 ** 3:.2f} GB",
			}
			if pt_cuda_available:
						lowerCamelCase__ :      str								=		torch.cuda.get_device_name()

			print("""\nCopy-and-paste the text below in your GitHub issue\n""" )
			print("""\n""".join([f"- {prop}: {val}" for prop, val in info.items()] ) )

			print("""- `Accelerate` default config:""" if args.config_file is None else """- `Accelerate` config passed:""" )
			lowerCamelCase__ :      Optional[int]								=		(
			    """\n""".join([f"\t- {prop}: {val}" for prop, val in accelerate_config.items()] )
			    if isinstance(UpperCamelCase      ,			UpperCamelCase )
			    else f"\t{accelerate_config}"
			)
			print(UpperCamelCase )

			lowerCamelCase__ :      Dict								=		accelerate_config

			return info






def      _A				()  ->int:



			'''simple docstring'''







			lowerCamelCase__ :      Any								=		env_command_parser()
			lowerCamelCase__ :      Union[str, Any]								=		parser.parse_args()
			env_command(UpperCamelCase )
			return 0


if __name__ == "__main__":
				raise SystemExit(main())








from math import factorial, pi






def      _A				(UpperCamelCase		:      float      ,			UpperCamelCase		:      int = 30 )  ->float:



			'''simple docstring'''







			if not isinstance(UpperCamelCase      ,			(int, float) ):
						raise ValueError("""maclaurin_sin() requires either an int or float for theta""" )

			if not isinstance(UpperCamelCase      ,			UpperCamelCase ) or accuracy <= 0:
						raise ValueError("""maclaurin_sin() requires a positive int for accuracy""" )

			lowerCamelCase__ :      Dict								=		float(UpperCamelCase )
			lowerCamelCase__ :      int								=		theta // (2 * pi)
			theta -= 2 * div * pi
			return sum(
			    (-1) ** r * theta ** (2 * r + 1) / factorial(2 * r + 1 ) for r in range(UpperCamelCase ) )






def      _A				(UpperCamelCase		:      float      ,			UpperCamelCase		:      int = 30 )  ->float:



			'''simple docstring'''







			if not isinstance(UpperCamelCase      ,			(int, float) ):
						raise ValueError("""maclaurin_cos() requires either an int or float for theta""" )

			if not isinstance(UpperCamelCase      ,			UpperCamelCase ) or accuracy <= 0:
						raise ValueError("""maclaurin_cos() requires a positive int for accuracy""" )

			lowerCamelCase__ :      int								=		float(UpperCamelCase )
			lowerCamelCase__ :      Optional[int]								=		theta // (2 * pi)
			theta -= 2 * div * pi
			return sum((-1) ** r * theta ** (2 * r) / factorial(2 * r ) for r in range(UpperCamelCase ) )


if __name__ == "__main__":
				import doctest

				doctest.testmod()

				print(maclaurin_sin(10))
				print(maclaurin_sin(-10))
				print(maclaurin_sin(10, 15))
				print(maclaurin_sin(-10, 15))

				print(maclaurin_cos(5))
				print(maclaurin_cos(-5))
				print(maclaurin_cos(10, 15))
				print(maclaurin_cos(-10, 15))



