





"""simple docstring"""




# 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       _SCREAMING_SNAKE_CASE		(	_lowercase						:    str=None					) ->Optional[Any]:






	'''simple docstring'''






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

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

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






def       _SCREAMING_SNAKE_CASE		(	_lowercase						:    int					) ->Dict:






	'''simple docstring'''






	a      :		Optional[Any]	=				torch.__version__
	a      :		Union[str, Any]	=				torch.cuda.is_available()
	a      :		Optional[Any]	=				is_xpu_available()
	a      :		List[Any]	=				is_npu_available()

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

	a      :		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(_lowercase					),
	    "PyTorch NPU available": str(_lowercase					),
	    "System RAM": F"""{psutil.virtual_memory().total / 1024 ** 3:.2f} GB""",
	}
	if pt_cuda_available:
		a      :		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:"					)
	a      :		List[Any]	=				(
	    "\n".join([F"""\t- {prop}: {val}""" for prop, val in accelerate_config.items()]					)
	    if isinstance(_lowercase    ,       _lowercase					)
	    else F"""\t{accelerate_config}"""
	)
	print(_lowercase					)

	a      :		List[Any]	=				accelerate_config

	return info






def       _SCREAMING_SNAKE_CASE		(	) ->int:






	'''simple docstring'''






	a      :		Optional[int]	=				env_command_parser()
	a      :		Tuple	=				parser.parse_args()
	env_command(_lowercase					)
	return 0


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









"""simple docstring"""




def       _SCREAMING_SNAKE_CASE		(	_lowercase						:    list					) ->int:






	'''simple docstring'''






	if not grid or not grid[0]:
		raise TypeError("The grid does not contain the appropriate information"					)

	for cell_n in range(1    ,       len(grid[0]					)					):
		grid[0][cell_n] += grid[0][cell_n - 1]
	a      :		Union[str, Any]	=				grid[0]

	for row_n in range(1    ,       len(_lowercase					)					):
		a      :		Optional[Any]	=				grid[row_n]
		a      :		Tuple	=				fill_row(_lowercase    ,       _lowercase					)
		a      :		List[Any]	=				grid[row_n]

	return grid[-1][-1]






def       _SCREAMING_SNAKE_CASE		(	_lowercase						:    list    ,       _lowercase						:    list					) ->list:






	'''simple docstring'''






	current_row[0] += row_above[0]
	for cell_n in range(1    ,       len(_lowercase					)					):
		current_row[cell_n] += min(current_row[cell_n - 1]    ,       row_above[cell_n]					)

	return current_row


if __name__ == "__main__":
		import doctest

		doctest.testmod()


