

"""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 						A							(  snake_case__=None     ):




			'''simple docstring'''


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

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

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

def 						A							(  snake_case__     ):




			'''simple docstring'''


			SCREAMING_SNAKE_CASE__										=   torch.__version__
			SCREAMING_SNAKE_CASE__										=   torch.cuda.is_available()
			SCREAMING_SNAKE_CASE__										=   is_xpu_available()
			SCREAMING_SNAKE_CASE__										=   is_npu_available()

			SCREAMING_SNAKE_CASE__										=   """Not found"""
			# Get the default from the config file.
			if args.config_file is not None or os.path.isfile(snake_case__     ):
						SCREAMING_SNAKE_CASE__										=   load_config_from_file(args.config_file     ).to_dict()

			SCREAMING_SNAKE_CASE__										=   {
			    """`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(snake_case__     ),
			    """PyTorch NPU available""": str(snake_case__     ),
			    """System RAM""": f"""{psutil.virtual_memory().total / 10_24 ** 3:.2f} GB""",
			}
			if pt_cuda_available:
						SCREAMING_SNAKE_CASE__										=   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:"""     )
			SCREAMING_SNAKE_CASE__										=   (
			    """\n""".join([f"""\t- {prop}: {val}""" for prop, val in accelerate_config.items()]     )
			    if isinstance(snake_case__		,					snake_case__     )
			    else f"""\t{accelerate_config}"""
			)
			print(snake_case__     )

			SCREAMING_SNAKE_CASE__										=   accelerate_config

			return info

def 						A							(  ):




			'''simple docstring'''


			SCREAMING_SNAKE_CASE__										=   env_command_parser()
			SCREAMING_SNAKE_CASE__										=   parser.parse_args()
			env_command(snake_case__     )
			return 0


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





"""simple docstring"""




def 						A							(  snake_case__		,					snake_case__     ):




			'''simple docstring'''


			SCREAMING_SNAKE_CASE__										=   len(snake_case__     )
			SCREAMING_SNAKE_CASE__										=   len(snake_case__     )
			SCREAMING_SNAKE_CASE__										=   (
			    first_str_length if first_str_length > second_str_length else second_str_length
			)
			SCREAMING_SNAKE_CASE__										=   []
			for char_count in range(snake_case__     ):
						if char_count < first_str_length:
									output_list.append(first_str[char_count]     )
						if char_count < second_str_length:
									output_list.append(second_str[char_count]     )
			return "".join(snake_case__     )


if __name__ == "__main__":
						print(alternative_string_arrange("AB", "XYZ"), end=" ")


