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- #!/usr/bin/env python
- # 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 subprocess
- 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_mlu_available, is_musa_available, is_npu_available, is_sdaa_available, is_xpu_available
- def env_command_parser(subparsers=None):
- if subparsers is not None:
- parser = subparsers.add_parser("env")
- else:
- parser = argparse.ArgumentParser("Accelerate env command")
- parser.add_argument(
- "--config_file", default=None, help="The config file to use for the default values in the launching script."
- )
- if subparsers is not None:
- parser.set_defaults(func=env_command)
- return parser
- def env_command(args):
- pt_version = torch.__version__
- pt_cuda_available = torch.cuda.is_available()
- pt_xpu_available = is_xpu_available()
- pt_mlu_available = is_mlu_available()
- pt_sdaa_available = is_sdaa_available()
- pt_musa_available = is_musa_available()
- pt_npu_available = is_npu_available()
- accelerator = "N/A"
- if pt_cuda_available:
- accelerator = "CUDA"
- elif pt_xpu_available:
- accelerator = "XPU"
- elif pt_mlu_available:
- accelerator = "MLU"
- elif pt_sdaa_available:
- accelerator = "SDAA"
- elif pt_musa_available:
- accelerator = "MUSA"
- elif pt_npu_available:
- accelerator = "NPU"
- accelerate_config = "Not found"
- # Get the default from the config file.
- if args.config_file is not None or os.path.isfile(default_config_file):
- accelerate_config = load_config_from_file(args.config_file).to_dict()
- # if we can run which, get it
- command = None
- bash_location = "Not found"
- if os.name == "nt":
- command = ["where", "accelerate"]
- elif os.name == "posix":
- command = ["which", "accelerate"]
- if command is not None:
- bash_location = subprocess.check_output(command, text=True, stderr=subprocess.STDOUT).strip()
- info = {
- "`Accelerate` version": version,
- "Platform": platform.platform(),
- "`accelerate` bash location": bash_location,
- "Python version": platform.python_version(),
- "Numpy version": np.__version__,
- "PyTorch version": f"{pt_version}",
- "PyTorch accelerator": accelerator,
- "System RAM": f"{psutil.virtual_memory().total / 1024**3:.2f} GB",
- }
- if pt_cuda_available:
- info["GPU type"] = torch.cuda.get_device_name()
- elif pt_xpu_available:
- info["XPU type"] = torch.xpu.get_device_name()
- elif pt_mlu_available:
- info["MLU type"] = torch.mlu.get_device_name()
- elif pt_sdaa_available:
- info["SDAA type"] = torch.sdaa.get_device_name()
- elif pt_musa_available:
- info["MUSA type"] = torch.musa.get_device_name()
- elif pt_npu_available:
- info["CANN version"] = torch.version.cann
- 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:")
- accelerate_config_str = (
- "\n".join([f"\t- {prop}: {val}" for prop, val in accelerate_config.items()])
- if isinstance(accelerate_config, dict)
- else f"\t{accelerate_config}"
- )
- print(accelerate_config_str)
- info["`Accelerate` configs"] = accelerate_config
- return info
- def main() -> int:
- parser = env_command_parser()
- args = parser.parse_args()
- env_command(args)
- return 0
- if __name__ == "__main__":
- raise SystemExit(main())
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