131 lines
4.2 KiB
Python
131 lines
4.2 KiB
Python
#!/usr/bin/env python
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# Copyright 2022 The HuggingFace Team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import argparse
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import os
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import platform
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import subprocess
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import numpy as np
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import psutil
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import torch
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from accelerate import __version__ as version
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from accelerate.commands.config import default_config_file, load_config_from_file
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from ..utils import is_mlu_available, is_musa_available, is_npu_available, is_sdaa_available, is_xpu_available
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def env_command_parser(subparsers=None):
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if subparsers is not None:
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parser = subparsers.add_parser("env")
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else:
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parser = argparse.ArgumentParser("Accelerate env command")
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parser.add_argument(
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"--config_file", default=None, help="The config file to use for the default values in the launching script."
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)
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if subparsers is not None:
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parser.set_defaults(func=env_command)
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return parser
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def env_command(args):
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pt_version = torch.__version__
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pt_cuda_available = torch.cuda.is_available()
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pt_xpu_available = is_xpu_available()
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pt_mlu_available = is_mlu_available()
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pt_sdaa_available = is_sdaa_available()
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pt_musa_available = is_musa_available()
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pt_npu_available = is_npu_available()
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accelerator = "N/A"
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if pt_cuda_available:
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accelerator = "CUDA"
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elif pt_xpu_available:
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accelerator = "XPU"
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elif pt_mlu_available:
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accelerator = "MLU"
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elif pt_sdaa_available:
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accelerator = "SDAA"
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elif pt_musa_available:
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accelerator = "MUSA"
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elif pt_npu_available:
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accelerator = "NPU"
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accelerate_config = "Not found"
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# Get the default from the config file.
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if args.config_file is not None or os.path.isfile(default_config_file):
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accelerate_config = load_config_from_file(args.config_file).to_dict()
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# if we can run which, get it
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command = None
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bash_location = "Not found"
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if os.name == "nt":
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command = ["where", "accelerate"]
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elif os.name == "posix":
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command = ["which", "accelerate"]
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if command is not None:
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bash_location = subprocess.check_output(command, text=True, stderr=subprocess.STDOUT).strip()
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info = {
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"`Accelerate` version": version,
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"Platform": platform.platform(),
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"`accelerate` bash location": bash_location,
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"Python version": platform.python_version(),
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"Numpy version": np.__version__,
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"PyTorch version": f"{pt_version}",
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"PyTorch accelerator": accelerator,
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"System RAM": f"{psutil.virtual_memory().total / 1024**3:.2f} GB",
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}
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if pt_cuda_available:
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info["GPU type"] = torch.cuda.get_device_name()
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elif pt_xpu_available:
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info["XPU type"] = torch.xpu.get_device_name()
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elif pt_mlu_available:
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info["MLU type"] = torch.mlu.get_device_name()
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elif pt_sdaa_available:
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info["SDAA type"] = torch.sdaa.get_device_name()
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elif pt_musa_available:
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info["MUSA type"] = torch.musa.get_device_name()
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elif pt_npu_available:
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info["CANN version"] = torch.version.cann
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print("\nCopy-and-paste the text below in your GitHub issue\n")
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print("\n".join([f"- {prop}: {val}" for prop, val in info.items()]))
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print("- `Accelerate` default config:" if args.config_file is None else "- `Accelerate` config passed:")
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accelerate_config_str = (
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"\n".join([f"\t- {prop}: {val}" for prop, val in accelerate_config.items()])
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if isinstance(accelerate_config, dict)
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else f"\t{accelerate_config}"
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)
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print(accelerate_config_str)
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info["`Accelerate` configs"] = accelerate_config
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return info
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def main() -> int:
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parser = env_command_parser()
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args = parser.parse_args()
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env_command(args)
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return 0
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if __name__ == "__main__":
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raise SystemExit(main())
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