File size: 3,056 Bytes
82fea12 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 |
#!/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 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 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_npu_available = is_npu_available()
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()
info = {
"`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(pt_xpu_available),
"PyTorch NPU available": str(pt_npu_available),
"System RAM": f"{psutil.virtual_memory().total / 1024 ** 3:.2f} GB",
}
if pt_cuda_available:
info["GPU type"] = 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:")
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())
|