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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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