57 lines
1.9 KiB
Python
57 lines
1.9 KiB
Python
# Copyright The PyTorch Lightning team.
|
|
#
|
|
# 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.
|
|
"""
|
|
Runs either `.fit()` or `.test()` on a single node across multiple gpus.
|
|
"""
|
|
from argparse import ArgumentParser
|
|
|
|
from pytorch_lightning import Trainer, seed_everything
|
|
from tests.base import EvalModelTemplate
|
|
import os
|
|
import torch
|
|
|
|
|
|
def main():
|
|
seed_everything(1234)
|
|
parser = ArgumentParser(add_help=False)
|
|
parser = Trainer.add_argparse_args(parser)
|
|
parser.add_argument('--trainer_method', default='fit')
|
|
parser.add_argument('--tmpdir')
|
|
parser.set_defaults(gpus=2)
|
|
parser.set_defaults(distributed_backend="ddp")
|
|
args = parser.parse_args()
|
|
|
|
model = EvalModelTemplate()
|
|
trainer = Trainer.from_argparse_args(args)
|
|
|
|
result = {}
|
|
if args.trainer_method == 'fit':
|
|
trainer.fit(model)
|
|
result = {'status': 'complete', 'method': args.trainer_method, 'result': None}
|
|
if args.trainer_method == 'test':
|
|
result = trainer.test(model)
|
|
result = {'status': 'complete', 'method': args.trainer_method, 'result': result}
|
|
if args.trainer_method == 'fit_test':
|
|
trainer.fit(model)
|
|
result = trainer.test(model)
|
|
result = {'status': 'complete', 'method': args.trainer_method, 'result': result}
|
|
|
|
if len(result) > 0:
|
|
file_path = os.path.join(args.tmpdir, 'ddp.result')
|
|
torch.save(result, file_path)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
main()
|