Cannot re-initialize CUDA in forked subprocess
moose-in-australia opened this issue · comments
I am trying to run training for the end-to-end masked transformer using the ActivityNet data set. Currently I am running this on an AWS EC2 instance of type p2.xlarge, which has one GPU. I call the training script as follows:
CUDA_VISIBLE_DEVICES=0 python scripts/train.py --dist_url ./ss_model --cfgs_file cfgs/anet.yml --checkpoint_path ./checkpoint/ss_model --batch_size 14 --world_size 1 --cuda --sent_weight 0.25 --mask_weight 1.0 --gated_mask | tee log/ss_model-0
Unfortunately I run into the error below with regards to multiprocessing. So far I have been unable to debug it successfully. When adding the spawn method as indicated by the error messages, further errors occur. I would appreciate any help in figuring out what I'm doing wrong.
train.py:122: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details.
options_yaml = yaml.load(handle)
Namespace(alpha=0.95, attn_dropout=0.2, batch_size=14, beta=0.999, cap_dropout=0.2, cfgs_file='cfgs/anet.yml', checkpoint_path='./checkpoint/weird', cls_weight=1.0, cuda=True, d_hidden=2048, d_model=1024, dataset='anet', dataset_file='./data/anet/anet_annotations_trainval.json', densecap_references=['./data/anet/val_1.json', './data/anet/val_2.json'], dist_backend='gloo', dist_url='./weird', dur_file='./data/anet/anet_duration_frame.csv', enable_visdom=False, epsilon=1e-08, feature_root='./dataset', gated_mask=True, grad_norm=1, image_feat_size=3072, in_emb_dropout=0.1, kernel_list=[1, 2, 3, 4, 5, 7, 9, 11, 15, 21, 29, 41, 57, 71, 111, 161, 211, 251], learning_rate=0.1, load_train_samplelist=False, load_valid_samplelist=False, loss_alpha_r=2, losses_log_every=1, mask_weight=1.0, max_epochs=20, max_sentence_len=20, n_heads=8, n_layers=2, neg_thresh=0.3, num_workers=1, optim='sgd', patience_epoch=1, pos_thresh=0.7, reduce_factor=0.5, reg_weight=10, sample_prob=0, sampling_sec=0.5, save_checkpoint_every=1, save_train_samplelist=False, save_valid_samplelist=False, scst_weight=0.0, seed=213, sent_weight=0.25, slide_window_size=480, slide_window_stride=20, start_from='', stride_factor=50, train_data_folder=['training'], train_sample=20, train_samplelist_path='/z/home/luozhou/subsystem/densecap_vid/train_samplelist.pkl', val_data_folder=['validation'], valid_batch_size=64, valid_samplelist_path='/z/home/luozhou/subsystem/densecap_vid/valid_samplelist.pkl', vis_emb_dropout=0.1, world_size=1)
loading dataset
# of words in the vocab: 4563
# of sentences in training: 37421, # of sentences in validation: 17505
# of training videos: 10009
size of the sentence block variable (['training']): torch.Size([37415, 20])
Process ForkPoolWorker-1:
Traceback (most recent call last):
File "/home/ubuntu/miniconda3/envs/demo_ss2/lib/python3.6/multiprocessing/process.py", line 258, in _bootstrap
self.run()
File "/home/ubuntu/miniconda3/envs/demo_ss2/lib/python3.6/multiprocessing/process.py", line 93, in run
self._target(*self._args, **self._kwargs)
File "/home/ubuntu/miniconda3/envs/demo_ss2/lib/python3.6/multiprocessing/pool.py", line 108, in worker
task = get()
File "/home/ubuntu/miniconda3/envs/demo_ss2/lib/python3.6/multiprocessing/queues.py", line 337, in get
return _ForkingPickler.loads(res)
File "/home/ubuntu/miniconda3/envs/demo_ss2/lib/python3.6/site-packages/torch/multiprocessing/reductions.py", line 95, in rebuild_storage_cuda
torch.cuda._lazy_init()
File "/home/ubuntu/miniconda3/envs/demo_ss2/lib/python3.6/site-packages/torch/cuda/__init__.py", line 159, in _lazy_init
"Cannot re-initialize CUDA in forked subprocess. " + msg)
RuntimeError: Cannot re-initialize CUDA in forked subprocess. To use CUDA with multiprocessing, you must use the 'spawn' start method
Process ForkPoolWorker-2:
Traceback (most recent call last):
File "/home/ubuntu/miniconda3/envs/demo_ss2/lib/python3.6/multiprocessing/process.py", line 258, in _bootstrap
self.run()
File "/home/ubuntu/miniconda3/envs/demo_ss2/lib/python3.6/multiprocessing/process.py", line 93, in run
self._target(*self._args, **self._kwargs)
File "/home/ubuntu/miniconda3/envs/demo_ss2/lib/python3.6/multiprocessing/pool.py", line 108, in worker
task = get()
File "/home/ubuntu/miniconda3/envs/demo_ss2/lib/python3.6/multiprocessing/queues.py", line 337, in get
return _ForkingPickler.loads(res)
File "/home/ubuntu/miniconda3/envs/demo_ss2/lib/python3.6/site-packages/torch/multiprocessing/reductions.py", line 95, in rebuild_storage_cuda
torch.cuda._lazy_init()
File "/home/ubuntu/miniconda3/envs/demo_ss2/lib/python3.6/site-packages/torch/cuda/__init__.py", line 159, in _lazy_init
"Cannot re-initialize CUDA in forked subprocess. " + msg)
RuntimeError: Cannot re-initialize CUDA in forked subprocess. To use CUDA with multiprocessing, you must use the 'spawn' start method
Process ForkPoolWorker-3:
Process ForkPoolWorker-4:
Traceback (most recent call last):
File "/home/ubuntu/miniconda3/envs/demo_ss2/lib/python3.6/multiprocessing/process.py", line 258, in _bootstrap
self.run()
File "/home/ubuntu/miniconda3/envs/demo_ss2/lib/python3.6/multiprocessing/process.py", line 93, in run
self._target(*self._args, **self._kwargs)
File "/home/ubuntu/miniconda3/envs/demo_ss2/lib/python3.6/multiprocessing/pool.py", line 108, in worker
task = get()
File "/home/ubuntu/miniconda3/envs/demo_ss2/lib/python3.6/multiprocessing/queues.py", line 337, in get
return _ForkingPickler.loads(res)
File "/home/ubuntu/miniconda3/envs/demo_ss2/lib/python3.6/site-packages/torch/multiprocessing/reductions.py", line 95, in rebuild_storage_cuda
torch.cuda._lazy_init()
File "/home/ubuntu/miniconda3/envs/demo_ss2/lib/python3.6/site-packages/torch/cuda/__init__.py", line 159, in _lazy_init
"Cannot re-initialize CUDA in forked subprocess. " + msg)
RuntimeError: Cannot re-initialize CUDA in forked subprocess. To use CUDA with multiprocessing, you must use the 'spawn' start method
Traceback (most recent call last):
File "/home/ubuntu/miniconda3/envs/demo_ss2/lib/python3.6/multiprocessing/process.py", line 258, in _bootstrap
self.run()
File "/home/ubuntu/miniconda3/envs/demo_ss2/lib/python3.6/multiprocessing/process.py", line 93, in run
self._target(*self._args, **self._kwargs)
File "/home/ubuntu/miniconda3/envs/demo_ss2/lib/python3.6/multiprocessing/pool.py", line 108, in worker
task = get()
File "/home/ubuntu/miniconda3/envs/demo_ss2/lib/python3.6/multiprocessing/queues.py", line 337, in get
return _ForkingPickler.loads(res)
File "/home/ubuntu/miniconda3/envs/demo_ss2/lib/python3.6/site-packages/torch/multiprocessing/reductions.py", line 95, in rebuild_storage_cuda
torch.cuda._lazy_init()
File "/home/ubuntu/miniconda3/envs/demo_ss2/lib/python3.6/site-packages/torch/cuda/__init__.py", line 159, in _lazy_init
"Cannot re-initialize CUDA in forked subprocess. " + msg)
RuntimeError: Cannot re-initialize CUDA in forked subprocess. To use CUDA with multiprocessing, you must use the 'spawn' start method
THCudaCheck FAIL file=/opt/conda/conda-bld/pytorch_1525909934016/work/aten/src/THC/generic/THCStorage.c line=150 error=3 : initialization error
Process ForkPoolWorker-5:
Traceback (most recent call last):
File "/home/ubuntu/miniconda3/envs/demo_ss2/lib/python3.6/multiprocessing/process.py", line 258, in _bootstrap
self.run()
File "/home/ubuntu/miniconda3/envs/demo_ss2/lib/python3.6/multiprocessing/process.py", line 93, in run
self._target(*self._args, **self._kwargs)
File "/home/ubuntu/miniconda3/envs/demo_ss2/lib/python3.6/multiprocessing/pool.py", line 108, in worker
task = get()
File "/home/ubuntu/miniconda3/envs/demo_ss2/lib/python3.6/multiprocessing/queues.py", line 337, in get
return _ForkingPickler.loads(res)
File "/home/ubuntu/miniconda3/envs/demo_ss2/lib/python3.6/site-packages/torch/multiprocessing/reductions.py", line 94, in rebuild_storage_cuda
return storage._new_view(offset, view_size)
RuntimeError: cuda runtime error (3) : initialization error at /opt/conda/conda-bld/pytorch_1525909934016/work/aten/src/THC/generic/THCStorage.c:150
THCudaCheck FAIL file=/opt/conda/conda-bld/pytorch_1525909934016/work/aten/src/THC/generic/THCStorage.c line=150 error=3 : initialization error
@moose-in-australia you may want to refer to this issue: salesforce#11