train error

[nuist-xinyu]

Traceback (most recent call last):
File "train.py", line 203, in
train(training_dbs, validation_db, args.start_iter)
File "train.py", line 138, in train
training_loss, focal_loss, pull_loss, push_loss, regr_loss = nnet.train(**training)
File "/home/xinyu/CenterNet-master/nnet/py_factory.py", line 82, in train
loss_kp = self.network(xs, ys)
File "/home/xinyu/anaconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 477, in call
result = self.forward(*input, kwargs)
File "/home/xinyu/CenterNet-master/models/py_utils/data_parallel.py", line 66, in forward
inputs, kwargs = self.scatter(inputs, kwargs, self.device_ids, self.chunk_sizes)
File "/home/xinyu/CenterNet-master/models/py_utils/data_parallel.py", line 77, in scatter
return scatter_kwargs(inputs, kwargs, device_ids, dim=self.dim, chunk_sizes=self.chunk_sizes)
File "/home/xinyu/CenterNet-master/models/py_utils/scatter_gather.py", line 30, in scatter_kwargs
inputs = scatter(inputs, target_gpus, dim, chunk_sizes) if inputs else []
File "/home/xinyu/CenterNet-master/models/py_utils/scatter_gather.py", line 25, in scatter
return scatter_map(inputs)
File "/home/xinyu/CenterNet-master/models/py_utils/scatter_gather.py", line 18, in scatter_map
return list(zip(map(scatter_map, obj)))
File "/home/xinyu/CenterNet-master/models/py_utils/scatter_gather.py", line 20, in scatter_map
return list(map(list, zip(map(scatter_map, obj))))
File "/home/xinyu/CenterNet-master/models/py_utils/scatter_gather.py", line 15, in scatter_map
return Scatter.apply(target_gpus, chunk_sizes, dim, obj)
File "/home/xinyu/anaconda3/lib/python3.6/site-packages/torch/nn/parallel/_functions.py", line 87, in forward
outputs = comm.scatter(input, ctx.target_gpus, ctx.chunk_sizes, ctx.dim, streams)
File "/home/xinyu/anaconda3/lib/python3.6/site-packages/torch/cuda/comm.py", line 142, in scatter
return tuple(torch._C._scatter(tensor, devices, chunk_sizes, dim, streams))
RuntimeError: CUDA error (10): invalid device ordinal (check_status at /opt/conda/conda-bld/pytorch_1532502421238/work/aten/src/ATen/cuda/detail/CUDAHooks.cpp:36)
frame #0: torch::cuda::scatter(at::Tensor const&, at::ArrayRef, at::optional<std::vector<long, std::allocator > > const&, long, at::optional<std::vector<CUDAStreamInternals, std::allocator<CUDAStreamInternals> > > const&) + 0x4e1 (0x7fac77038871 in /home/xinyu/anaconda3/lib/python3.6/site-packages/torch/_C.cpython-36m-x86_64-linux-gnu.so)
frame #1: + 0xc42a0b (0x7fac77040a0b in /home/xinyu/anaconda3/lib/python3.6/site-packages/torch/_C.cpython-36m-x86_64-linux-gnu.so)
frame #2: + 0x38a5cb (0x7fac767885cb in /home/xinyu/anaconda3/lib/python3.6/site-packages/torch/_C.cpython-36m-x86_64-linux-gnu.so)

frame #13: THPFunction_apply(_object, _object) + 0x38f (0x7fac76b66a2f in /home/xinyu/anaconda3/lib/python3.6/site-packages/torch/_C.cpython-36m-x86_64-linux-gnu.so)

[nuist-xinyu]

@Duankaiwen 谢谢小哥哥

[Duankaiwen]

Can I see your full log?

[nuist-xinyu]

loading all datasets...
using 4 threads
loading from cache file: cache/coco_trainval2014.pkl
No cache file found...
loading annotations into memory...
Done (t=25.19s)
creating index...
index created!
118287it [01:18, 1509.02it/s]
loading annotations into memory...
Done (t=20.50s)
creating index...
index created!
loading from cache file: cache/coco_trainval2014.pkl
loading annotations into memory...
Done (t=18.08s)
creating index...
index created!
loading from cache file: cache/coco_trainval2014.pkl
loading annotations into memory...
Done (t=20.29s)
creating index...
index created!
loading from cache file: cache/coco_trainval2014.pkl
loading annotations into memory...
Done (t=23.57s)
creating index...
index created!
loading from cache file: cache/coco_minival2014.pkl
No cache file found...
loading annotations into memory...
Done (t=1.26s)
creating index...
index created!
5000it [00:03, 1478.28it/s]
loading annotations into memory...
Done (t=0.61s)
creating index...
index created!
system config...
{'batch_size': 48,
'cache_dir': 'cache',
'chunk_sizes': [6, 6, 6, 6, 6, 6, 6, 6],
'config_dir': 'config',
'data_dir': './data',
'data_rng': <mtrand.RandomState object at 0x7fac46fc3870>,
'dataset': 'MSCOCO',
'decay_rate': 10,
'display': 5,
'learning_rate': 0.00025,
'max_iter': 480000,
'nnet_rng': <mtrand.RandomState object at 0x7fac46fc38b8>,
'opt_algo': 'adam',
'prefetch_size': 6,
'pretrain': None,
'result_dir': 'results',
'sampling_function': 'kp_detection',
'snapshot': 5000,
'snapshot_name': 'CenterNet-104',
'stepsize': 450000,
'test_split': 'testdev',
'train_split': 'trainval',
'val_iter': 500,
'val_split': 'minival',
'weight_decay': False,
'weight_decay_rate': 1e-05,
'weight_decay_type': 'l2'}
db config...
{'ae_threshold': 0.5,
'border': 128,
'categories': 80,
'data_aug': True,
'gaussian_bump': True,
'gaussian_iou': 0.7,
'gaussian_radius': -1,
'input_size': [511, 511],
'kp_categories': 1,
'lighting': True,
'max_per_image': 100,
'merge_bbox': False,
'nms_algorithm': 'exp_soft_nms',
'nms_kernel': 3,
'nms_threshold': 0.5,
'output_sizes': [[128, 128]],
'rand_color': True,
'rand_crop': True,
'rand_pushes': False,
'rand_samples': False,
'rand_scale_max': 1.4,
'rand_scale_min': 0.6,
'rand_scale_step': 0.1,
'rand_scales': array([0.6, 0.7, 0.8, 0.9, 1. , 1.1, 1.2, 1.3]),
'special_crop': False,
'test_scales': [1],
'top_k': 70,
'weight_exp': 8}
len of db: 118287
start prefetching data...
start prefetching data...
shuffling indices...
shuffling indices...
start prefetching data...
shuffling indices...
start prefetching data...
shuffling indices...
building model...
module_file: models.CenterNet-104
start prefetching data...
shuffling indices...
total parameters: 210062960
setting learning rate to: 0.00025
training start...
0%| | 0/480000 [00:00<?, ?it/s]Traceback (most recent call last):
File "train.py", line 203, in
train(training_dbs, validation_db, args.start_iter)
File "train.py", line 138, in train
training_loss, focal_loss, pull_loss, push_loss, regr_loss = nnet.train(**training)
File "/home/xinyu/CenterNet-master/nnet/py_factory.py", line 82, in train
loss_kp = self.network(xs, ys)
File "/home/xinyu/anaconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 477, in call
result = self.forward(*input, kwargs)
File "/home/xinyu/CenterNet-master/models/py_utils/data_parallel.py", line 66, in forward
inputs, kwargs = self.scatter(inputs, kwargs, self.device_ids, self.chunk_sizes)
File "/home/xinyu/CenterNet-master/models/py_utils/data_parallel.py", line 77, in scatter
return scatter_kwargs(inputs, kwargs, device_ids, dim=self.dim, chunk_sizes=self.chunk_sizes)
File "/home/xinyu/CenterNet-master/models/py_utils/scatter_gather.py", line 30, in scatter_kwargs
inputs = scatter(inputs, target_gpus, dim, chunk_sizes) if inputs else []
File "/home/xinyu/CenterNet-master/models/py_utils/scatter_gather.py", line 25, in scatter
return scatter_map(inputs)
File "/home/xinyu/CenterNet-master/models/py_utils/scatter_gather.py", line 18, in scatter_map
return list(zip(map(scatter_map, obj)))
File "/home/xinyu/CenterNet-master/models/py_utils/scatter_gather.py", line 20, in scatter_map
return list(map(list, zip(map(scatter_map, obj))))
File "/home/xinyu/CenterNet-master/models/py_utils/scatter_gather.py", line 15, in scatter_map
return Scatter.apply(target_gpus, chunk_sizes, dim, obj)
File "/home/xinyu/anaconda3/lib/python3.6/site-packages/torch/nn/parallel/_functions.py", line 87, in forward
outputs = comm.scatter(input, ctx.target_gpus, ctx.chunk_sizes, ctx.dim, streams)
File "/home/xinyu/anaconda3/lib/python3.6/site-packages/torch/cuda/comm.py", line 142, in scatter
return tuple(torch._C._scatter(tensor, devices, chunk_sizes, dim, streams))
RuntimeError: CUDA error (10): invalid device ordinal (check_status at /opt/conda/conda-bld/pytorch_1532502421238/work/aten/src/ATen/cuda/detail/CUDAHooks.cpp:36)
frame #0: torch::cuda::scatter(at::Tensor const&, at::ArrayRef, at::optional<std::vector<long, std::allocator > > const&, long, at::optional<std::vector<CUDAStreamInternals, std::allocator<CUDAStreamInternals> > > const&) + 0x4e1 (0x7fac77038871 in /home/xinyu/anaconda3/lib/python3.6/site-packages/torch/_C.cpython-36m-x86_64-linux-gnu.so)
frame #1: + 0xc42a0b (0x7fac77040a0b in /home/xinyu/anaconda3/lib/python3.6/site-packages/torch/_C.cpython-36m-x86_64-linux-gnu.so)
frame #2: + 0x38a5cb (0x7fac767885cb in /home/xinyu/anaconda3/lib/python3.6/site-packages/torch/_C.cpython-36m-x86_64-linux-gnu.so)

frame #13: THPFunction_apply(_object, _object) + 0x38f (0x7fac76b66a2f in /home/xinyu/anaconda3/lib/python3.6/site-packages/torch/_C.cpython-36m-x86_64-linux-gnu.so)

[Duankaiwen]

How many GPUs do you have?

[nuist-xinyu]

i have put the val into the training set as you said,but this erro occurred
thank you help me @Duankaiwen

[nuist-xinyu]

16G

[Duankaiwen]

How many GPUs, not GPU memory

[nuist-xinyu]

sorrysorry 8g

[nuist-xinyu]

only one ，2070

[Duankaiwen]

Modify 'batch_size' to 3 and 'chunk_sizes' to [3] in config/CenterNet-104.json. If out of memory, then modify 'batch_size' to 2 and 'chunk_sizes' to [2]

[nuist-xinyu]

thank you

[nuist-xinyu]

best wish for you
i have try it

[nuist-xinyu]

Traceback (most recent call last):
File "train.py", line 203, in
train(training_dbs, validation_db, args.start_iter)
File "train.py", line 138, in train
training_loss, focal_loss, pull_loss, push_loss, regr_loss = nnet.train(**training)
File "/home/xinyu/CenterNet-master/nnet/py_factory.py", line 82, in train
loss_kp = self.network(xs, ys)
File "/home/xinyu/anaconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 477, in call
result = self.forward(*input, **kwargs)
File "/home/xinyu/CenterNet-master/models/py_utils/data_parallel.py", line 66, in forward
inputs, kwargs = self.scatter(inputs, kwargs, self.device_ids, self.chunk_sizes)
File "/home/xinyu/CenterNet-master/models/py_utils/data_parallel.py", line 77, in scatter
return scatter_kwargs(inputs, kwargs, device_ids, dim=self.dim, chunk_sizes=self.chunk_sizes)
File "/home/xinyu/CenterNet-master/models/py_utils/scatter_gather.py", line 30, in scatter_kwargs
inputs = scatter(inputs, target_gpus, dim, chunk_sizes) if inputs else []
File "/home/xinyu/CenterNet-master/models/py_utils/scatter_gather.py", line 25, in scatter
return scatter_map(inputs)
File "/home/xinyu/CenterNet-master/models/py_utils/scatter_gather.py", line 18, in scatter_map
return list(zip(map(scatter_map, obj)))
File "/home/xinyu/CenterNet-master/models/py_utils/scatter_gather.py", line 20, in scatter_map
return list(map(list, zip(map(scatter_map, obj))))
File "/home/xinyu/CenterNet-master/models/py_utils/scatter_gather.py", line 15, in scatter_map
return Scatter.apply(target_gpus, chunk_sizes, dim, obj)
File "/home/xinyu/anaconda3/lib/python3.6/site-packages/torch/nn/parallel/_functions.py", line 87, in forward
outputs = comm.scatter(input, ctx.target_gpus, ctx.chunk_sizes, ctx.dim, streams)
File "/home/xinyu/anaconda3/lib/python3.6/site-packages/torch/cuda/comm.py", line 142, in scatter
return tuple(torch._C._scatter(tensor, devices, chunk_sizes, dim, streams))
RuntimeError: given chunk sizes don't sum up to the tensor's size (sum(chunk_sizes) == 16, but expected 2) (scatter at torch/csrc/cuda/comm.cpp:135)
frame #0: + 0xc42a0b (0x7f94eb489a0b in /home/xinyu/anaconda3/lib/python3.6/site-packages/torch/_C.cpython-36m-x86_64-linux-gnu.so)
frame #1: + 0x38a5cb (0x7f94eabd15cb in /home/xinyu/anaconda3/lib/python3.6/site-packages/torch/_C.cpython-36m-x86_64-linux-gnu.so)

frame #12: THPFunction_apply(_object, _object) + 0x38f (0x7f94eafafa2f in /home/xinyu/anaconda3/lib/python3.6/site-packages/torch/_C.cpython-36m-x86_64-linux-gnu.so)

[nuist-xinyu]

Ah, I am crazy now.
Still not, God, help me.

[Duankaiwen]

Can I see your config/CenterNet-104.json?