RuntimeError: dimension out of range (expected to be in range of [-2, 1], but got 2)

[ekremcet]

I am trying to train the CornerNet on my machine but it produces the following error.

loading all datasets...
using 4 threads
loading from cache file: ./cache/coco_trainval2014.pkl
loading annotations into memory...
Done (t=8.28s)
creating index...
index created!
loading from cache file: ./cache/coco_trainval2014.pkl
loading annotations into memory...
Done (t=8.38s)
creating index...
index created!
loading from cache file: ./cache/coco_trainval2014.pkl
loading annotations into memory...
Done (t=9.22s)
creating index...
index created!
loading from cache file: ./cache/coco_trainval2014.pkl
loading annotations into memory...
Done (t=8.18s)
creating index...
index created!
loading from cache file: ./cache/coco_minival2014.pkl
loading annotations into memory...
Done (t=0.23s)
creating index...
index created!
system config...
{'batch_size': 1,
'cache_dir': './cache',
'chunk_sizes': [1],
'config_dir': './config',
'data_dir': './data',
'data_rng': <mtrand.RandomState object at 0x7fd5039ad4c8>,
'dataset': 'MSCOCO',
'decay_rate': 10,
'display': 5,
'learning_rate': 0.00025,
'max_iter': 500000,
'nnet_rng': <mtrand.RandomState object at 0x7fd5039ad510>,
'opt_algo': 'adam',
'prefetch_size': 5,
'pretrain': None,
'result_dir': './results',
'sampling_function': 'kp_detection',
'snapshot': 100,
'snapshot_name': 'CornerNet',
'stepsize': 450000,
'test_split': 'testdev',
'train_split': 'trainval',
'val_iter': 100,
'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],
'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': 100,
'weight_exp': 8}
len of db: 118287
start prefetching data...
shuffling indices...
start prefetching data...
shuffling indices...
start prefetching data...
shuffling indices...
start prefetching data...
shuffling indices...
start prefetching data...
building model...
module_file: models.CornerNet
shuffling indices...
total parameters: 201035212
setting learning rate to: 0.00025
training start...
0%| | 0/500000 [00:00<?, ?it/s]
Traceback (most recent call last):
File "train.py", line 195, in
train(training_dbs, validation_db, args.start_iter)
File "train.py", line 137, in train
training_loss = nnet.train(**training)
File "/home/ekrem/PycharmProjects/CornerNet/nnet/py_factory.py", line 81, in train
loss = self.network(xs, ys)
File "/home/ekrem/anaconda3/envs/CornerNet/lib/python3.6/site-packages/torch/nn/modules/module.py", line 491, in call
result = self.forward(*input, **kwargs)
File "/home/ekrem/PycharmProjects/CornerNet/models/py_utils/data_parallel.py", line 68, in forward
return self.module(*inputs[0], **kwargs[0])
File "/home/ekrem/anaconda3/envs/CornerNet/lib/python3.6/site-packages/torch/nn/modules/module.py", line 491, in call
result = self.forward(*input, **kwargs)
File "/home/ekrem/PycharmProjects/CornerNet/nnet/py_factory.py", line 20, in forward
loss = self.loss(preds, ys, **kwargs)
File "/home/ekrem/anaconda3/envs/CornerNet/lib/python3.6/site-packages/torch/nn/modules/module.py", line 491, in call
result = self.forward(*input, **kwargs)
File "/home/ekrem/PycharmProjects/CornerNet/models/py_utils/kp.py", line 297, in forward
pull, push = self.ae_loss(tl_tag, br_tag, gt_mask)
File "/home/ekrem/PycharmProjects/CornerNet/models/py_utils/kp_utils.py", line 197, in _ae_loss
dist = tag_mean.unsqueeze(1) - tag_mean.unsqueeze(2)
RuntimeError: dimension out of range (expected to be in range of [-2, 1], but got 2)

I have set batch_size = 1 and chunk_sizes = [1] to get rid of the out of memory error as mentioned in #4

Any suggestions ?
Thanks

[lianbobo]

CornerNet/models/py_utils/kp_utils.py
Above line 193 ( mask = mask.unsqueeze(1) + mask.unsqueeze(2) ) add a line of code：tag_mean = tag_mean.unsqueeze(0)

[ekremcet]

CornerNet/models/py_utils/kp_utils.py
Above line 193 ( mask = mask.unsqueeze(1) + mask.unsqueeze(2) ) add a line of code：tag_mean = tag_mean.unsqueeze(0)

This solved the problem. Thanks !

[duanqipeng]

CornerNet/models/py_utils/kp_utils.py
Above line 193 ( mask = mask.unsqueeze(1) + mask.unsqueeze(2) ) add a line of code：tag_mean = tag_mean.unsqueeze(0)

This solved the problem. Thanks !

hey! i got the same error as u meet,then i use the method to solve the problem,but get another problem

IndexError: The shape of the mask [2, 128, 128] at index 0does not match the shape of the indexed tensor [1, 2, 2, 128] at index 0
i have 4 gpu and use bachsize=6,chunksize=[1,1,2,2]