Hello,while running main.py, I got some error. Any solutions or suggestions for this issue?
My enviroment:ubuntu16.04 + NVIDIA GTX 960M+anaconda3+ python3.6+pytorch1.0.0+CoppeliaSim4.0. And I use the code for pytorch 1.0.0,
`Connected to simulation.
CUDA detected. Running with GPU acceleration.
/home/zhb/anaconda3/envs/work/lib/python3.6/site-packages/torchvision/models/densenet.py:212: UserWarning: nn.init.kaiming_normal is now deprecated in favor of nn.init.kaiming_normal_.
nn.init.kaiming_normal(m.weight.data)
/home/zhb/zhb_ws/src/visual-pushing-grasping/models.py:203: UserWarning: nn.init.kaiming_normal is now deprecated in favor of nn.init.kaiming_normal_.
nn.init.kaiming_normal(m[1].weight.data)
/home/zhb/anaconda3/envs/work/lib/python3.6/site-packages/torch/nn/_reduction.py:49: UserWarning: size_average and reduce args will be deprecated, please use reduction='none' instead.
warnings.warn(warning.format(ret))
Creating data logging session: /home/zhb/zhb_ws/src/visual-pushing-grasping/logs/2021-04-30.21:00:29

Training iteration: 0
/home/zhb/zhb_ws/src/visual-pushing-grasping/models.py:235: UserWarning: volatile was removed and now has no effect. Use with torch.no_grad(): instead.
rotate_color = F.grid_sample(Variable(input_color_data, volatile=True).cuda(), flow_grid_before, mode='nearest')
/home/zhb/zhb_ws/src/visual-pushing-grasping/models.py:236: UserWarning: volatile was removed and now has no effect. Use with torch.no_grad(): instead.
rotate_depth = F.grid_sample(Variable(input_depth_data, volatile=True).cuda(), flow_grid_before, mode='nearest')
/home/zhb/anaconda3/envs/work/lib/python3.6/site-packages/torch/nn/modules/upsampling.py:129: UserWarning: nn.Upsample is deprecated. Use nn.functional.interpolate instead.
warnings.warn("nn.{} is deprecated. Use nn.functional.interpolate instead.".format(self.name))
/home/zhb/anaconda3/envs/work/lib/python3.6/site-packages/torch/nn/functional.py:2423: UserWarning: Default upsampling behavior when mode=bilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
"See the documentation of nn.Upsample for details.".format(mode))
Primitive confidence scores: 1.670718 (push), 3.414888 (grasp)
Strategy: exploit (exploration probability: 0.500000)
Action: grasp at (12, 103, 183)
Executing: grasp at (-0.358000, -0.018000, 0.050978)
Grasp successful: False
Time elapsed: 20.776577

Training iteration: 1
Change detected: False (value: 258)
Current reward: 0.000000
Future reward: 0.000000
Expected reward: 0.000000 + 0.500000 x 0.000000 = 0.000000
Primitive confidence scores: 1.596479 (push), 2.667503 (grasp)
Strategy: exploit (exploration probability: 0.500000)
Action: grasp at (6, 119, 183)
Traceback (most recent call last):
File "main.py", line 450, in
main(args)
File "main.py", line 301, in main
trainer.backprop(prev_color_heightmap, prev_valid_depth_heightmap, prev_primitive_action, prev_best_pix_ind, label_value)
File "/home/zhb/zhb_ws/src/visual-pushing-grasping/trainer.py", line 342, in backprop
push_predictions, grasp_predictions, state_feat = self.forward(color_heightmap, depth_heightmap, is_volatile=False, specific_rotation=best_pix_ind[0])
File "/home/zhb/zhb_ws/src/visual-pushing-grasping/trainer.py", line 163, in forward
output_prob, state_feat = self.model.forward(input_color_data, input_depth_data, is_volatile, specific_rotation)
File "/home/zhb/zhb_ws/src/visual-pushing-grasping/models.py", line 292, in forward
interm_push_color_feat = self.push_color_trunk.features(rotate_color)
File "/home/zhb/anaconda3/envs/work/lib/python3.6/site-packages/torch/nn/modules/module.py", line 489, in call
result = self.forward(*input, **kwargs)
File "/home/zhb/anaconda3/envs/work/lib/python3.6/site-packages/torch/nn/modules/container.py", line 92, in forward
input = module(input)
File "/home/zhb/anaconda3/envs/work/lib/python3.6/site-packages/torch/nn/modules/module.py", line 489, in call
result = self.forward(*input, **kwargs)
File "/home/zhb/anaconda3/envs/work/lib/python3.6/site-packages/torch/nn/modules/container.py", line 92, in forward
input = module(input)
File "/home/zhb/anaconda3/envs/work/lib/python3.6/site-packages/torch/nn/modules/module.py", line 489, in call
result = self.forward(*input, **kwargs)
File "/home/zhb/anaconda3/envs/work/lib/python3.6/site-packages/torchvision/models/densenet.py", line 141, in forward
new_features = super(_DenseLayer, self).forward(x)
File "/home/zhb/anaconda3/envs/work/lib/python3.6/site-packages/torch/nn/modules/container.py", line 92, in forward
input = module(input)
File "/home/zhb/anaconda3/envs/work/lib/python3.6/site-packages/torch/nn/modules/module.py", line 489, in call
result = self.forward(*input, **kwargs)
File "/home/zhb/anaconda3/envs/work/lib/python3.6/site-packages/torch/nn/modules/batchnorm.py", line 76, in forward
exponential_average_factor, self.eps)
File "/home/zhb/anaconda3/envs/work/lib/python3.6/site-packages/torch/nn/functional.py", line 1623, in batch_norm
training, momentum, eps, torch.backends.cudnn.enabled
RuntimeError: CUDA out of memory. Tried to allocate 5.12 MiB (GPU 0; 1.96 GiB total capacity; 1.09 GiB already allocated; 1.94 MiB free; 27.21 MiB cached)
`