ARISE-Initiative / robosuite-benchmark

Benchmarking Repository for robosuite + SAC
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RunTime error when using train.py #11

Open caishanglei opened 3 years ago

caishanglei commented 3 years ago

Traceback (most recent call last): File "scripts/train.py", line 131, in run_experiment() File "scripts/train.py", line 104, in run_experiment experiment(variant, agent=args.agent) File "/home/luai/1/robosuite/robosuite-benchmark/util/rlkit_utils.py", line 163, in experiment algorithm.train() File "/home/luai/1/robosuite/robosuite-benchmark/util/rlkit_custom.py", line 46, in train self._train() File "/home/luai/1/robosuite/robosuite-benchmark/util/rlkit_custom.py", line 235, in _train self.trainer.train(train_data) File "/home/luai/1/robosuite/robosuite-benchmark/rlkit/rlkit/torch/torch_rl_algorithm.py", line 40, in train self.train_from_torch(batch) File "/home/luai/1/robosuite/robosuite-benchmark/rlkit/rlkit/torch/sac/sac.py", line 144, in train_from_torch policy_loss.backward() File "/home/luai/anaconda3/envs/rl/lib/python3.6/site-packages/torch/tensor.py", line 245, in backward torch.autograd.backward(self, gradient, retain_graph, create_graph, inputs=inputs) File "/home/luai/anaconda3/envs/rl/lib/python3.6/site-packages/torch/autograd/init.py", line 147, in backward allow_unreachable=True, accumulate_grad=True) # allow_unreachable flag RuntimeError: one of the variables needed for gradient computation has been modified by an inplace operation: [torch.cuda.FloatTensor [256, 1]], which is output 0 of TBackward, is at version 2; expected version 1 instead. Hint: enable anomaly detection to find the operation that failed to compute its gradient, with torch.autograd.set_detect_anomaly(True).

csufangyu commented 3 years ago

hi,I have got the same problem.you can change version of torch