Python – PyTorch Model Training: RuntimeError: cuDNN error: CUDNN_STATUS_INTERNAL_ERROR

After training a PyTorch model on a GPU for several hours, the program fails with the error

RuntimeError: cuDNN error: CUDNN_STATUS_INTERNAL_ERROR

Training Conditions

• Neural Network: PyTorch 4-layer nn.LSTM with nn.Linear output
• Deep Q Network Agent (Vanilla DQN with Replay Memory)
• state passed into forward() has the shape (32, 20, 15), where 32 is the batch size
• 50 seconds per episode
• Error occurs after about 583 episodes (8 hours) or 1,150,000 steps, where each step involves a forward pass through the LSTM model.

My code also has the following values set before the training began

torch.manual_seed(0)
torch.backends.cudnn.deterministic = True
torch.backends.cudnn.benchmark = False
np.random.seed(0)

How can we troubleshoot this problem? Since this occurred 8 hours into the training, some educated guess will be very helpful here!

Thanks!

Update:

Commenting out the 2 torch.backends.cudnn... lines did not work. CUDNN_STATUS_INTERNAL_ERROR still occurs, but much earlier at around Episode 300 (585,000 steps).

torch.manual_seed(0)
#torch.backends.cudnn.deterministic = True
#torch.backends.cudnn.benchmark = False
np.random.seed(0)

System

• PyTorch 1.6.0.dev20200525
• CUDA 10.2
• cuDNN 7604
• Python 3.8
• Windows 10
• nVidia 1080 GPU

Error Traceback

RuntimeError                              Traceback (most recent call last)
<ipython-input-18-f5bbb4fdfda5> in <module>
     57 
     58     while not done:
---> 59         action = agent.choose_action(state)
     60         state_, reward, done, info = env.step(action)
     61         score += reward

<ipython-input-11-5ad4dd57b5ad> in choose_action(self, state)
     58         if np.random.random() > self.epsilon:
     59             state = T.tensor([state], dtype=T.float).to(self.q_eval.device)
---> 60             actions = self.q_eval.forward(state)
     61             action = T.argmax(actions).item()
     62         else:

<ipython-input-10-94271a92f66e> in forward(self, state)
     20 
     21     def forward(self, state):
---> 22         lstm, hidden = self.lstm(state)
     23         actions = self.fc1(lstm[:,-1:].squeeze(1))
     24         return actions

~\AppData\Local\Continuum\anaconda3\envs\rl\lib\site-packages\torch\nn\modules\module.py in __call__(self, *input, **kwargs)
    575             result = self._slow_forward(*input, **kwargs)
    576         else:
--> 577             result = self.forward(*input, **kwargs)
    578         for hook in self._forward_hooks.values():
    579             hook_result = hook(self, input, result)

~\AppData\Local\Continuum\anaconda3\envs\rl\lib\site-packages\torch\nn\modules\rnn.py in forward(self, input, hx)
    571         self.check_forward_args(input, hx, batch_sizes)
    572         if batch_sizes is None:
--> 573             result = _VF.lstm(input, hx, self._flat_weights, self.bias, self.num_layers,
    574                               self.dropout, self.training, self.bidirectional, self.batch_first)
    575         else:

RuntimeError: cuDNN error: CUDNN_STATUS_INTERNAL_ERROR

Update: Tried try... except on my code where this error occurs at, and in addition to RuntimeError: cuDNN error: CUDNN_STATUS_INTERNAL_ERROR, we also get a second traceback for the error RuntimeError: CUDA error: unspecified launch failure

During handling of the above exception, another exception occurred:

RuntimeError                              Traceback (most recent call last)
<ipython-input-4-e8f15cc8cf4f> in <module>
     61 
     62     while not done:
---> 63         action = agent.choose_action(state)
     64         state_, reward, done, info = env.step(action)
     65         score += reward

<ipython-input-3-1aae79080e99> in choose_action(self, state)
     58         if np.random.random() > self.epsilon:
     59             state = T.tensor([state], dtype=T.float).to(self.q_eval.device)
---> 60             actions = self.q_eval.forward(state)
     61             action = T.argmax(actions).item()
     62         else:

<ipython-input-2-6d22bb632c4c> in forward(self, state)
     25         except Exception as e:
     26             print('error in forward() with state:', state.shape, 'exception:', e)
---> 27             print('state:', state)
     28         actions = self.fc1(lstm[:,-1:].squeeze(1))
     29         return actions

~\AppData\Local\Continuum\anaconda3\envs\rl\lib\site-packages\torch\tensor.py in __repr__(self)
    152     def __repr__(self):
    153         # All strings are unicode in Python 3.
--> 154         return torch._tensor_str._str(self)
    155 
    156     def backward(self, gradient=None, retain_graph=None, create_graph=False):

~\AppData\Local\Continuum\anaconda3\envs\rl\lib\site-packages\torch\_tensor_str.py in _str(self)
    331                 tensor_str = _tensor_str(self.to_dense(), indent)
    332             else:
--> 333                 tensor_str = _tensor_str(self, indent)
    334 
    335     if self.layout != torch.strided:

~\AppData\Local\Continuum\anaconda3\envs\rl\lib\site-packages\torch\_tensor_str.py in _tensor_str(self, indent)
    227     if self.dtype is torch.float16 or self.dtype is torch.bfloat16:
    228         self = self.float()
--> 229     formatter = _Formatter(get_summarized_data(self) if summarize else self)
    230     return _tensor_str_with_formatter(self, indent, formatter, summarize)
    231 

~\AppData\Local\Continuum\anaconda3\envs\rl\lib\site-packages\torch\_tensor_str.py in __init__(self, tensor)
     99 
    100         else:
--> 101             nonzero_finite_vals = torch.masked_select(tensor_view, torch.isfinite(tensor_view) & tensor_view.ne(0))
    102 
    103             if nonzero_finite_vals.numel() == 0:

RuntimeError: CUDA error: unspecified launch failure