I checked other suggestions, but other people used RNN Networks and data labels. In my case, everything was working fine yesterday, but suddenly my code is not working anymore.
I am trying to run this python code on my local machine:
C:/w/1/s/tmp_conda_3.6_045031/conda/conda-bld/pytorch_1565412750030/work/aten/src/THC/THCTensorIndex.cu:189: block: [25,0,0], thread: [63,0,0] Assertion dstIndex < dstAddDimSize failed. THCudaCheck FAIL file=C:/w/1/s/tmp_conda_3.6_045031/conda/conda-bld/pytorch_1565412750030/work/aten/src\THC/THCTensorMathCompareT.cuh line=69 error=59 : device-side assert triggered Traceback (most recent call last): File “rainbow.py”, line 763, in agent.train(epochs, horizon) File “rainbow.py”, line 629, in train loss = self.update_model() File “rainbow.py”, line 578, in update_model elementwise_loss_n_loss = self._compute_dqn_loss(samples, gamma) File “rainbow.py”, line 710, in _compute_dqn_loss dist = self.dqn.dist(state) File “rainbow.py”, line 386, in dist print(x) File “C:\Users\un_po\Anaconda3\envs\rainbowPy\lib\site-packages\torch\tensor.py”, line 82, in repr return torch._tensor_str._str(self) File “C:\Users\un_po\Anaconda3\envs\rainbowPy\lib\site-packages\torch_tensor_str.py”, line 300, in _str tensor_str = _tensor_str(self, indent) File “C:\Users\un_po\Anaconda3\envs\rainbowPy\lib\site-packages\torch_tensor_str.py”, line 201, in _tensor_str formatter = _Formatter(get_summarized_data(self) if summarize else self) File “C:\Users\un_po\Anaconda3\envs\rainbowPy\lib\site-packages\torch_tensor_str.py”, line 87, in init nonzero_finite_vals = torch.masked_select(tensor_view, torch.isfinite(tensor_view) & tensor_view.ne(0)) File “C:\Users\un_po\Anaconda3\envs\rainbowPy\lib\site-packages\torch\functional.py”, line 228, in isfinite return (tensor == tensor) & (tensor.abs() != inf) RuntimeError: cuda runtime error (59) : device-side assert triggered at C:/w/1/s/tmp_conda_3.6_045031/conda/conda-bld/pytorch_1565412750030/work/aten/src\THC/THCTensorMathCompareT.cuh:69 Yesterday the same code just worked fine.
And the code still works on CPU.
4 Reset to default