Traceback (most recent call last):
File "/home/shared/tabzilla/TabSurvey/tabzilla_experiment.py", line 137, in __call__
result = cross_validation(model, self.dataset, self.time_limit)
File "/home/shared/tabzilla/TabSurvey/tabzilla_utils.py", line 236, in cross_validation
loss_history, val_loss_history = curr_model.fit(
File "/home/shared/tabzilla/TabSurvey/models/tabtransformer.py", line 120, in fit
loss.backward()
File "/opt/conda/envs/torch/lib/python3.10/site-packages/torch/_tensor.py", line 363, in backward
torch.autograd.backward(self, gradient, retain_graph, create_graph, inputs=inputs)
File "/opt/conda/envs/torch/lib/python3.10/site-packages/torch/autograd/__init__.py", line 173, in backward
Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
RuntimeError: self must be a matrix
occurs on datasets:
traceback: