BUG

[MsXFang]

Traceback (most recent call last): File "train_ctfp.py", line 160, in loss.backward() File "/home/fry/anaconda3/envs/CTFP1/lib/python3.8/site-packages/torch/_tensor.py", line 255, in backward torch.autograd.backward(self, gradient, retain_graph, create_graph, inputs=inputs) File "/home/fry/anaconda3/envs/CTFP1/lib/python3.8/site-packages/torch/autograd/init.py", line 147, in backward Variable._execution_engine.run_backward( File "/home/fry/anaconda3/envs/CTFP1/lib/python3.8/site-packages/torch/autograd/function.py", line 87, in apply return self._forward_cls.backward(self, *args) # type: ignore[attr-defined] File "/home/fry/anaconda3/envs/CTFP1/lib/python3.8/site-packages/torchdiffeq/_impl/adjoint.py", line 126, in backward aug_state = odeint( File "/home/fry/anaconda3/envs/CTFP1/lib/python3.8/site-packages/torchdiffeq/_impl/odeint.py", line 72, in odeint shapes, func, y0, t, rtol, atol, method, options, event_fn, t_is_reversed = _check_inputs(func, y0, t, rtol, atol, method, options, event_fn, SOLVERS) File "/home/fry/anaconda3/envs/CTFP1/lib/python3.8/site-packages/torchdiffeq/_impl/misc.py", line 207, in _check_inputs rtol = _tuple_tol('rtol', rtol, shapes) File "/home/fry/anaconda3/envs/CTFP1/lib/python3.8/site-packages/torchdiffeq/_impl/misc.py", line 115, in _tuple_tol assert len(tol) == len(shapes), "If using tupled {} it must have the same length as the tuple y0".format(name) AssertionError: If using tupled rtol it must have the same length as the tuple y0