I keep getting this error when trying to compute the grads of a non-leaf tensor during training.

```
RuntimeError Traceback (most recent call last)
<ipython-input-6-5a671eebd60a> in <module>
18 # group['lr'] = newlr
19
<ipython-input-5-80f6a1f0d5ab> in train(model, opt, data_loader, criterion, device)
19 register_nonleaf_grads(logits)
20 crossent = criterion(logits, y)
---> 21 crossent.backward(retain_graph=True)
~/miniconda3/envs/tflow/lib/python3.7/site-packages/torch/tensor.py in backward(self, gradient, retain_graph, create_graph, inputs)
243 create_graph=create_graph,
244 inputs=inputs)
--> 245 torch.autograd.backward(self, gradient, retain_graph, create_graph, inputs=inputs)
246
247 def register_hook(self, hook):
~/miniconda3/envs/tflow/lib/python3.7/site-packages/torch/autograd/__init__.py in backward(tensors, grad_tensors, retain_graph, create_graph, grad_variables, inputs)
145 Variable._execution_engine.run_backward(
146 tensors, grad_tensors_, retain_graph, create_graph, inputs,
--> 147 allow_unreachable=True, accumulate_grad=True) # allow_unreachable flag
148
149
RuntimeError: Unable to find a valid cuDNN algorithm to run convolution
```

Here’s my approach, any ideas what I’m doing wrong?

```
def register_nonleaf_grads(variable):
def hook(grad):
variable.nonleaf_grads = grad
variable.register_hook(hook)
def train(model, opt, data, criterion):
for x, y in data:
x.requires_grad_()
logits = model(x)
register_nonleaf_grads(logits)
crossent = criterion(logits, y)
crossent.backward(retain_graph=True)
loss = crossent + l2_norm
x.grad.zero_()
logits.nonleaf_grads.zero_()
opt.zero_grad()
loss.backward()
opt.step()
```