Hey,
I’m using the following code in order to get the gradients of the tensor calculated. I want to change the tensor values in aspect to the loss:
> from facenet_pytorch import InceptionResnetV1
> import torch.nn as nn
> resnet = InceptionResnetV1(pretrained='vggface2').eval()
> tensor1 = torch.tensor((), dtype=torch.float32)
> tensor2 = torch.tensor((), dtype=torch.float32)
> tensor1 = torch.stack([(tensor1.new_ones(3,160,160))])
> tensor2 = torch.stack([(tensor2.new_ones(3,160,160))])
> tensor1.require_grad=True
> ev1 = resnet(tensor1)
> ev2 = resnet(tensor2)
> print(ev1.shape) # torch.Size([1, 512])
> cos = nn.CosineSimilarity()
> loss = cos(ev1, ev2)
> loss.backward(retain_graph=True)
> data_grad = ev1.grad.data
> print(data_grad)

It seems that loss.backwards doesnt calc anything because in the next line
(ev1.grad.data) grad is None : 
     15 loss.backward(retain_graph=True)
---> 16 data_grad = ev1.grad.data

AttributeError: 'NoneType' object has no attribute 'data'

I also got a warning that I try to access .grad attribute of a tensor that isnt a leaf tensor. So how can I calc the grad of the orig tensor ?