How to assign gradients to model parameters manually?

In A3C, the gradients of main thread parameters are copied from training threads.
But the gradients of pytorch nn.module cannot be reassigned?
So how to implement this procedure?

BTW. is there a function like tf.gather_nd() in pytorch?
to extract values in specific indexes of the tensor (multidimensional).
Cause right now, the torch.indes_select can only select from one dimension.

to answer your second question, you can create a mask tensor and index elements via this mask tensor:


import torch

x = torch.randn(2, 3, 2)

mask =

# mask is a torch.ByteTensor of same shape and size as x



(0 ,.,.) =
  0  0
  0  0
  0  1

(1 ,.,.) =
  0  1
  1  0
  1  0
[torch.ByteTensor of size 2x3x2]

[torch.FloatTensor of size 4]

1 Like

Thank you smth.
If I have an index list where same indexes may repeat for several times.

Then I think this method is useless.

Did you try gather?

But gather always returns a tensor with same dimension as the input right?

Yes, that’s the limitation.