[MXNet Forum] [Gluon] Selective backpropagation

[Miguel Romero via MXNet Forum <mx...@discoursemail.com.INVALID>]

Hello,

I am trying to implement a model that is trained (in a simplified way) as follows:

Given image1 & image2:
```
out1 = Net(image1)
out2 = Net(image2)

loss = loss_func(out1, out2)
```

However, I only want the back-propagation to be done for one of the images. What would be the best way to do this?

Right now I am running into the following error when trying to just add one of those passes under `with mx.autograd.record():`:

```
Error in operator node_1436_backward: [00:58:51] src/imperative/./imperative_utils.h:774: Check failed: g.GetAttr<size_t>("storage_type_num_unknown_nodes") == 0U (4 vs. 0)
```





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