Hi all,

If I were to use a Conv2d with a stride of 1, a kernel size of 1, no padding and no bias. This would be equivalent to multiplying a matrix by another matrix right?

```
self.matrix_mul =
nn.Conv2d(
in_channels=3,
out_channels=3,
kernel_size=1,
stride=1,
padding=0,
bias=False)
```

So essentially if I were to train a single layer on a dataset where:

Input: square image

Target: same square image

The single layer would learn the identity matrix right?

(Ps. Iām a bit rusty on my matrix math.)

Thanks.