I’m currently implementing a custom
nn.Module in pytorch. I was wondering if anyone has best practices for optimizing your module for speed?
As an example, my module has a list of 4 x tensors of (64 x 784), and I loop through to perform iterations. I’m wondering if would be more performant to do matrix operations instead by making tensor ( 4 x 64 x 784 )?
Anyone have best practices of when to use loops vs. converting to matrix operations?