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Current implementation of Conv2dReLU, which is widely used in the codebase, has the use_batchnorm parameter that was set up first as a boolean before evolving for the use case for inplace batchnorm with an implicit string usage.
Why not modify the current API and use a normalization string parameter, which could be used to set up groupnorm or layernorm, which perform better with smaller batch sizes?
I can do the code quickly for that, and I will also add a warning that use_batchnorm might be deprecated in the future.
The text was updated successfully, but these errors were encountered:
Hey, it might be a cool feature! The only thing we have to consider is how to provide additional settings for layernorm or groupnorm. So it might be a dictionary instead, similar to aux_params. For example:
use_norm={"type": "layernorm", "eps": 1e-5}
Would you like to add this feature? I would appreciate a contribution if you have the bandwidth. Thank you!
Current implementation of Conv2dReLU, which is widely used in the codebase, has the use_batchnorm parameter that was set up first as a boolean before evolving for the use case for inplace batchnorm with an implicit string usage.
Why not modify the current API and use a normalization string parameter, which could be used to set up groupnorm or layernorm, which perform better with smaller batch sizes?
I can do the code quickly for that, and I will also add a warning that use_batchnorm might be deprecated in the future.
The text was updated successfully, but these errors were encountered: