Mohammed Innat
Mohammed Innat
@divyashreepathihalli Uh, sorry for the confusion. Actually, I prepared some kaggle notebooks (currently its private) which will help you to evaluate or verify the model and weights. You can also...
@divyashreepathihalli > and update the kaggle handle to be "kaggle_handle": "kaggle://keras//keras//
@sonali-kumari1 Thanks for your response. - `"full"`: Apply rematerialization globally to all supported operations. what are the supported operations here? - `"list_of_layers"`: Apply rematerialization to a specific list of layer...
@sonali-kumari1 Thanks for the update. 1. For built-in models like `keras.applications.DenseNet121`, I think `mode=full` is more appropriate. And `mode=list_of_layers` with `layer_names=["dense_1"]` is very specific, because the densenet model may not...
@divyashreepathihalli A gentle reminder.
Can you add some references, sounds interesting.
The `fill_mode="mirror"` sounds like a `fill_mode="reflect"`.
@bhack Thanks for sharing this information, very useful. It's definitely an effective option. > Cutout, which improves clean accuracy but not robustness, and additive Gaussian noise, which improves robustness but...
@sachinprasadhs > If you encounter a KerasCV feature that is missing from KerasHub, or would like to propose an addition to the library, please file [an issue with KerasHub](https://github.com/keras-team/keras-hub/issues). Firstly,...
@kernel-loophole I can't review other than giving comment. The code is overall well-structured. There may (or may not) be a need for minor adjustments to fully align with the Keras...