Is it faster than Keras built-in SeparableConv2D layer?

[kirillfish]

Depthwise separable convolutions are notoriously hard to implement efficiently. In particular, SeparableConv2D in Keras (as well as group convolutions in Keras and PyTorch) leads to almost no speedup on CPU, and makes training even slower on GPU, despite the number of parameters dropped by an order of magnitude.

Are you planning to add some sort of benchmarking here? I think fast group convolution and depthwise convolution are the features many people need really badly.