Feature Request: Add Mish Activation

[digantamisra98]

Mish is a novel activation function proposed in this paper.
It has shown promising results so far and has been adopted in several packages including:

TensorFlow-Addons	SpaCy (Tok2Vec Layer)	Thinc - SpaCy's official NLP based ML library
Eclipse's deeplearning4j	Hasktorch	Echo AI
CNTKX - Extension of Microsoft's CNTK	FastAI-Dev	Darknet
Yolov3	BeeDNN - Library in C++	Gen-EfficientNet-PyTorch
dnet	ruby-dnn	blackcat-tensors
DL4S	HuggingFace Transformers	PAGI
OpenCV	Odin-AI	Mini DNN
Efficient Segmentation Networks

All benchmarks, analysis and links to official package implementations can be found in this repository

Mish also was recently used for a submission on the Stanford DAWN Cifar-10 Training Time Benchmark where it obtained 94% accuracy in just 10.7 seconds which is the current best score on 4 GPU and second fastest overall. Additionally, Mish has shown to improve convergence rate by requiring less epochs. Reference -

Mish also has shown consistent improved ImageNet scores and is more robust. Reference -

Additional ImageNet benchmarks along with Network architectures and weights are avilable on my repository.

Summary of Vision related results:

It would be nice to have Mish as an option within the activation function group.

This is the comparison of Mish with other conventional activation functions in a SEResNet-50 for CIFAR-10:

[keerthanvasist]

Thank you for the feature request @digantamisra98. We will implement the Mish activation function soon.

[digantamisra98]

@keerthanvasist Thank you for considering the request.

[digantamisra98]

Noticed, that Mish has been recently committed to DJL - b06feb1
Closing this issue then. Thanks for adding Mish.