@@ -391,8 +391,9 @@ The following workflows have common variables with the above illustrated workflo
The following workflows contain a search space containing a set of possible neural networks architectures that can be used by `Distributed_Auto_ML` to automatically find the best combinations of neural architectures within the search space.
*Handwritten_Digit_Classification:* trains a simple deep CNN on the MNIST dataset using the PyTorch library. This example allows to search for two types of neural architectures defined in the Handwritten_Digit_Classification_Search_Space.json file.
*Single_Handwritten_Digit_Classification:* trains a simple deep CNN on the MNIST dataset using the PyTorch library. This example allows to search for two types of neural architectures defined in the Handwritten_Digit_Classification_Search_Space.json file.
*Multiple_Objective_Handwritten_Digit_Classification:* trains a simple deep CNN on the MNIST dataset using the PyTorch library. This example allows optimizing multiple losses, such as accuracy, number of parameters, and memory access cost (MAC) measure.
