brainspy.algorithms#
It provides different default algorithms for brains-py, that already add several features that are particular to dopant-networks. There are two main flavours of algorithms: Genetic Algorithm and Gradient Descent. Both algorithms can be executed seamlessly by importing and calling their corresponding ‘train’ function. For general purpose, the corresponding train function can be loaded from brainspy.utils.manager. For more advanced implementation, a custom algorithm is recommended. Check the wiki for more information.
Modules
File containing the genetic algorithm methods and the optimizer class for training a single DNPU. |
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File containing the gradient descent algorithm methods adapted for DNPU classes and custom torch.nn.Module children custom classes that contain DNPU classes or DNPU based modules from brainspy.processors.modules. |