FIG. 19 illustrates training and deployment of a deep neural network, according to at least one embodiment. In at least one embodiment, untrained neural network 1906 is trained using a training dataset 1902. In at least one embodiment, training framework 1904 is a PyTorch framework, whereas in other embodiments, training framework 1904 is a TensorFlow, Boost, Caffe, Microsoft Cognitive Toolkit/CNTK, MXNet, Chainer, Keras, Deeplearning4j, or other training framework. In at least one embodiment, training framework 1904 trains an untrained neural network 1906 and enables it to be trained using processing resources described herein to generate a trained neural network 1908. In at least one embodiment, weights may be chosen randomly or by pre-training using a deep belief network. In at least one embodiment, training may be performed in either a supervised, partially supervised, or unsupervised manner.
