All Classes and Interfaces

Classes
Class
Description
AlexNet contains a generic implementation of AlexNet adapted from [torchvision implmentation](https://github.com/pytorch/vision/blob/master/torchvision/models/alexnet.py)
The Builder to construct a AlexNet object.
Model Zoo is a repository that contains all models for DJL.
An imperative model zoo provider implements the ZooProvider interface.
GoogLeNet uses a stack of a total of 9 inception blocks and global average pooling to generate its estimates.
The Builder to construct a GoogLeNet object.
The model was introduced (and named for) Yann Lecun, for the purpose of recognizing handwritten digits in images [LeNet5](http://yann.lecun.com/exdb/lenet/).
The Builder to construct a LeNet object.
Multilayer Perceptron (MLP) NeuralNetworks.
A BlockFactory class that creates MLP block.
MobileNetV1 contains a generic implementation of Mobilenet adapted from https://github.com/weiaicunzai/pytorch-cifar100/blob/master/models/mobilenet.py (Original author weiaicunzai).
The Builder to construct a MobileNetV1 object.
MobileNetV2 contains a generic implementation of MobilenetV2 adapted from https://github.com/weiaicunzai/pytorch-cifar100/blob/master/models/mobilenetv2.py (Original author weiaicunzai).
The Builder to construct a MobileNetV2 object.
NiN uses convolutional layers with window shapes of 11×11 , 5×5 , and 3×3 , and the corresponding numbers of output channels are the same as in AlexNet.
The Builder to construct a NiN object.
A BlockFactory class that creates ResNetV1 block.
ResNetV1 contains a generic implementation of ResNet adapted from https://github.com/tornadomeet/ResNet/blob/master/symbol_resnet.py (Original author Wei Wu) by Antti-Pekka Hynninen.
The Builder to construct a ResNetV1 object.
SimpleTextDecoder implements a Decoder that employs a RecurrentBlock to decode text input.
SimpleTextEncoder implements a Encoder that employs a RecurrentBlock to encode text input.
SingleShotDetection is an implementation of Block that implements a Single Shot Detection (SSD) model for object detection.
The Builder to construct a SingleShotDetection.
SqueezeNet contains a generic implementation of Squeezenet adapted from [torchvision implmentation](https://github.com/pytorch/vision/blob/master/torchvision/models/squeezenet.py)
A BlockFactory class that creates SingleShotDetection block.
TabNet contains a generic implementation of TabNet adapted from https://towardsdatascience.com/implementing-tabnet-in-pytorch-fc977c383279 (Original author Samrat Thapa)
AttentionTransformer is where the tabNet models learn the relationship between relevant features, and decides which features to pass on to the feature transformer of the current decision step.
The Builder to construct a TabNet object.
DecisionStep is just combining featureTransformer and attentionTransformer together.
VGG model from the "Very Deep Convolutional Networks for Large-Scale Image Recognition" https://arxiv.org/abs/1409.1556 paper.
The Builder to construct a VGG object.
YOLOV3 contains a generic implementation of yolov3 (Original author bubbliiiing).
The Builder to construct a YOLOV3 object.