TensorLayer 1.8.3

This release focuses on model compression and acceleration, feel free to discuss here.

New APIs

• TenaryDenseLayer, TenaryConv2d, DorefaDenseLayer, DorefaConv2d for Tenary Weight Net and DoReFa-Net (by @XJTUWYD)
• BinaryDenseLayer, BinaryConv2d, SignLayer, ScaleLayer for BinaryNet (by @zsdonghao)
• tl.act.htanh for BinaryNet (by @zsdonghao)
• GlobalMeanPool3d, GlobalMaxPool3d (by @zsdonghao)
• ZeroPad1d, ZeroPad2d, ZeroPad3d (by @zsdonghao)

New Updates

• Fixed bug of tl.utils.predict #426 56335c5 (by @xionghhcs)
• Enable skip biases in Conv3dLayer, the same as beta and gamma in BatchNormLayer 7a5b258 (by @lllcho)

New Examples

• SqueezeNet (ImageNet). AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size, see tutorial_squeezenet.py (by @zsdonghao)
• BinaryNet. Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1, see tutorial_binarynet_mnist_cnn.py (by @zsdonghao)
• Tenary Weight Network, see mnist cifar10. (by @XJTUWYD)
• DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients, see mnist cifar10. (by @XJTUWYD)

New Discussion

• Model Compression and Acceleration
• Real Time Object Detection
• Real Time Pose Estimation
• Text to Speech (TTS)
• High-level Model API