Mobile Updates
PyTorch 1.6 brings increased performance and general stability for mobile on-device inference. We squashed a few bugs, continued maintenance and added few new features while improving fp32 and int8 performance on a large variety of ML model inference on CPU backend.
[Beta] Mobile Features and Performance

Stateless and stateful XNNPACK Conv and Linear operators
Stateless MaxPool2d + JIT optimization passes
JIT pass optimizations: Conv + BatchNorm fusion, graph rewrite to replace conv2d/linear with xnnpack ops, relu/hardtanh fusion, dropout removal
QNNPACK integration removes requantization scale constraint
Per-channel quantization for conv, linear and dynamic linear
Disable tracing for mobile client to save ~600 KB on full-jit builds

Updated Domain Libraries
torchvision 0.7