Major Updates

Building tools is coming! Provide nn-Meter building tools for users to build latency predictor for their own devices (#43, #59, #66)

• Provide a unified interface to connect with TFLite and OpenVINO platforms, and support users to connect their own devices
• Support operator fusion rules detection on target backend, and support users to design new test cases.
• Provide tools to build kernel latency predictor for several built-in kernels or user-customized kernels.
• Support both Tensorflow and PyTorch implementation of fusion rule test cases and kernels.
• Provide examples for using nn-Meter building tools.

Minor Updates & Bug Fixes

• Add quick start tutorials for users to get started (#58)
• Provide support to torch v1.10, tensorflow v2.7, and nni v2.7 (#43)
• Fix bugs in torch converter and kernel detector (#47, #49)
• Fix bugs in shape parsing of global avgpool and se operator in onnx converter (#60)

The TFLite Benchmark Tools with version tensorflow==2.1 and tensorflow==2.7 for nn-Meter builder.

Major Updates

• Add nn-Meter Bench Dataset (#25)
• Add GNN dataloader for nn-Meter Bench Dataset (#27)
• Support torch v1.9, tensorflow v2.6, nni v2.5 (#36)
• Add notebook examples for nn-Meter usage (#26, #29)

Minor Updates & Bug Fixes

• Support hardware latency prediction for ProxylessNAS in NNI (https://github.com/microsoft/nni/pull/4206)
• Refine shape attributes to sync with NNI (fix issue https://github.com/microsoft/nni/issues/4198, PR #30, #33)
• Refactor of nn-Meter Project (#41)

Release 1.0 - 9/1/2021 (initial release)

Initial release of nn-Meter.

Major Features

• Support pip install and source codes install
• Support latency prediction for a CNN model with a predefined predictor (edge device)
• Provide command line interface nn-meter after installation, and python binding module nn_meter
• Provide Docs

Known Issues

• Synchronization with NNI: a stable NNI-based torch converter relies on NNI>=2.5.
• Can not support torch.jit._overload_method due to issues from torch.