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This release features several major improvements. Some of the highlights are: Arbitrary bits quantization algorithm; High-level auto-differentiable programming IR--Relay(NNVMv2).

The community welcomes new reviewers @nishi-t @were @siju-samuel @jroesch @xqdan @zhiics @grwlf @ajtulloch @vinx13 @junrushao1994 @FrozenGene @liangfu , new committers @srkreddy1238 @eqy @masahi @nhynes @phisiart @merrymercy @Laurawly @adityaatluri @Huyuwei

Change List

  • Fully featured 8-bit network support
    • 8bit quantizer
    • Arbitrary bits quantization algorithm
    • Intel cpu support
  • NVidia GPU 8-bit kernel
    • int8 gemm recipe
    • int8 conv2d
    • Autotvm integration
  • Automated tuning and scheduling
    • AutoTVM optimizations for mobile GPUs
    • AutoTVM optimizations for CUDA
    • AutoTVM optimizations for x86
  • Initial release of the differentiable programming IR, Relay
    • Generic & informative Relay error reporting #2408
    • Relay IR text format support #1781
    • Support control flows
    • A Normal Form Canonicalization #2251
    • Type system support
    • End to end compilation
    • FoldScaleAxis #2020
    • SimplifyInference #2033
    • CombineParallelConv2D #2089
    • InstrumentBoundCheckers pass #2079
    • Bind & FoldConstant #2100
    • Alter Op Layout #2150
    • General OpFusion #2090
  • CodeGen
    • Gcc / g++ compatible C code generator for TVM #2161
    • Device type annotation for heterogeneous compilation #2361
    • Cache packed func ptr, lift alloca #2070
    • Generalize compute to tensor region #1476
  • Runtime
    • Relay interpreter and compiler #1954
    • Heterogeneous runtime #1695
    • Language bindings: Golang runtime #1470 , Rust runtime #1597
    • Add min_repeat_ms to time_evaluator #2200
    • Bundled interpreter demonstration #2297
    • Enable PlanMemory in the graph runtime #2120
  • Language Binding
  • VTA
    • Improved RPC for VTA #2043
  • Hybrid python programming model
    • Support for scheduling #2416
    • Support for Inter-function call #2287
    • Backend support #2477
  • TOP
    • Initial support for sparse tensor computation
    • Improve ARM CPU depthwise convolution performance #2345
    • Port winograd ops to relay #2356
  • Tutorials and docs
    • Relay language docs #2232
    • Tutorials on how to use SGX backend
    • How to write a pass in python
    • General lowering flow of TVM
    • How to do tensorize
    • TFLite frontend tutorial #2508
    • Keras seq2seq model for translation tutorial #1815
    • Committer guide and tips #2468
    • Code review guideline on API designs #2459

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