If you check in something that is not reflected in Roadmap issue, please reply
to that issue so it can get added.
+
+## 0.5
+This release features several major improvements. Some of the highlights are: Arbitrary bits quantization algorithm; High-level auto-differentiable programming IR -- Relay.
+
+- Fully featured 8-bit network support
+ - 8bit quantizer
+ - Arbitrary bits quantization algorithm
+ - Intel cpu support
+ - ARM 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
+ * Frontend support: Caffe2 #2507 , CoreML #2476 , Keras #2376 , MXNet #2163 , ONNX, TFLite #2365
+ * Operator coverage #1799 #2051
+ - 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
+ - Rust frontend #2292
+- VTA
+ - Improved RPC for VTA #2043
+- Hybrid python programming model
+ - Support for scheduling #2416
+ - Support for Inter-function call #2287
+ - Backend support #2477
+- TOPI
+ - Initial support for sparse tensor computation
+ - Improve ARM CPU depthwise convolution performance #2345
+ - Port winograd ops to relay #2356
+ - Add faster-rcnn proposal op #2420
+- 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
+
+
+
## 0.4
This release features several major improvements. The high-level graph optimizer is now part of TVM repo. Some of the highlights are: Initial support of AutoTVM for automated optimization; customized accelerator backend VTA.