This release is the first stable version of ONNX.
This version also includes the ONNX-ML profile that extends ONNX with classic ML constructs. This is an optional profile.
The following changes have been made since the 0.2 release:
- Adds versioning documentation
- Adds release management notes
- Operator specs include samples
- Adds operator sets, imports and experimental operator support.
- Adds an AttributeType enum, doc_string fields, domain for NodeProto.
- Adds named metadata properties to models.
- Remove sparse tensor protos.
- Checker now available in C++ with Python wrapper.
- Adds Identity, Affine, ThresholdRelu, ScaledTanh, ParametricSoftplus, ImageScaler, MeanVarianceNormalization, Crop, Embedding, HardSigmoid, Mean, Clip, LogSoftmax, Hardmax, Softsign, Softplus, MatMul, InstanceNormalization, LRN, ReduceSumSquare, ReduceLogSum, ReduceL1, ReduceL2, RNN, GRU, LSTM, SpaceToDepth, DepthToSpace, Tile.
- Adds And, Or, Xor, Greater, Less, Equal, Not.
- Removes Caffe2ConvTranspose, SpatialBN, LRN, ChannelShuffle, RecurrentNetwork.
- Replaces Normalization with LpNormalization.
- Adds type constraints.
- Much improved tests for operators and reporting.