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* Release Note for 1.21.0 - Release Note for 1.21.0 Signed-off-by: Chunseok Lee <[email protected]> * Update docs/release/1.21/index.rst Co-authored-by: seongwoo chae <[email protected]> * Update docs/release/1.21/release-note_1.21.0.md Co-authored-by: Sanggyu Lee <[email protected]> Signed-off-by: Chunseok Lee <[email protected]> Co-authored-by: seongwoo chae <[email protected]> Co-authored-by: Sanggyu Lee <[email protected]>
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.. ONE documentation master file, created by | ||
sphinx-quickstart on Wed Sep 06 12:18:12 2022. | ||
You can adapt this file completely to your liking, but it should at least | ||
contain the root `toctree` directive. | ||
1.21 | ||
==== | ||
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.. toctree:: | ||
:maxdepth: 2 | ||
:caption: Contents: | ||
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./release-note-1.21.0.md |
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# Release Note 1.21.0 | ||
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## ONE Compiler | ||
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- Support unrolling of LSTM and RNN Ops in `one-import-onnx` tool | ||
- Introduced new tools `one-infer`, `circle-operator`, `circle-interpreter` | ||
- Introduced `Workflow`(WIP) in `one-cmds` | ||
- New option `quant_config` in `one-quantize` | ||
- New option `fake_quantize` in `one-quantize` | ||
- More Ops supported: Densify | ||
- More Ops for quantization: ReduceMax | ||
- More Ops for mixed-precision quantization (MPQ): LeakyRelu, Neg, Relu6, Squeeze | ||
- More Ops for `convert_nchw_to_nhwc` option: LogSoftmax, ReduceMax, SplitV, Softmax | ||
- New optimization options in `one-optimize`: `replace_non_const_fc_with_bmm`, `resolve_customop_splitv`, `fold_densify` | ||
- Improved reshape elimination in `convert_nchw_to_nhwc` option. | ||
- Support fusion of Channel-wise Add + Relu with TConv | ||
- Support negative axis in ArgMin/Max | ||
- Show errors for unrecognized options in `one-optimize` | ||
- Fix shape inference for `StridedSlice` | ||
- Fix FuseBatchNormWithTConvPass to support TConv with bias | ||
- Deprecate `--O1` option in `circle2circle` | ||
- Support gcc-11 | ||
- Support limited Float16 for kernels constants with dequantization to Float32 | ||
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## ONE Runtime | ||
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### Basic Multimodel nnpackage | ||
- Runtime supports to run nnpackage with two models | ||
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### Channel Wise Quantization on Conv2D and Depthwise Conv2D | ||
- Conv2D and Depthwise Conv2D supports per-channel quantization of uint8 type. | ||
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### Batch Execution with TRIX backend | ||
- TRIX backend supports batch execution which run in parallel with multicore | ||
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