diff options
Diffstat (limited to 'docs')
-rw-r--r-- | docs/conf.py | 2 | ||||
-rw-r--r-- | docs/howto/how-to-build-runtime-tizen-gbs-rpi4.md | 18 | ||||
-rw-r--r-- | docs/release/1.20/index.rst | 13 | ||||
-rw-r--r-- | docs/release/1.20/release-note-1.20.0.md | 34 | ||||
-rw-r--r-- | docs/release/1.21/index.rst | 13 | ||||
-rw-r--r-- | docs/release/1.21/release-note_1.21.0.md | 35 |
6 files changed, 101 insertions, 14 deletions
diff --git a/docs/conf.py b/docs/conf.py index 84197e6d6..409e5f79b 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -21,7 +21,7 @@ copyright = '2020, Samsung Research & contributors' author = 'Samsung Research & contributors' # The full version, including alpha/beta/rc tags -release = '1.20.0' +release = '1.21.0' # -- General configuration --------------------------------------------------- diff --git a/docs/howto/how-to-build-runtime-tizen-gbs-rpi4.md b/docs/howto/how-to-build-runtime-tizen-gbs-rpi4.md index 1f8c0c289..57b2b787c 100644 --- a/docs/howto/how-to-build-runtime-tizen-gbs-rpi4.md +++ b/docs/howto/how-to-build-runtime-tizen-gbs-rpi4.md @@ -174,34 +174,26 @@ $ vi j2/etc/systemd/system/ip.service and set as like: ``` [Service] -Type=simple Restart=always RestartSec=1 User=root -ExecStart=/bin/sh /bin/ip.sh +ExecStart=/bin/sh -c "ifconfig eth0 192.168.x.y netmask 255.255.255.0 up" [Install] WantedBy=multi-user.target ``` +Replace 192.168.x.y to your actual ip address. -(5-3) Add a new file -``` -$ vi j2/bin/ip.sh -``` -and set with IP address for your RPi4: -``` -ifconfig eth0 192.168.x.y netmask 255.255.255.0 up -``` -where you should update `192.168.x.y` part to your actual IP address. -(5-4) Add a symbolic link +(5-3) Add a symbolic link ``` +$ sudo mkdir -p j2/etc/systemd/system/multi-user.target.wants/ $ pushd j2/etc/systemd/system/multi-user.target.wants/ $ sudo ln -s ../../system/ip.service . $ popd ``` -(5-5) Now that every thing is ready, unmount and unplug your memory card and plug into +(5-4) Now that every thing is ready, unmount and unplug your memory card and plug into RPi4, turn on the power. ``` $ sync diff --git a/docs/release/1.20/index.rst b/docs/release/1.20/index.rst new file mode 100644 index 000000000..082d867f3 --- /dev/null +++ b/docs/release/1.20/index.rst @@ -0,0 +1,13 @@ +.. ONE documentation master file, created by + sphinx-quickstart on Tue Apr 26 10:18:12 2022. + You can adapt this file completely to your liking, but it should at least + contain the root `toctree` directive. + +1.20 +==== + +.. toctree:: + :maxdepth: 2 + :caption: Contents: + + ./release-note-1.20.0.md diff --git a/docs/release/1.20/release-note-1.20.0.md b/docs/release/1.20/release-note-1.20.0.md new file mode 100644 index 000000000..2c75e06af --- /dev/null +++ b/docs/release/1.20/release-note-1.20.0.md @@ -0,0 +1,34 @@ +# Release Note 1.20.0 + +## ONE Compiler + +### Compiler Frontend + +- luci-interpreter supports multiple kernels with PAL layer including Cortext-M +- luci-interpreter supports integer tensor for partly kernels +- luci import support constant without coping to reduce memory for luci-interpreter +- Reduce duplicate codes to package released modules +- Limited support for ONNX LSTM/RNN unrolling while importing +- Limited support for ARM32 cross build +- Support new operator: SVDF +- New virtual CircleVariable to support tensor with variable +- Support quantization of BatchMatMul Op +- Support mixed(UINT8 + INT16) quantization +- Support backward propagation of quantization parameters +- Upgrade default python to version 3.8 +- Support TensorFlow 2.8.0, ONNX-TF 1.10.0, ONNX 1.11.0 +- Upgrade circle schema to follow tflite schema v3b +- Refactor to mio-tflite280, mio-circle04 with version and helpers methods +- Use one flatbuffers 2.0 version +- Drop support for TensorFlow 1.x +- Fix for several bugs, performance enhancements, and typos + +## ONE Runtime + +### Introduce TRIX backend +- TRIX backend supports trix binary with NHWC layout +- TRIX backend supports trix binary with input/output of Q8 and Q16 type + +### API supports new data type +- Symmetric Quantized int16 type named "NNFW_TYPE_TENSOR_QUANT16_SYMM_SIGNED" + diff --git a/docs/release/1.21/index.rst b/docs/release/1.21/index.rst new file mode 100644 index 000000000..587065f56 --- /dev/null +++ b/docs/release/1.21/index.rst @@ -0,0 +1,13 @@ +.. 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 +==== + +.. toctree:: + :maxdepth: 2 + :caption: Contents: + + ./release-note-1.21.0.md diff --git a/docs/release/1.21/release-note_1.21.0.md b/docs/release/1.21/release-note_1.21.0.md new file mode 100644 index 000000000..49bf074b6 --- /dev/null +++ b/docs/release/1.21/release-note_1.21.0.md @@ -0,0 +1,35 @@ +# Release Note 1.21.0 + +## ONE Compiler + +- 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 + +## ONE Runtime + +### Basic Multimodel nnpackage +- Runtime supports to run nnpackage with two models + +### Channel Wise Quantization on Conv2D and Depthwise Conv2D +- Conv2D and Depthwise Conv2D supports per-channel quantization of uint8 type. + +### Batch Execution with TRIX backend +- TRIX backend supports batch execution which run in parallel with multicore + |