InfiniTensor/README.md

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# InfiniTensor
[中文项目简介](/README_CN.md) | Documentation | [中文文档](/docs/INDEX.md)
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InfiniTensor is a high-performance inference engine tailored for GPUs and AI accelerators. Its design focuses on effective deployment and swift academic validation.
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## Get started
### Make Commands
- `make`/`make build`: Builds the project;
- `make install-python`: Builds the project then install the python frontend;
- `make test-cpp`: Builds the project then run cpp unit tests;
- `make test-onnx`: Run python unit tests;
---
Dev for 202303ddl (#66) * add activation operatiopn relu, tanh, sigmoid on mlu * commit for format * add activation backward operation * add test for activation_backward * add test * add convbpfilter * fix * add transpsoe code and test * add trigon function operation on mlu: sin,cos,tan,asin,sinh,asinh * add copy operation on mlu * add ceil operation and floor operation * add operation clip * add operation cnnl div, test and test for divdemo bangc kernel * add divnonan operation and test * add erf operation * add exp operation * add operation fill * add log operation * add log1p operation * add l2loss operation * add maximum and minimum operation * add mseloss operation * add negTensor operation * add power operation * add reciprocal operation * add sqrt and rsqrt operation * add transform operation * add addn operation * add muln operation * cherrry pick some operation * add floordiv operation and floordivtrunc operation * add floormod operation * add cumsum operation * add det operation * add pad operation * format * add concat operation * format * add split operation * fix concat and split operation * add round operation * add pooling operation * add square operation * add squaredDifference operation * code format fix * add flip operation * code format fix * add hardtanh operation * add logic operation * add addcdiv and addcmul operation * add arange operation * add bitcompute operation * add net test * fmt Signed-off-by: YdrMaster <ydrml@hotmail.com> * style: rename Signed-off-by: YdrMaster <ydrml@hotmail.com> * fix: 用 NativeCpuRuntime 替换 CpuRuntime Signed-off-by: YdrMaster <ydrml@hotmail.com> * fix code * fix code * fix code by review suggestion * remove operation which is not the onnx operation * fix format * clang format * refactor: tensor 的 print 加一层模板的 dataToString Signed-off-by: YdrMaster <ydrml@hotmail.com> * fix: onnx 导出 Signed-off-by: YdrMaster <ydrml@hotmail.com> * feat: 增加计算图优化接口 Signed-off-by: YdrMaster <ydrml@hotmail.com> * add clip operation * feat: 支持导入 clip Signed-off-by: YdrMaster <ydrml@hotmail.com> * test: 导入导出测试加入 ci Signed-off-by: YdrMaster <ydrml@hotmail.com> * fix batch norm * feat: 增加 Shape 算子 Signed-off-by: YdrMaster <ydrml@hotmail.com> * feat: 支持导入 unsqueeze Signed-off-by: YdrMaster <ydrml@hotmail.com> * fix: 修正 clip 接口 feat: 支持导入 transpose Signed-off-by: YdrMaster <ydrml@hotmail.com> * add broadcast operation * fix elementwise-broadcast * fix elementwise broadcast * add broadcast for gpu elementsie * feat: pad 支持 axes 负数 feat: 不支持的 padding 导出为独立的 pad 算子 feat: 支持导入 onnxsim 过的 inception Signed-off-by: YdrMaster <ydrml@hotmail.com> * fix: 修正池化的测试 Signed-off-by: YdrMaster <ydrml@hotmail.com> * feat: 导出 pads,支持 inception 导入导出,已加入 ci Signed-off-by: YdrMaster <ydrml@hotmail.com> * feat: 支持 densenet 导入导出,并加入 ci Signed-off-by: YdrMaster <ydrml@hotmail.com> * feat: 导入 squeeze Signed-off-by: YdrMaster <ydrml@hotmail.com> * fix softmax * feat: 导出 clip 和 transpose Signed-off-by: YdrMaster <ydrml@hotmail.com> * feat: 支持 Conv 的 bias Signed-off-by: YdrMaster <ydrml@hotmail.com> * fix: bias of conv Signed-off-by: YdrMaster <ydrml@hotmail.com> * fix: bias of conv Signed-off-by: YdrMaster <ydrml@hotmail.com> * feat: 导入 split Signed-off-by: YdrMaster <ydrml@hotmail.com> * feat: 导出 split Signed-off-by: YdrMaster <ydrml@hotmail.com> * fix: conv Signed-off-by: YdrMaster <ydrml@hotmail.com> * fix: conv group Signed-off-by: YdrMaster <ydrml@hotmail.com> * fix: matmul 的 bias 没有放在输入里,修正 Signed-off-by: YdrMaster <ydrml@hotmail.com> * fix exmaple * fix: 改正 reduce_mean 导出 Signed-off-by: YdrMaster <ydrml@hotmail.com> * refactor: 修改 slice 实现与 onnx 一致 Signed-off-by: YdrMaster <ydrml@hotmail.com> * style: 不导出两个 runtime 函数 Signed-off-by: YdrMaster <ydrml@hotmail.com> * doc: 中文使用指南 Signed-off-by: YdrMaster <ydrml@hotmail.com> * doc: 补全指南 Signed-off-by: YdrMaster <ydrml@hotmail.com> * fix: 修复导入数据的问题 Signed-off-by: YdrMaster <ydrml@hotmail.com> * fmt Signed-off-by: YdrMaster <ydrml@hotmail.com> * feat: 添加 Dropout 基本结构,但不支持两个输出是不同的类型 Signed-off-by: YdrMaster <ydrml@hotmail.com> * feat: 重新导出优化接口 feat: dropout 导入 Signed-off-by: YdrMaster <ydrml@hotmail.com> * build: BANG 选项加入 Makefile Signed-off-by: YdrMaster <ydrml@hotmail.com> * fxi code, change of test/kernels/bang/test* is use NativeCpuRuntime. chaneg of include/bang/bang_runtime is for the cntoolkit upgrade. * feat: 导出 bang runtime Signed-off-by: YdrMaster <ydrml@hotmail.com> * add USE_BANG=1 * fix matmul * fix reshape * fix * fix activation * fix transpose * format * format * update Makefile Signed-off-by: YdrMaster <ydrml@hotmail.com> * feat: 支持导入导出 ConvTranspose Signed-off-by: YdrMaster <ydrml@hotmail.com> * add prelu on mlu * fix: ConvTranspose Signed-off-by: YdrMaster <ydrml@hotmail.com> * feat: 支持导入导出 PRelu Signed-off-by: YdrMaster <ydrml@hotmail.com> * add convtrans on mlu * fmt Signed-off-by: YdrMaster <ydrml@hotmail.com> * docs: 更新 README_CN.md Signed-off-by: YdrMaster <ydrml@hotmail.com> * fix code by review suggestions * style Signed-off-by: YdrMaster <ydrml@hotmail.com> * fix: Softmax 的 axis 可以用默认值?感觉是 onnx 不标准 Signed-off-by: YdrMaster <ydrml@hotmail.com> * fix cuda & intelcpu bugs after merging --------- Signed-off-by: YdrMaster <ydrml@hotmail.com> Co-authored-by: wanghailu <wanghailu0717@163.com> Co-authored-by: wanghailu <wanghailu@qiyuanlab.com> Co-authored-by: whjthu <haojie0429@gmail.com>
2023-04-18 15:10:33 +08:00
> - Sets env: `TEST=OFF` to accelerate compiling.
> - Sets env: `CUDA=ON` to enable cuda.
> - Sets env: `BANG=ON` to enable bang.
### CMake Options
There are several configurable CMake options, see the [CMakeLists.txt](/CMakeLists.txt#L5) file.
- If `USE_BACKTRACE` is `ON`, `libdw-dev` have to be installed. See the README of [backward-cpp](https://github.com/bombela/backward-cpp) for details.
- If `USE_PROTOBUF` is `ON`, `protobuf` have to be installed. See the README of [protobuf](https://github.com/protocolbuffers/protobuf) for details.
- If `USE_CUDA` is `ON`, `cuda` have to be installed.
## Roadmap
- [EinNet](https://github.com/InfiniTensor/InfiniTensor/tree/NNET_e2e) is going to be merged into the main branch.
- Integration of [PET](https://github.com/thu-pacman/PET), a tensor program optimizer supporting partially equivalent transformations.
- Supported hardware
- ✔ NVIDIA GPU
- ✔ Cambricon MLU
- ⬜ Ascend NPU
- ⬜ Kunlunxin XPU
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## Contributor Guide
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InfiniTensor development is based on the pull request on Github. Before requesting for merging, a PR should satisfy the following requirements
1. Pass all tests.
1. Now CI on Github will test everything that can be tested in the ci environment, including code format. So, script `test/script/clang_format_inplace.sh` is for formatting all code.
2. Contributors should run `ctest` manually and copy its output to the PR. Use fenced code blocks (triple backquotes, i.e., `` ``` ``) to avoid referencing in Github. Otherwise, `#` in the output is interpreted as a Github reference. Do not directly paste the ctest output in commit messages either for the same reason.
2. Receive at least one approval from reviewers.
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3. PR title should be concise since it is going to be the commit message in the main branch after merging and squashing.
## Reference
Please cite EinNet or PET in your publications if it helps your research:
```
@article{zheng2023einnet,
title={EINNET: Optimizing Tensor Programs with Derivation-Based Transformations},
author={Zheng, Liyan and Wang, Haojie and Zhai, Jidong and Hu, Muyan and Ma, Zixuan and Wang, Tuowei and Huang, Shuhong and Miao, Xupeng and Tang, Shizhi and Huang, Kezhao and Jia, Zhihao},
booktitle={17th USENIX Symposium on Operating Systems Design and Implementation (OSDI 23)},
pages={739--755},
year={2023}
}
@inproceedings{wang2021pet,
title={PET: Optimizing tensor programs with partially equivalent transformations and automated corrections},
author={Wang, Haojie and Zhai, Jidong and Gao, Mingyu and Ma, Zixuan and Tang, Shizhi and Zheng, Liyan and Li, Yuanzhi and Rong, Kaiyuan and Chen, Yuanyong and Jia, Zhihao},
booktitle={15th USENIX Symposium on Operating Systems Design and Implementation (OSDI 21)},
pages={37--54},
year={2021}
}
```