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deepC-0.13
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DeepC: Deep Neural Network Compiler
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | deepC-0.13 |
| نام | deepC |
| نسخه کتابخانه | 0.13 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Rohit Sharma et. al. |
| ایمیل نویسنده | rohit@find-domain-name-on-github.com |
| آدرس صفحه اصلی | https://github.com/ai-techsystems/dnnCompiler |
| آدرس اینترنتی | https://pypi.org/project/deepC/ |
| مجوز | - |
# deepC
---
[](https://travis-ci.org/ai-techsystems/dnnCompiler)
[](https://badge.fury.io/py/deepC)
[](LICENSE)
[](https://opencollective.com/dnnc)
## 🏃♂️ Using deepC
Here are few of many ways.
1. Try deepC with [Colab Noteboook](https://colab.research.google.com/drive/1EKgQcMCHr-0OsG9qJ4wXv7J4JFlPY7CK)
1. Install it on Ubuntu (or other debian derivatives) using ```pip install deepC```
1. [Compile onnx model](test/compiler/mnist/README.md)
1. Use deepC with a [Docker File](Dockerfile)
See more examples in [tutorial](tutorials/README.md) dir.
## 📛 what is deepC?
deepC Compiler and inference framework is designed to **enable and perform** deep learning neural networks by focussing on features of custom ai-accelerators like micro-controllers, eFPGAs, cpus and other embedded devices like [raspberry-pi](https://www.raspberrypi.org/), [odroid](https://www.hardkernel.com/), [arduino](https://www.arduino.cc/), [SparkFun Edge](https://www.sparkfun.com/products/15170), [risc-V](https://www.amazon.com/Seeed-Studio-Sipeed-Maixduino-RISC-V/dp/B07SW9ZWQQ) and others.
deepC also offers ahead of time compiler producing optimized executable based on [LLVM compiler tool chain](https://llvm.org/) specialized for deep neural networks with [ONNX](https://onnx.ai/) as front end.
## 📝 Design
Main components of **deepC** have been designed to represent and optimize the common deep learning networks in high level graph IR and to transform the computation graph to minimize memory utilization, optimize data layout and fuse computation patterns for different hardware backends.
<img width="800" alt="Architecture" src="https://github.com/ai-techsystems/dnnCompiler/blob/master/misc/dnnCompilerArch.jpg">
Read more at [high level design document](docs/highLevelDesign.md)
## 💧 PreRequisites
* [ONNX 1.5](https://github.com/onnx/onnx/tree/rel-1.5.0#installation)
* [LLVM 8.0](http://releases.llvm.org/8.0.0/docs/GettingStarted.html#getting-started-quickly-a-summary)
* [Python 3.6](https://www.python.org/downloads/release/python-360/)
* [SWIG 3.0](https://sourceforge.net/projects/swig/files/swig/swig-3.0.12/)
## ⚙ Installation
build and install dnn Compiler locally from source code with following steps
### ⭕ Ubuntu 18.04
You can install ubuntu18.04 on windows [Watch HowTo video here](https://www.youtube.com/watch?v=QbmRXJJKsvs) or [Google it](https://www.google.com/search?q=how+to+setup+ubuntu+on+virtualbox&oq=how+to+setup+ubuntu+on+virtual+box)
Follow the steps to install pre-requisites
```
sudo apt-get update
sudo apt-get install build-essential python3.6-dev python3-pip swig doxygen clang-format clang clang-8 llvm-8 llvm-8-dev
sudo pip3 install numpy onnx
```
Once you are done, build dnnCompiler
```
git clone https://github.com/ai-techsystems/dnnCompiler.git
cd dnnCompiler
make
```
#### 📜 Output
```
find include src swig -name \*.h -print0 -o -name \*.cpp -print0 | xargs -0 -P8 -n1 clang-format -i
make -C src
make[1]: Entering directory 'dnnCompiler/src'
make -C core
make[2]: Entering directory 'dnnCompiler/src/core'
compiling broadcast.cpp
/usr/bin/g++ -O3 -Wall -std=c++14 -fPIC -march=native -msse2 \
-isystem ./packages/eigen-eigen-323c052e1731 -I./include \
-c broadcast.cpp -o obj/broadcast.o
compiling tensor.cpp
...
...
/usr/bin/g++ -shared ./obj/dnnc_swig.o ./obj/dnnc_pyutils.o ./obj/dnnc_api.o -o lib/libdnnc.so
ln -s -f lib/libdnnc.so _dnnc.so
/usr/bin/python3 ../test/swig/basic.py
```
## ➕ Contribute
dnn Compiler adopts apache committer model, we aim to create an open source project that is maintained and owned by the community. Checkout the Contributor Guide.
## 🙏 Acknowledgement
We acknowledge the efforts predecessor projects like [LLVM](https://llvm.org/), [ONNX](https://onnx.ai/) etc. to make this project a reality.
---
## 🕵️♂️ Why compiler❔
dnnCompiler is targeted towards devices with small formfactor like microcontrollers, which are part of all sorts of household devices: think appliances, cars, and toys. In fact, there are around 30 billion microcontroller-powered devices produced each year. They're cheap, require very little energy, and are very reliable.
By bringing deep learning models to tiny microcontrollers, we can boost the intelligence of billions of devices that we use in our lives, without relying on expensive hardware or reliable internet connections. Imagine smart appliances that can adapt to your daily routine, intelligent industrial sensors that understand the difference between problems and normal operation, and magical toys that can help kids learn in fun and delightful ways.
**🚧 Project Under Development.** *Stay tuned. We plan to release the first version in Nov. 2019.*
## Contributors
### Code Contributors
This project exists thanks to all the people who contribute. [[Contribute](CONTRIBUTING.md)].
<a href="https://github.com/ai-techsystems/dnnCompiler/graphs/contributors"><img src="https://opencollective.com/dnnc/contributors.svg?width=890&button=false" /></a>
### Financial Contributors
Become a financial contributor and help us sustain our community. [[Contribute](https://opencollective.com/dnnc/contribute)]
#### Individuals
<a href="https://opencollective.com/dnnc"><img src="https://opencollective.com/dnnc/individuals.svg?width=890"></a>
#### Organizations
Support this project with your organization. Your logo will show up here with a link to your website. [[Contribute](https://opencollective.com/dnnc/contribute)]
نیازمندی
| مقدار | نام |
|---|---|
| ==1.5.0 | onnx |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.5 | Python |
نحوه نصب
نصب پکیج whl deepC-0.13:
pip install deepC-0.13.whl
نصب پکیج tar.gz deepC-0.13:
pip install deepC-0.13.tar.gz