├── .gitignore ├── sandbox ├── notebooks │ └── models │ │ ├── pretrained_VGG10_w8a8_20.pth │ │ └── pretrained_VGG10_w8a8_20_export.onnx ├── Dockerfile └── run-docker.sh ├── submission_form.txt ├── README.md └── LICENSE /.gitignore: -------------------------------------------------------------------------------- 1 | sandbox/notebooks/.ipynb_checkpoints 2 | -------------------------------------------------------------------------------- /sandbox/notebooks/models/pretrained_VGG10_w8a8_20.pth: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Xilinx/brevitas-radioml-challenge-21/HEAD/sandbox/notebooks/models/pretrained_VGG10_w8a8_20.pth -------------------------------------------------------------------------------- /sandbox/notebooks/models/pretrained_VGG10_w8a8_20_export.onnx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Xilinx/brevitas-radioml-challenge-21/HEAD/sandbox/notebooks/models/pretrained_VGG10_w8a8_20_export.onnx -------------------------------------------------------------------------------- /submission_form.txt: -------------------------------------------------------------------------------- 1 | ### INFO ### 2 | The format for the submission must be a zipfile including: 3 | - This filled out form 4 | - Full source code for end-to-end reproducibility 5 | - Dockerfile-based environment setup 6 | (we suggest to base your submission on this sandbox repository) 7 | - Exported .onnx model with batch size = 1 8 | - Trained .pth checkpoint 9 | 10 | ### FILL IN ### 11 | # Overall test accuracy reached: 12 | -> 13 | 14 | # Inference cost score reached: 15 | -> 16 | 17 | # Complete output dictionary printed by the inference_cost() function: 18 | -> 19 | 20 | # Path to .onnx model within this zipfile: 21 | -> 22 | 23 | # Path to .pth checkpoint within this zipfile: 24 | -> 25 | 26 | # Link to GitHub repository containing your code 27 | # (to be made public after submission deadline): 28 | -> 29 | 30 | # Instructions for reproduction: 31 | -> 32 | 33 | # Further comments: 34 | -> 35 | -------------------------------------------------------------------------------- /sandbox/Dockerfile: -------------------------------------------------------------------------------- 1 | # Copyright 2021 Xilinx 2 | # Licensed under the Apache License, Version 2.0 (the "License"); 3 | # you may not use this file except in compliance with the License. 4 | # You may obtain a copy of the License at 5 | # 6 | # http://www.apache.org/licenses/LICENSE-2.0 7 | # 8 | # Unless required by applicable law or agreed to in writing, software 9 | # distributed under the License is distributed on an "AS IS" BASIS, 10 | # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 11 | # See the License for the specific language governing permissions and 12 | # limitations under the License. 13 | 14 | FROM pytorch/pytorch:1.7.1-cuda11.0-cudnn8-runtime 15 | 16 | # Alternative base images 17 | #FROM pytorch/pytorch:1.8.0-cuda11.1-cudnn8-runtime 18 | #FROM pytorch/pytorch:1.6.0-cuda10.1-cudnn7-runtime 19 | 20 | LABEL maintainer="Yaman Umuroglu " 21 | ARG GID 22 | ARG GNAME 23 | ARG UNAME 24 | ARG UID 25 | ARG PASSWD 26 | 27 | WORKDIR /workspace 28 | 29 | RUN apt-get update 30 | RUN apt-get -y upgrade 31 | RUN apt-get install -y build-essential 32 | RUN apt-get install -y libglib2.0-0 33 | RUN apt-get install -y libsm6 34 | RUN apt-get install -y libxext6 35 | RUN apt-get install -y libxrender-dev 36 | RUN apt-get install -y nano 37 | RUN apt-get install -y zsh 38 | RUN apt-get install -y rsync 39 | RUN apt-get install -y git 40 | RUN apt-get install -y sshpass 41 | RUN apt-get install -y wget 42 | RUN apt-get install -y unzip 43 | RUN apt-get install -y zip 44 | RUN echo "StrictHostKeyChecking no" >> /etc/ssh/ssh_config 45 | 46 | RUN pip install future==0.18.2 47 | RUN pip install numpy==1.18.0 48 | RUN pip install scipy==1.5.2 49 | RUN pip install ipykernel==5.5.5 50 | RUN pip install jupyter==1.0.0 51 | RUN pip install matplotlib==3.3.1 --ignore-installed 52 | RUN pip install netron>=4.7.9 53 | RUN pip install pandas==1.1.5 54 | RUN pip install scikit-learn==0.24.1 55 | RUN pip install tqdm==4.61.1 56 | RUN pip install dill==0.3.3 57 | RUN pip install brevitas==0.6.0 58 | RUN pip install onnxoptimizer==0.2.6 59 | RUN pip install git+https://github.com/Xilinx/finn-base.git@feature/itu_competition_21#egg=finn-base[onnx] 60 | RUN pip install versioned-hdf5 61 | 62 | # switch user 63 | RUN groupadd -g $GID $GNAME 64 | RUN useradd -M -u $UID $UNAME -g $GNAME 65 | RUN usermod -aG sudo $UNAME 66 | RUN echo "$UNAME:$PASSWD" | chpasswd 67 | RUN echo "root:$PASSWD" | chpasswd 68 | RUN chown -R $UNAME:$GNAME /workspace 69 | RUN ln -s /workspace /home/$UNAME 70 | USER $UNAME 71 | 72 | WORKDIR /home/$UNAME/sandbox 73 | 74 | CMD ["bash"] 75 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Sandbox: Lightning-Fast Modulation Classification with Hardware-Efficient Neural Networks 2 | 3 | This repository provides a Docker-based environment to get started with the [Lightning-Fast Modulation Classification with Hardware-Efficient Neural Networks](https://challenge.aiforgood.itu.int/match/matchitem/34) problem statement of the [**ITU AI/ML in 5G Challenge**](https://aiforgood.itu.int/ai-ml-in-5g-challenge/). The sandbox environment includes PyTorch and Brevitas and serves a Jupyter notebook that guides you through definition, training, and evaluation of an exemplary quantized CNN model. 4 | 5 | ## Prerequisites 6 | 7 | The sandbox was tested on Ubuntu, but the containerized setup should work on most platforms. 8 | 9 | - Install Docker Engine 10 | - Convenient install script: [get.docker.com](https://get.docker.com) 11 | - Full installation instructions: [docs.docker.com/engine/install/](https://docs.docker.com/engine/install/) 12 | - To use docker without `sudo` you should follow these [instructions](https://docs.docker.com/engine/install/linux-postinstall/) to add your user to the `docker group` 13 | - Optional steps to enable GPU-accelerated training (recommended) 14 | - Install current NVIDIA driver 15 | - Install NVIDIA Container Toolkit, see instructions here: [github.com/NVIDIA/nvidia-docker](https://github.com/NVIDIA/nvidia-docker) 16 | 17 | ## Using the sandbox notebook 18 | 19 | 1. Clone this repository 20 | 2. Set optional environment variables 21 | - `DATASET_DIR`: This directory will be mounted inside the container at "/workspace/dataset", download instructions can be found inside the Jupyter notebook 22 | - `DOCKER_GPUS`: Select GPUs which will be accessible from within the container, for example `all` or `device=0` 23 | - `JUPYTER_PORT`: Override default port (8888) 24 | - `NETRON_PORT`: Override default port (8081) 25 | - `JUPYTER_PASSWD_HASH`: Override default password ("radioml") 26 | - `LOCALHOST_URL`: Set the IP/URL of the machine if you don't access it via `localhost` 27 | 3. Run `./run_docker.sh` inside `sandbox/` to launch the Jupyter notebook server 28 | - Alternatively for experimenting: Run `./run_docker.sh bash` to launch an interactive shell 29 | 4. Connect to `http://HOSTNAME:JUPYTER_PORT` from a browser and login with password "radioml" 30 | 31 | ## Getting help 32 | Connect with the challenge organizers and other participants on [GitHub discussion](https://github.com/Xilinx/brevitas-radioml-challenge-21/discussions). For questions related to quantization-aware training with Brevitas, there is also a separate Gitter channel: [![Gitter](https://badges.gitter.im/xilinx-brevitas/community.svg)](https://gitter.im/xilinx-brevitas/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge) 33 | -------------------------------------------------------------------------------- /sandbox/run-docker.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | # Copyright 2021 Xilinx 3 | # Licensed under the Apache License, Version 2.0 (the "License"); 4 | # you may not use this file except in compliance with the License. 5 | # You may obtain a copy of the License at 6 | # 7 | # http://www.apache.org/licenses/LICENSE-2.0 8 | # 9 | # Unless required by applicable law or agreed to in writing, software 10 | # distributed under the License is distributed on an "AS IS" BASIS, 11 | # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12 | # See the License for the specific language governing permissions and 13 | # limitations under the License. 14 | 15 | GREEN='\033[0;32m' 16 | RED='\033[0;31m' 17 | YELLOW='\033[0;33m' 18 | NC='\033[0m' # No Color 19 | # green echo 20 | gecho () { 21 | echo -e "${GREEN}$1${NC}" 22 | } 23 | # red echo 24 | recho () { 25 | echo -e "${RED}$1${NC}" 26 | } 27 | # yellow echo 28 | yecho () { 29 | echo -e "${YELLOW}$1${NC}" 30 | } 31 | 32 | DOCKER_GID=$(id -g) 33 | DOCKER_GNAME=$(id -gn) 34 | DOCKER_UNAME=$(id -un) 35 | DOCKER_UID=$(id -u) 36 | DOCKER_PASSWD="sandbox" 37 | # generate a random number per-run to allow multiple 38 | # containers from the same user 39 | DOCKER_RND=$(shuf -i0-32768 -n1) 40 | DOCKER_TAG="sandbox_${DOCKER_UNAME}" 41 | DOCKER_INST_NAME="sandbox_${DOCKER_UNAME}" 42 | # ensure Docker tag and inst. name are all lowercase 43 | DOCKER_TAG=$(echo "$DOCKER_TAG" | tr '[:upper:]' '[:lower:]') 44 | DOCKER_INST_NAME=$(echo "$DOCKER_INST_NAME" | tr '[:upper:]' '[:lower:]') 45 | # Absolute path to this script, e.g. /home/user/bin/foo.sh 46 | SCRIPT=$(readlink -f "$0") 47 | # Absolute path this script is in, thus /home/user/bin 48 | SCRIPTPATH=$(dirname "$SCRIPT") 49 | 50 | # the settings below will be taken from environment variables if available, 51 | # otherwise the defaults below will be used 52 | : ${JUPYTER_PORT=8888} 53 | : ${JUPYTER_PASSWD_HASH=sha1:a8165c509d95:e3d55958f35e77b8565d0c38a7cca31d7a0e2c3b} # "radioml" 54 | : ${NETRON_PORT=8081} 55 | : ${LOCALHOST_URL="localhost"} 56 | : ${DATASET_DIR=""} 57 | : ${DOCKER_GPUS=""} 58 | 59 | DOCKER_INTERACTIVE="" 60 | DOCKER_EXTRA="" 61 | 62 | if [ "$1" = "bash" ]; then 63 | gecho "Running container only" 64 | DOCKER_CMD="bash" 65 | DOCKER_INTERACTIVE="-it" 66 | else 67 | gecho "Running Jupyter notebook server" 68 | if [ -z "$JUPYTER_PASSWD_HASH" ]; then 69 | JUPYTER_PASSWD_ARG="" 70 | else 71 | JUPYTER_PASSWD_ARG="--NotebookApp.password=$JUPYTER_PASSWD_HASH" 72 | fi 73 | DOCKER_CMD="jupyter notebook --no-browser --ip=0.0.0.0 --port $JUPYTER_PORT $JUPYTER_PASSWD_ARG notebooks" 74 | DOCKER_EXTRA+="-e JUPYTER_PORT=$JUPYTER_PORT " 75 | DOCKER_EXTRA+="-e NETRON_PORT=$NETRON_PORT " 76 | DOCKER_EXTRA+="-p $JUPYTER_PORT:$JUPYTER_PORT " 77 | DOCKER_EXTRA+="-p $NETRON_PORT:$NETRON_PORT " 78 | fi 79 | 80 | # Build the sandbox Docker image 81 | # Need to ensure this is done within the root folder: 82 | gecho "Building Docker image.." 83 | OLD_PWD=$(pwd) 84 | cd $SCRIPTPATH 85 | docker build -f Dockerfile --tag=$DOCKER_TAG \ 86 | --build-arg GID=$DOCKER_GID \ 87 | --build-arg GNAME=$DOCKER_GNAME \ 88 | --build-arg UNAME=$DOCKER_UNAME \ 89 | --build-arg UID=$DOCKER_UID \ 90 | --build-arg PASSWD=$DOCKER_PASSWD \ 91 | . 92 | cd $OLD_PWD 93 | 94 | # Launch container with current directory mounted 95 | DOCKER_EXEC="docker run -t --rm $DOCKER_INTERACTIVE --init " 96 | DOCKER_EXEC+="--hostname $DOCKER_INST_NAME " 97 | DOCKER_EXEC+="-e SHELL=/bin/bash " 98 | DOCKER_EXEC+="-v $SCRIPTPATH:/workspace/sandbox " 99 | 100 | # Increase shared memory size for multithreaded dataloading 101 | DOCKER_EXEC+="--shm-size=256m " 102 | 103 | gecho "Docker container is named $DOCKER_INST_NAME" 104 | gecho "Port-forwarding for Jupyter $JUPYTER_PORT:$JUPYTER_PORT" 105 | gecho "Port-forwarding for Netron $NETRON_PORT:$NETRON_PORT" 106 | gecho "Mounting $SCRIPTPATH at /workspace/sandbox" 107 | 108 | # mount dataset 109 | if [[ "$DATASET_DIR" != "" ]]; then 110 | DOCKER_EXEC+="-v $DATASET_DIR:/workspace/dataset " 111 | gecho "Mounting $DATASET_DIR at /workspace/dataset" 112 | else 113 | yecho "Not set: DATASET_DIR to mount" 114 | fi 115 | 116 | # expose selected GPUs 117 | if [[ "$DOCKER_GPUS" != "" ]]; then 118 | DOCKER_EXEC+="--gpus $DOCKER_GPUS " 119 | gecho "Exposing GPU(s): $DOCKER_GPUS" 120 | else 121 | yecho "Not set: DOCKER_GPUS to expose" 122 | fi 123 | 124 | DOCKER_EXEC+="-e LOCALHOST_URL=$LOCALHOST_URL " 125 | DOCKER_EXEC+="$DOCKER_EXTRA " 126 | DOCKER_EXEC+="$DOCKER_TAG $DOCKER_CMD" 127 | 128 | $DOCKER_EXEC 129 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | Apache License 2 | Version 2.0, January 2004 3 | http://www.apache.org/licenses/ 4 | 5 | TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 6 | 7 | 1. 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