add spconv docker weekly build

.github/build.yaml

+name: build
+
+on:
+  push:
+    branches:
+      - master
+  schedule:
+    # * is a special character in YAML so you have to quote this string
+    - cron:  '0 0 * * 6' # base builds run every saturday
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+    env:
+      DOCKER_IMAGE_NAME: scrin/dev-spconv
+      DOCKER_FILE_PATH: ./Dockerfile
+
+    # TODO: create a action to reuse code. the problem is how to reuse docker-login.
+    steps:
+      - uses: actions/checkout@master
+      - name: Build Docker
+        run: |
+          docker build . --file ${{env.DOCKER_FILE_PATH}} --tag ${{env.DOCKER_IMAGE_NAME}}:latest
+          docker tag ${{env.DOCKER_IMAGE_NAME}}:latest ${{env.DOCKER_IMAGE_NAME}}:${{ github.sha }}
+          
+
+      - name: Login to Registry
+        uses: azure/docker-login@v1
+        with:
+          username: ${{ secrets.DOCKER_USERNAME }}
+          password: ${{ secrets.DOCKER_PASSWORD }}
+
+      - name: Publish to Registry
+        run: |
+          docker push ${{env.DOCKER_IMAGE_NAME}}:latest
+          docker push ${{env.DOCKER_IMAGE_NAME}}:${{ github.sha }}

Dockerfile

+FROM scrin/dev:latest
+
+RUN cd /root && \
+    git clone --depth 1 --recurive https://www.github.com/traveller59/spconv.git && \
+    cd ./spconv && \
+    python setup.py install

README.md

 # SpConv: PyTorch Spatially Sparse Convolution Library
 
+[![Build Status](https://github.com/traveller59/spconv/workflows/build/badge.svg)](https://github.com/traveller59/spconv/actions?query=workflow%3Abuild)
+
 This is a spatially sparse convolution library like [SparseConvNet](https://github.com/facebookresearch/SparseConvNet) but faster and easy to read. This library provide sparse convolution/transposed, submanifold convolution, inverse convolution and sparse maxpool.
 
 The GPU Indice Generation algorithm is a unofficial implementation of paper [SECOND](http://www.mdpi.com/1424-8220/18/10/3337). That algorithm (don't include GPU SubM indice generation algorithm) may be protected by patent.
@@ -12,6 +14,10 @@ This project only support tensors with spatial volume less than ```std::numeric_
 
 2019-5-24: spconv v1.1 released, now indice generation will use hash table as default (CPU code only support hash table). you can use ```use_hash=False``` to use dense table when using CUDA. In addition, add CPU only build support.
 
+## Docker:
+
+```docker pull scrin/dev-spconv```, contains python 3.8, cuda 10.1, fish shell, newest pytorch and tensorflow.
+
 ## Install on Ubuntu 16.04/18.04
 
 * if you are using pytorch 1.4+ and encounter "nvcc fatal: unknown -Wall", you need to go to torch package dir and remove flags contains "-Wall" in INTERFACE_COMPILE_OPTIONS in Caffe2Targets.cmake. This problem can't be fixed in this project (to avoid this, I need to remove all torch dependency in cuda sources and drop half support).