quick test

Dockerfile

@@ -16,6 +16,8 @@ RUN apt update
 # base stuff
 RUN apt --yes install build-essential wget curl rpl
 
+RUN echo "Build started at: $(date "+%Y-%m-%d %H:%M")"
+
 # NodeJS - LEGACY/DEPRECATED WAY
 #RUN curl -fsSL https://deb.nodesource.com/setup_18.x | bash -
 #RUN apt --yes install nodejs
@@ -24,7 +26,7 @@ RUN apt --yes install build-essential wget curl rpl
 RUN apt --yes install -y ca-certificates gnupg
 RUN mkdir -p /etc/apt/keyrings
 RUN curl -fsSL https://deb.nodesource.com/gpgkey/nodesource-repo.gpg.key | gpg --dearmor -o /etc/apt/keyrings/nodesource.gpg
-ENV NODE_MAJOR=20
+ENV NODE_MAJOR=18
 RUN echo "deb [signed-by=/etc/apt/keyrings/nodesource.gpg] https://deb.nodesource.com/node_$NODE_MAJOR.x nodistro main" | tee /etc/apt/sources.list.d/nodesource.list
 RUN apt update
 RUN apt --yes install nodejs
@@ -68,7 +70,6 @@ RUN wget https://github.com/Kitware/CMake/releases/download/v3.24.1/cmake-3.24.1
 #RUN wget https://download.pytorch.org/libtorch/cu118/libtorch-cxx11-abi-shared-with-deps-2.0.1%2Bcu118.zip \
 # && unzip libtorch-cxx11-abi-shared-with-deps-2.0.1+cu118.zip -d external/
 
-
 # Set up a new user named "user" with user ID 1000
 RUN useradd -o -u 1000 user
 
@@ -77,7 +78,6 @@ USER user
 
 ENV PYTHON_BIN /usr/bin/python3
 
-
 #ENV PATH /usr/local/cuda-12.2/bin:$PATH
 #ENV LD_LIBRARY_PATH /usr/local/cuda-12.2/lib64:$LD_LIBRARY_PATH
 # Let's try to downgrade
@@ -106,51 +106,11 @@ RUN git clone --recursive https://github.com/MrNeRF/gaussian-splatting-cuda
 
 WORKDIR $HOME/app/gaussian-splatting-cuda
 
-RUN wget https://download.pytorch.org/libtorch/cu118/libtorch-cxx11-abi-shared-with-deps-2.0.1%2Bcu118.zip  
-RUN unzip libtorch-cxx11-abi-shared-with-deps-2.0.1+cu118.zip -d external/
-RUN rm libtorch-cxx11-abi-shared-with-deps-2.0.1+cu118.zip
-
-# Build (on CPU, this will add compute_35 as build target, which we do not want)
-# There seems to be a work around, see this thread:
-# https://github.com/MrNeRF/gaussian-splatting-cuda/issues/14
-# here is the hack:
-
-# Replace "native" by "all"
-# inspired by https://github.com/ztxz16/fastllm/pull/309/files
-#
-
-# CUDA architectures are defined as codes
-# by default CMake detected:
-# 3.5;5.0;8.0;8.6;8.9;9.0
-# To see the mapping: https://arnon.dk/matching-sm-architectures-arch-and-gencode-for-various-nvidia-cards/
-# A10G and A100 -> Ampere -> sm_80, sm_86, sm_87 -> 8.0;8.6;8.7
-# Nvidia T4 -> Turing -> sm_75 -> 7.5
-# ? -> Lovelace ->  sm_89 -> 8.6
-# ? -> Hopper -> sm_90 -> 9.0
-
-# this doesn't something, but then it still try to build for arch 3.5 / 35
-# RUN find . -name CMakeLists.txt -exec sed -i 's/CUDA_ARCHITECTURES native/CUDA_ARCHITECTURES "80;86;89;90"/' {} +
-
-RUN find . -name CMakeLists.txt -exec sed -i 's/CUDA_ARCHITECTURES native/CUDA_ARCHITECTURES all/' {} +
-
-#RUN cmake -B build -D CMAKE_BUILD_TYPE=Release -D CUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda-12.2/ -D CUDA_VERSION=12.2
-# Let's try to downgrade the version
-RUN cmake -B build -D CMAKE_BUILD_TYPE=Release -D CUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda-11.8/ -D CUDA_VERSION=11.8
-
-RUN ls -la build/
-RUN ls -la build/external/
-RUN ls -la build/CMakeFiles
-
-# we actually cannot generate for "all" architectures: compute_35 is not supported anymore
-# RUN find . -name CMakeLists.txt -exec sed -i 's/-gencode arch=compute_35,code=sm_35//' {} +
-
-RUN cmake --build build -- -j8
+# for quick testing we disabled the rest
 
 COPY --chown=user . $HOME/app/gaussian-splatting-cuda
 
-# do we need to copy cuda over? I don't think so?
-#WORKDIR /usr/local/cuda-12.2
-#COPY --chown=user . $HOME/app/cuda-12.2
+RUN echo "Build ended at: $(date "+%Y-%m-%d %H:%M")"
 
 EXPOSE 7860
 

README.md

@@ -7,3 +7,28 @@ sdk: docker
 pinned: true
 app_port: 3000
 ---
+
+## Presentation
+
+### What is this project?
+
+Gaussian Splatting API is a REST API to generate 3D Gaussian Splatting scenes from a set of images.
+
+### What is the licence?
+
+## Running on your machine
+
+### Prerequisites
+
+You need a machine with CUDA, a GPU etc
+
+### Environment variables
+
+- `STORAGE_PATH`: on HF use `/data`, on a local you can use `.sandbox/`
+
+### Deployment to Hugging Face
+
+This can take some time.
+
+note: this is a long build (~30 min)
+

src/config.mts

@@ -2,7 +2,8 @@ import path from "node:path"
 
 export const storagePath = `${process.env.STORAGE_PATH || './sandbox'}`
 
-export const postDirFilePath = path.join(storagePath, "posts")
+export const inputsDirFilePath = path.join(storagePath, "training_inputs")
+export const outputsDirFilePath = path.join(storagePath, "training_outputs")
 
 export const shotFormatVersion = 1
 export const sequenceFormatVersion = 1

src/index.mts

@@ -7,12 +7,15 @@ initFolders()
 const app = express()
 const port = 7860
 
-// fix this error: "PayloadTooLargeError: request entity too large"
-// there are multiple version because.. yeah well, it's Express!
-// app.use(bodyParser.json({limit: '50mb'}));
-//app.use(bodyParser.urlencoded({limit: '50mb', extended: true}));
-app.use(express.json({limit: '50mb'}));
-app.use(express.urlencoded({limit: '50mb', extended: true}));
+const queue = []
+const queueLimit = 4
+
+app.use(express.json({limit: '50mb'}))
+app.use(express.urlencoded({limit: '50mb', extended: true}))
+
+app.post("/", async (req, res) => {
+  // TODO
+})
 
 app.get("/", async (req, res) => {
   // this is what users will see in the space - but no need to show something scary

src/initFolders.mts

@@ -1,12 +1,11 @@
 import {
-  postDirFilePath
+  inputsDirFilePath,
+  outputsDirFilePath,
 } from "./config.mts"
 import { createDirIfNeeded } from "./utils/createDirIfNeeded.mts"
 
 export const initFolders = () => {
-
-  console.log("no new folder to create")
-  
- //  console.log(`initializing folders..`)
-  // createDirIfNeeded(postDirFilePath)
+  console.log(`initializing folders..`)
+  createDirIfNeeded(inputsDirFilePath)
+  createDirIfNeeded(outputsDirFilePath)
 }

tmp.txt

@@ -0,0 +1,144 @@
+#FROM nvidia/cuda:12.2.0-devel-ubuntu20.04
+# let's try to downgrade the version of CUDA
+FROM nvidia/cuda:11.8.0-devel-ubuntu20.04
+
+LABEL maintainer="Hugging Face"
+
+ARG DEBIAN_FRONTEND=noninteractive
+
+# Use login shell to read variables from `~/.profile` (to pass dynamic created variables between RUN commands)
+SHELL ["sh", "-lc"]
+
+# WORKDIR /workdir
+
+RUN apt update
+
+# base stuff
+RUN apt --yes install build-essential wget curl rpl
+
+RUN echo "Build started at: $(date "+%Y-%m-%d %H:%M")"
+
+# NodeJS - LEGACY/DEPRECATED WAY
+#RUN curl -fsSL https://deb.nodesource.com/setup_18.x | bash -
+#RUN apt --yes install nodejs
+
+# NodeJS - NEW, MORE ANNOYING WAY
+RUN apt --yes install -y ca-certificates gnupg
+RUN mkdir -p /etc/apt/keyrings
+RUN curl -fsSL https://deb.nodesource.com/gpgkey/nodesource-repo.gpg.key | gpg --dearmor -o /etc/apt/keyrings/nodesource.gpg
+ENV NODE_MAJOR=18
+RUN echo "deb [signed-by=/etc/apt/keyrings/nodesource.gpg] https://deb.nodesource.com/node_$NODE_MAJOR.x nodistro main" | tee /etc/apt/sources.list.d/nodesource.list
+RUN apt update
+RUN apt --yes install nodejs
+
+# git and file management
+RUN apt --yes install git git-lfs unzip
+RUN git lfs install
+
+# Python
+RUN apt --yes install python3 python3-pip
+RUN python3 -m pip install --no-cache-dir --upgrade pip
+
+
+# required for CMake it seems
+RUN apt --yes install libtbb-dev libeigen3-dev g++ libssl-dev checkinstall
+
+
+# The app require CMake 3.24+ but this version of Ubuntu only has the 3.16
+# So we need to install a more recent version
+#RUN apt-get update \
+#  && rm -rf /var/lib/apt/lists/* \
+RUN wget https://github.com/Kitware/CMake/releases/download/v3.24.1/cmake-3.24.1-Linux-x86_64.sh \
+  -q -O /tmp/cmake-install.sh \
+  && chmod u+x /tmp/cmake-install.sh \
+  && mkdir /opt/cmake-3.24.1 \
+  && /tmp/cmake-install.sh --skip-license --prefix=/opt/cmake-3.24.1 \
+  && rm /tmp/cmake-install.sh \
+  && ln -s /opt/cmake-3.24.1/bin/* /usr/local/bin
+
+# Install cmake 3.24
+#RUN wget https://github.com/Kitware/CMake/releases/download/v3.24.1/cmake-3.22.1.tar.gz \
+# && tar -zvxf cmake-3.24.1.tar.gz \
+# && cd cmake-3.24.1 \
+# && ./bootstrap \
+# && make -j8 \
+# && checkinstall --pkgname=cmake --pkgversion="3.20-custom" --default
+# Copy contents from 2 levels up
+#COPY . ./
+
+# Download and extract libtorch
+#RUN wget https://download.pytorch.org/libtorch/cu118/libtorch-cxx11-abi-shared-with-deps-2.0.1%2Bcu118.zip \
+# && unzip libtorch-cxx11-abi-shared-with-deps-2.0.1+cu118.zip -d external/
+
+# Set up a new user named "user" with user ID 1000
+RUN useradd -o -u 1000 user
+
+# Switch to the "user" user
+USER user
+
+ENV PYTHON_BIN /usr/bin/python3
+
+#ENV PATH /usr/local/cuda-12.2/bin:$PATH
+#ENV LD_LIBRARY_PATH /usr/local/cuda-12.2/lib64:$LD_LIBRARY_PATH
+# Let's try to downgrade
+ENV PATH /usr/local/cuda-11.8/bin:$PATH
+ENV LD_LIBRARY_PATH /usr/local/cuda-11.8/lib64:$LD_LIBRARY_PATH
+
+
+# Set home to the user's home directory
+ENV HOME=/home/user \
+	PATH=/home/user/.local/bin:$PATH
+
+# Set the working directory to the user's home directory
+WORKDIR $HOME/app
+
+# Install app dependencies
+# A wildcard is used to ensure both package.json AND package-lock.json are copied
+# where available (npm@5+)
+COPY --chown=user package*.json $HOME/app
+
+RUN npm install
+
+# Copy the current directory contents into the container at $HOME/app setting the owner to the user
+COPY --chown=user . $HOME/app
+
+RUN git clone --recursive https://github.com/MrNeRF/gaussian-splatting-cuda
+
+WORKDIR $HOME/app/gaussian-splatting-cuda
+
+RUN wget https://download.pytorch.org/libtorch/cu118/libtorch-cxx11-abi-shared-with-deps-2.0.1%2Bcu118.zip  
+RUN unzip libtorch-cxx11-abi-shared-with-deps-2.0.1+cu118.zip -d external/
+RUN rm libtorch-cxx11-abi-shared-with-deps-2.0.1+cu118.zip
+
+# Build (on CPU, this will add compute_35 as build target, which we do not want)
+# There seems to be a work around, see this thread:
+# https://github.com/MrNeRF/gaussian-splatting-cuda/issues/14
+# here is the hack:
+#
+# Replace "native" by "all"
+# inspired by https://github.com/ztxz16/fastllm/pull/309/files
+#
+# CUDA architectures are defined as codes
+# by default CMake detected:
+# 3.5;5.0;8.0;8.6;8.9;9.0
+# To see the mapping: https://arnon.dk/matching-sm-architectures-arch-and-gencode-for-various-nvidia-cards/
+# A10G and A100 -> Ampere -> sm_80, sm_86, sm_87 -> 8.0;8.6;8.7
+# Nvidia T4 -> Turing -> sm_75 -> 7.5
+# ? -> Lovelace ->  sm_89 -> 8.6
+# ? -> Hopper -> sm_90 -> 9.0
+RUN find . -name CMakeLists.txt -exec sed -i 's/CUDA_ARCHITECTURES native/CUDA_ARCHITECTURES all/' {} +
+
+#RUN cmake -B build -D CMAKE_BUILD_TYPE=Release -D CUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda-12.2/ -D CUDA_VERSION=12.2
+# Let's try to downgrade the version
+RUN cmake -B build -D CMAKE_BUILD_TYPE=Release -D CUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda-11.8/ -D CUDA_VERSION=11.8
+RUN cmake --build build -- -j8
+
+COPY --chown=user . $HOME/app/gaussian-splatting-cuda
+
+RUN echo "Build ended at: $(date "+%Y-%m-%d %H:%M")"
+
+EXPOSE 7860
+
+# we can't use this (it time out)
+# CMD [ "xvfb-run", "-s", "-ac -screen 0 1920x1080x24", "npm", "run", "start" ]
+CMD [ "npm", "run", "start" ]