add Dockerfile

.dockerignore

@@ -0,0 +1,4 @@
+.git
+.env
+*.pyc
+Dockerfile

Dockerfile

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+FROM pytorch/pytorch:2.4.0-cuda12.4-cudnn9-devel AS builder
+
+# Install build dependencies
+RUN apt-get update && \
+    apt-get install -y ffmpeg build-essential git rdfind
+
+WORKDIR /app
+ADD setup.sh   /app/setup.sh
+
+# Setup conda
+RUN conda config --set always_yes true && \
+    conda init && \
+    conda config --add channels defaults
+
+# Use bash shell so we can source activate
+SHELL ["/bin/bash", "-c"]
+
+
+RUN conda install torchvision=0.19.0 \
+                  onnx==1.17.0 \
+                  pytorch=2.4.0 \
+                  pytorch-cuda=12.4 \
+              --force-reinstall \
+              -c pytorch \
+              -c nvidia
+
+# Create a g++ wrapper for JIT, since the include dirs are passed with -i rather than -I for some reason
+RUN printf '#!/usr/bin/env bash\nexec /usr/bin/g++ -I/usr/local/cuda/include -I/usr/local/cuda/include/crt "$@"\n' > /usr/local/bin/gxx-wrapper && \
+    chmod +x /usr/local/bin/gxx-wrapper
+ENV CXX=/usr/local/bin/gxx-wrapper
+
+
+# Run setup.sh - this won't install all the things due to missing GPU in the builder
+RUN conda run -n base ./setup.sh --basic --xformers --flash-attn --diffoctreerast --vox2seq --spconv --mipgaussian --kaolin --nvdiffrast --demo
+
+# Now install additional Python packages
+# These ones work inside the builder
+RUN conda run -n base pip install diso
+RUN conda run -n base pip install plyfile utils3d flash_attn spconv-cu120 xformers onnxscript
+RUN conda run -n base pip install kaolin -f https://nvidia-kaolin.s3.us-east-2.amazonaws.com/torch-2.4.0_cu121.html
+RUN conda run -n base pip install git+https://github.com/NVlabs/nvdiffrast.git
+
+# Remove downloaded packages from conda and pip
+RUN conda clean --all -f -y
+RUN pip cache purge
+
+# Deduplicate with rdfind
+# This reduces the size of the image by a few hundred megs.
+RUN rdfind -makesymlinks true /opt/conda
+
+# Final stage
+FROM pytorch/pytorch:2.4.0-cuda12.4-cudnn9-devel AS final
+
+WORKDIR /app
+COPY --from=builder /usr/local/bin/gxx-wrapper /usr/local/bin/gxx-wrapper
+COPY --from=builder /opt/conda /opt/conda
+COPY --from=builder /root /root
+COPY --from=builder /app /app
+
+# Reinstall any runtime tools needed
+# git and build-essential are needed for post_install.sh script.
+# vim and strace are useful for debugging, remove those if you want to.
+RUN apt update && \
+    apt upgrade -y && \
+    apt install -y build-essential \
+                       git \
+                       strace \
+                       vim && \
+    rm -rf /var/lib/apt/lists/*
+
+# install these last, so we can experiment without excessive build times.
+COPY trellis         /app/trellis
+COPY app.py          /app/app.py
+COPY example.py      /app/example.py
+COPY extensions      /app/extensions
+COPY assets          /app/assets
+COPY onstart.sh      /app/onstart.sh
+COPY post_install.sh /app/post_install.sh
+
+ENV PATH=/opt/conda/bin:$PATH
+
+# This script runs the post_install steps
+
+# If you're pushing to a container registry, let this run once, run some
+# tests, then do `docker commit` to save the models along with the image.
+# This will ensure that it won't fail at runtime due to models being
+# unavailable, or network restrictions.
+CMD ["bash", "/app/onstart.sh"]
+

app.py

@@ -245,4 +245,4 @@ def deactivate_button() -> gr.Button:
 if __name__ == "__main__":
     pipeline = TrellisImageTo3DPipeline.from_pretrained("JeffreyXiang/TRELLIS-image-large")
     pipeline.cuda()
-    demo.launch()
+    demo.launch(server_name="0.0.0.0")

onstart.sh

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+#!/bin/bash
+
+cd /app
+
+echo "Doing post install steps"
+./post_install.sh
+
+export CXX=/usr/local/bin/gxx-wrapper
+
+echo "Launching app"
+python3 app.py
+
+echo "Something went wrong and it exited?"

post_install.sh

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+#!/bin/bash
+set -e
+
+# Check if post-install steps have already been run
+if [ -f /app/.post_install_done ]; then
+    echo "Post-install steps already completed."
+    exit 0
+fi
+
+cd /app
+
+echo "Install stuff that couldn't be installed without GPU"
+# Run the demo setup
+conda run -n base ./setup.sh --mipgaussian --diffoctreerast
+
+echo "Proving it actually works..."
+
+export CXX=/usr/local/bin/gxx-wrapper
+python example.py
+
+# Mark completion
+touch /app/.post_install_done
+
+echo "Post-install steps completed successfully."
+