GPU Dockerfile

Makefile

@@ -10,19 +10,29 @@ edit_render: blender/edit.blend imgs/buffer/scene_scene_0001.png imgs/buffer/sce
 	python3 scripts/render.py --stage EDIT
 
 model_render: blender/models/curve-skeleton-cube.obj
-	docker run --rm -v ${PWD}/dump:/tmp -v ${PWD}/blender/:/blender/ -v ${PWD}/scripts:/scripts -v ${PWD}/config.yaml:/config.yaml -v ${PWD}/imgs/:/imgs tennisgazelle/blender-pipeline:latest --python scripts/model-render.py
+	docker run --rm -v ${PWD}/dump:/tmp -v ${PWD}/blender/:/blender/ -v ${PWD}/scripts:/scripts -v ${PWD}/config.yaml:/config.yaml -v ${PWD}/imgs/:/imgs tennisgazelle/blender-pipeline:latest --python scripts/model_render.py
 
 local_model_render: local_move_common_to_blender_py
-	/Applications/Blender.app/Contents/MacOS/Blender -b --python scripts/model-render.py
+	/Applications/Blender.app/Contents/MacOS/Blender -b --python scripts/model_render.py
 
 single_obj_render: blender/models/curve-skeleton-cube.obj
 	docker run --rm -v ${PWD}/dump:/tmp -v ${PWD}/blender/:/blender/ -v ${PWD}/scripts:/scripts -v ${PWD}/config.yaml:/config.yaml -v ${PWD}/imgs/:/imgs tennisgazelle/blender-pipeline:latest --python scripts/obj-render.py -- --output_folder imgs/out/ blender/models/curve-skeleton-cube.obj
 
 local_single_obj_render: local_move_common_to_blender_py
 	/Applications/Blender.app/Contents/MacOS/Blender -b --python scripts/obj-render.py -- --output_folder imgs/out/ blender/models/curve-skeleton-cube.obj
 
-docker: scripts/Dockerfile
+docker: scripts/Dockerfile scripts/Dockerfile.gpu
 	docker build -t tennisgazelle/blender-pipeline:latest scripts/
+	docker build -t tennisgazelle/blender-pipeline-gpu:latest scripts/ -f scripts/Dockerfile.gpu
+
+local_enable_gpu: scripts/enable_gpu.py
+	/Applications/Blender.app/Contents/MacOS/Blender -b --python scripts/enable_gpy.py
+
+linux_local_enable_gpu:
+	/home/tennisgazelle/Downloads/blender-2.90.0-linux64/blender -b blender/cooler_scene.blend --python scripts/enable_gpu.py -f 1 -E CYCLES
+
+enable_gpu:
+	docker run --runtime=nvidia -e NVIDIA_VISIBLE_DEVICES=all --rm -v ${PWD}/imgs/:/imgs/ -v ${PWD}/blender/:/blender/ -v ${PWD}/scripts:/scripts -v ${PWD}/config.yaml:/config.yaml vogete/blender-cuda blender/cool_scene.blend --python scripts/force_gpu.py -f 1
 
 get_paths:
 	docker run --rm -v ${PWD}/blender/:/blender/ -v ${PWD}/scripts:/scripts -v ${PWD}/config.yaml:/config.yaml tennisgazelle/blender-pipeline:latest blender/cool_scene.blend --python scripts/get_path.py
@@ -54,3 +64,5 @@ docker_build_test:
 	echo 'if that works, try with the other blender files with yaml'
 	docker run --rm -v ${PWD}/blender/:/blender/ -v ${PWD}/scripts:/scripts blender-pipeline:latest blender/scene.blend --python scripts/get_path.py
 
+docker_check_gpu:
+	docker run --runtime=nvidia -e NVIDIA_VISIBLE_DEVICES=all --rm --entrypoint "" vogete/blender-cuda nvidia-smi

config.yaml

@@ -4,7 +4,7 @@ stages:
     file_output_format: '{bfile}_####'
 
   cool_scene:
-    buffer_frames: 1-90
+    buffer_frames: 1
     force_update: false
     render_output: 'imgs/buffer/'
     engine: CYCLES # todo: figure out how to do EEVEE
@@ -13,7 +13,7 @@ stages:
     blender_flags: ''
 
   scene:
-    buffer_frames: 1-90
+    buffer_frames: 1
     force_update: false
     render_output: 'imgs/buffer/'
     engine: CYCLES # todo: figure out how to do EEVEE
@@ -61,7 +61,11 @@ model_output_format: '{model}_{angle}_{map}'
 
 # experimental below, do not alter
 docker:
-  image: tennisgazelle/blender-pipeline:latest
-  render_cmd: docker run --rm -v {cwd}/blender/:/blender/ -v {cwd}/imgs:/imgs {image} blender/{blend_file} -E {engine} -F {format} -t 8 {flags}
-  # python_cmd: docker run --rm -v ${cwd}/blender/:/blender/ -v ${cwd}/scripts:/scripts -v ${cwd}/config.yaml:/config.yaml tennisgazelle/blender-pipeline:latest blender/scene.blend --python scripts/get_path.py
+  image: tennisgazelle/blender-pipeline-gpu:latest
+  # image: vogete/blender-cuda
+  # render_cmd: docker run --runtime=nvidia -e NVIDIA_VISIBLE_DEVICES=all --rm -v {cwd}/blender/:/blender/ -v {cwd}/imgs:/imgs {image} blender/{blend_file} -E {engine} -F {format} -t 8 -P scripts/force_gpu.py {flags}
+  render_cmd: docker run --runtime=nvidia -e NVIDIA_VISIBLE_DEVICES=all --rm -v {cwd}/blender/:/blender/ -v {cwd}/imgs:/imgs {image} blender/{blend_file} -E {engine} -F {format} -t 8 {flags} -P scripts/enable_gpu.py
+  # render_cmd: docker run --runtime=nvidia -e NVIDIA_VISIBLE_DEVICES=all --rm -v /scripts:/media -v {cwd}/blender/:/blender/ vogete/blender-cuda blender/cool_scene.blend -E CYCLES -t 0 -P scripts/force_gpu.py -o frame_### -f 1
 
+  # python_cmd: docker run --rm -v ${cwd}/blender/:/blender/ -v ${cwd}/scripts:/scripts -v ${cwd}/config.yaml:/config.yaml tennisgazelle/blender-pipeline:latest blender/scene.blend --python scripts/get_path.py
+  use_gpu: True

scripts/Dockerfile.gpu

@@ -0,0 +1,45 @@
+# ARG IMAGE_NAME
+# FROM ${IMAGE_NAME}:11.3.0-runtime-ubuntu20.04
+# LABEL maintainer "NVIDIA CORPORATION <cudatools@nvidia.com>"
+# ENV CUDNN_VERSION 8.2.0.53
+# LABEL com.nvidia.cudnn.version="${CUDNN_VERSION}"
+# RUN apt-get update && apt-get install -y --no-install-recommends \
+#     libcudnn8=$CUDNN_VERSION-1+cuda11.3 \
+#     && apt-mark hold libcudnn8 && \
+#     rm -rf /var/lib/apt/lists/*
+
+FROM nvidia/cuda:11.3.0-base-ubuntu20.04
+
+LABEL authors="Daniel Lopez <daniellopez@nevada.unr.edu>"
+
+# set up deps for blender
+RUN apt-get update && \
+	apt-get install -y \
+		curl \
+		libfreetype6 \
+		libglu1-mesa \
+		libxi6 \
+		libxrender1 \
+		xz-utils && \
+	apt-get -y autoremove
+
+# Download blender
+ENV BLENDER_MAJOR 2.82
+ENV BLENDER_VERSION 2.82a
+ENV BLENDER_URL https://download.blender.org/release/Blender${BLENDER_MAJOR}/blender-${BLENDER_VERSION}-linux64.tar.xz
+
+RUN curl -L ${BLENDER_URL} | tar -xJ -C /usr/local/ \
+    && mv /usr/local/blender-${BLENDER_VERSION}-linux64 /usr/local/blender
+
+# run the pip install for the bundled python
+RUN curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py \
+    && ls /usr/local/blender/${BLENDER_MAJOR}/python/lib \
+    && /usr/local/blender/${BLENDER_MAJOR}/python/bin/python3.7m get-pip.py \
+    && /usr/local/blender/${BLENDER_MAJOR}/python/bin/python3.7m -m pip install pyyaml yamale --user
+
+# Get the config common library near the blender executable
+COPY common.py /usr/local/blender/${BLENDER_MAJOR}/python/lib/python3.7/
+
+VOLUME /media
+WORKDIR /
+ENTRYPOINT ["/usr/local/blender/blender", "-b"]

scripts/config_schema.yaml

@@ -41,4 +41,5 @@ model_settings:
 docker_config:
   image: str()
   render_cmd: str()
+  use_gpu: bool(required=False, default=True)
 

scripts/enable_gpu.py

@@ -0,0 +1,21 @@
+# from model_render import Renderer
+
+import bpy
+bpy.data.scenes[0].render.engine = "CYCLES"
+
+# Set the device_type
+bpy.context.preferences.addons[
+    "cycles"
+].preferences.compute_device_type = "CUDA" # or "OPENCL"
+
+# Set the device and feature set
+bpy.context.scene.cycles.device = "GPU"
+
+# get_devices() to let Blender detects GPU device
+bpy.context.preferences.addons["cycles"].preferences.get_devices()
+print(bpy.context.preferences.addons["cycles"].preferences.compute_device_type)
+for d in bpy.context.preferences.addons["cycles"].preferences.devices:
+    d["use"] = 1 # Using all devices, include GPU and CPU
+    print(d["name"], d["use"])
+
+bpy.ops.wm.save_mainfile()

scripts/force_gpu.py

@@ -0,0 +1,11 @@
+import bpy
+for card in bpy.context.user_preferences.addons['cycles'].preferences.devices:
+    print(card.name)
+
+prefs = bpy.context.user_preferences.addons['cycles'].preferences
+print(prefs.compute_device_type)
+prefs.compute_device_type = 'CUDA'
+prefs.devices[0].use = True
+
+bpy.ops.wm.save_userpref()
+bpy.ops.wm.save_mainfile()

scripts/setup-nvidia-toolkit.sh

@@ -0,0 +1,18 @@
+#!/bin/bash
+
+# distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
+distribution=ubuntu20.04
+
+curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add - \
+
+curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
+
+sudo apt-get update
+
+sudo apt-get install -y nvidia-docker2
+
+sudo systemctl restart docker
+
+
+cpu time: 39.811s
+gpu time: 40.867