docker experience seems to work (#50)

Dockerfile

@@ -11,6 +11,7 @@ RUN apt-get update && apt-get install -y \
     # Dependencies required for python.
     build-essential \
     curl \
+    ffmpeg \
     git \
     libbz2-dev \
     libffi-dev \
@@ -24,6 +25,23 @@ RUN apt-get update && apt-get install -y \
     tk-dev \
     xz-utils \
     zlib1g-dev \
+    # VirtualGL Dependencies.
+    libc6 \
+    libglu1-mesa \
+    libglvnd-dev \
+    libxv1 \
+    mesa-utils \
+    openbox \
+    wget \
+    xvfb \
+    # CoppeliaSim Dependencies.
+    libglu1-mesa-dev \
+    '^libxcb.*-dev' \
+    libxi-dev \
+    libxkbcommon-dev \
+    libxkbcommon-x11-dev \
+    libxrender-dev \
+    libx11-xcb-dev \
     && apt-get clean \
     && rm -rf /var/lib/apt/lists/*
 
@@ -40,6 +58,33 @@ RUN pyenv global 3.9.12
 RUN mkdir $CODING_ROOT/code
 WORKDIR $CODING_ROOT/code
 
+# Download CoppeliaSim
+RUN mkdir $CODING_ROOT/.coppelia
+WORKDIR $CODING_ROOT/.coppelia
+RUN curl -L https://www.coppeliarobotics.com/files/V4_1_0/CoppeliaSim_Edu_V4_1_0_Ubuntu20_04.tar.xz -o CoppeliaSim_Edu_V4_1_0_Ubuntu20_04.tar.xz && \
+    tar -xf CoppeliaSim_Edu_V4_1_0_Ubuntu20_04.tar.xz && \
+    rm CoppeliaSim_Edu_V4_1_0_Ubuntu20_04.tar.xz
+
+# Set the working directory back to the code directory.
+WORKDIR $CODING_ROOT/code
+
+# modify environment variables for coppelia sim
+ENV COPPELIASIM_ROOT="$CODING_ROOT/.coppelia/CoppeliaSim_Edu_V4_1_0_Ubuntu20_04"
+ENV LD_LIBRARY_PATH="$LD_LIBRARY_PATH:$COPPELIASIM_ROOT"
+ENV QT_QPA_PLATFORM_PLUGIN_PATH="$COPPELIASIM_ROOT"
+
+# Install VirtualGL
+RUN wget --no-check-certificate https://github.com/VirtualGL/virtualgl/releases/download/3.1.1/virtualgl_3.1.1_amd64.deb \
+    && dpkg -i virtualgl_*.deb \
+    && rm virtualgl_*.deb
+
+# Configure VirtualGL
+RUN /opt/VirtualGL/bin/vglserver_config +s +f -t +egl
+
+# Setup environment variables for NVIDIA and VirtualGL
+ENV NVIDIA_VISIBLE_DEVICES all
+ENV NVIDIA_DRIVER_CAPABILITIES all
+
 # Copy in the requirements.
 COPY requirements-gpu.txt .
 
@@ -54,12 +99,23 @@ COPY third_party third_party
 # Install the third-party libraries.
 RUN pip install --no-cache-dir -e third_party/ndf_robot
 
+# Install pyrep.
+RUN pip install --no-cache-dir --no-build-isolation "pyrep @ git+https://github.com/stepjam/PyRep.git"
+
 # Copy in pyproject.toml.
 COPY pyproject.toml .
 RUN mkdir taxpose
 RUN touch taxpose/py.typed
 
-RUN pip install --no-cache-dir -e ".[develop]"
+# Install our project.
+RUN pip install --no-cache-dir -e ".[develop,rlbench]"
 
 # Copy in the code.
 COPY . .
+
+# Make directories for mounting.
+RUN mkdir $CODING_ROOT/data
+RUN mkdir $CODING_ROOT/logs
+
+COPY ./docker/entrypoint.sh /opt/baeisner/entrypoint.sh
+ENTRYPOINT ["/opt/baeisner/entrypoint.sh"]

docker/entrypoint.sh

@@ -0,0 +1,26 @@
+#!/bin/bash
+
+# Set the display env variable
+export DISPLAY=:99
+export VGL_DISPLAY="egl"
+
+# Start Xvfb
+Xvfb $DISPLAY -screen 0 1024x768x24 -nolisten tcp -nolisten unix +extension GLX  > /dev/null 2>&1 &
+
+# Wait a little for Xvfb to start
+sleep 2
+
+echo "Xvfb started on display $DISPLAY"
+
+# If VGL_DEVICE is set, then use it. Else use egl0.
+if [ -z "$VGL_DEVICE" ]; then
+    VGL_DEVICE="egl0"
+fi
+
+echo "Using VirtualGL device: $VGL_DEVICE"
+
+# Run your OpenGL application with VirtualGL (add +v command if needed.)
+vglrun \
+    -d $VGL_DEVICE \
+    -ld /opt/baeisner/.pyenv/versions/3.9.12/lib/python3.9/site-packages/torch/lib \
+    "$@"

pyproject.toml

@@ -58,10 +58,8 @@ develop = [
 build_docs = ["mkdocs-material", "mkdocstrings[python]"]
 rlbench = [
   # These should be installed manually...
-  "pyrep",
-  "rlbench",
-
-  # This can be done automatically.
+  # "pyrep",
+  # "rlbench @ git+https://github.com/stepjam/RLBench.git",
   "rpad-rlbench-utils @ git+https://github.com/r-pad/rlbench_utils.git",
 ]
 

scripts/debug_headless.py

@@ -0,0 +1,26 @@
+import time
+
+import numpy as np
+from rlbench.action_modes.action_mode import MoveArmThenGripper
+from rlbench.action_modes.arm_action_modes import JointVelocity
+from rlbench.action_modes.gripper_action_modes import Discrete
+from rlbench.environment import Environment
+from rlbench.tasks import FS10_V1
+
+action_mode = MoveArmThenGripper(
+    arm_action_mode=JointVelocity(), gripper_action_mode=Discrete()
+)
+env = Environment(action_mode, headless=True)
+env.launch()
+
+train_tasks = FS10_V1["train"]
+test_tasks = FS10_V1["test"]
+task_to_train = np.random.choice(train_tasks, 1)[0]
+task = env.get_task(task_to_train)
+task.sample_variation()  # random variation
+descriptions, obs = task.reset()
+
+# Step for 10s wall clock time
+start = time.time()
+while time.time() - start < 10:
+    obs, reward, terminate = task.step(np.random.normal(size=env.action_shape))