Docker Support

.gitmodules

@@ -1,3 +1,6 @@
 [submodule "third_party/isaacgym"]
 	path = third_party/isaacgym
-	url = ../../kscalelabs/isaacgym.git
+	url = ../../kscalelabs/isaacgym.git
+[submodule "sim/genesis/rsl_rl"]
+	path = sim/genesis/rsl_rl
+	url = [email protected]:leggedrobotics/rsl_rl.git

.vscode/settings.json

@@ -0,0 +1,4 @@
+{
+    "marscode.chatLanguage": "cn",
+    "CodeGPT.apiKey": "Ollama"
+}

analyze_onnx.py

@@ -0,0 +1,28 @@
+import onnxruntime as ort
+import numpy as np
+
+# 加载 ONNX 模型
+model_path = "sim/genesis/logs/zeroth-walking/model_100.onnx"
+session = ort.InferenceSession(model_path)
+
+# 获取输入信息
+input_name = session.get_inputs()[0].name
+input_shape = session.get_inputs()[0].shape
+print(f"Input name: {input_name}, shape: {input_shape}")
+
+# 创建随机输入数据
+obs_dim = input_shape[1]  # 获取观测维度
+dummy_input = np.random.randn(1, obs_dim).astype(np.float32)
+
+print(f"Dummy input shape: {dummy_input.shape}")
+print(f"Dummy input: {dummy_input}")
+
+# 运行模型
+outputs = session.run(None, {input_name: dummy_input})
+actions = outputs[0]
+
+# 分析输出
+print(f"Output actions shape: {actions.shape}")
+print(f"First 5 actions: {actions[0][:5]}")
+print(f"Actions mean: {np.mean(actions)}")
+print(f"Actions std: {np.std(actions)}")

docker/10_nvidia.json

@@ -0,0 +1,7 @@
+{
+    "file_format_version" : "1.0.0",
+        "ICD" : {
+            "library_path" : "libEGL_nvidia.so.0"
+    }
+}
+

docker/Dockerfile

@@ -0,0 +1,75 @@
+# 1stly, to build zeroth-bot-sim:v0
+# FROM nvidia/cuda:12.1.0-cudnn8-devel-ubuntu20.04   
+
+# COPY sources.list /etc/apt/sources.list
+
+# RUN mkdir /root/.pip
+# COPY pip.conf /root/.pip/pip.conf
+
+# RUN apt install -y wget zlib1g-dev libssl-dev libncurses5-dev libsqlite3-dev libreadline-dev libtk8.6 libgdm-dev libdb4o-cil-dev libpcap-dev
+# RUN wget https://mirrors.huaweicloud.com/python/3.8.19/Python-3.8.19.tar.xz && tar -xvf Python-3.8.19.tar.xz
+
+# WORKDIR  /root/Python-3.8.19
+# RUN ./configure --prefix=/usr/local && make && make install
+
+# WORKDIR /usr/local/bin/
+# RUN ln -s pip3 pip
+
+# WORKDIR  /app/sim/
+# RUN make install-dev
+
+# RUN wget https://developer.nvidia.com/isaac-gym-preview-4
+# # RUN tar -xvf 
+# RUN make install-third-party-external
+
+FROM zeroth-bot-sim:v0
+
+WORKDIR /root
+
+RUN apt update
+
+# on vnc client use <your docker ip>:5901
+RUN apt update && apt install -y \
+    --no-install-recommends \
+    libxcursor-dev \
+    libxrandr-dev \
+    libxinerama-dev \
+    libxi-dev \
+    mesa-common-dev \
+    zip \
+    unzip \
+    make \
+    vulkan-utils \
+    mesa-vulkan-drivers \
+    pigz \
+    git \
+    libegl1
+
+# WAR for eglReleaseThread shutdown crash in libEGL_mesa.so.0 (ensure it's never detected/loaded)
+# Can't remove package libegl-mesa0 directly (because of libegl1 which we need)
+RUN rm /usr/lib/x86_64-linux-gnu/libEGL_mesa.so.0 /usr/lib/x86_64-linux-gnu/libEGL_mesa.so.0.0.0 /usr/share/glvnd/egl_vendor.d/50_mesa.json
+
+COPY ./nvidia_icd.json /usr/share/vulkan/icd.d/nvidia_icd.json
+COPY ./10_nvidia.json /usr/share/glvnd/egl_vendor.d/10_nvidia.json
+
+
+WORKDIR /app/sim
+
+RUN useradd --create-home gymuser
+USER gymuser
+
+# copy gym repo to docker
+COPY --chown=gymuser . .
+
+# install gym modules
+ENV PATH="/home/gymuser/.local/bin:$PATH"
+
+RUN export MODEL_DIR=sim/resources/stompymicro
+
+ENV NVIDIA_VISIBLE_DEVICES=all NVIDIA_DRIVER_CAPABILITIES=all
+
+CMD ["tail","-f", "/dev/null"]
+
+# CMD ["python3", "sim/train.py", "--task=stompymicro", "--num_envs=4"]
+# python3 sim/train.py --task=stompymicro --num_envs=4
+

docker/README.md

@@ -0,0 +1,104 @@
+Preliminaries
+```
+Ensure nvidia-smi is work on your host machine.
+```
+
+There is a prebuilt docker image, tested on a amd64 machine, with Ubuntu 24.04 LTS.
+```
+docker pull ghcr.io/bigjohnn/zeroth-bot-sim:v1
+```
+
+But if that not work, maybe you can build it by yourself.
+
+Make some changes in your Dockerfile && docker-compose.yml.
+```
+PREBUILD a docker image that have external dependencies
+
+# 1stly, to build zeroth-bot-sim:v0
+# FROM nvidia/cuda:12.1.0-cudnn8-devel-ubuntu20.04   
+
+# COPY sources.list /etc/apt/sources.list
+
+# RUN mkdir /root/.pip
+# COPY pip.conf /root/.pip/pip.conf
+
+# RUN apt install -y wget zlib1g-dev libssl-dev libncurses5-dev libsqlite3-dev libreadline-dev libtk8.6 libgdm-dev libdb4o-cil-dev libpcap-dev
+# RUN wget https://mirrors.huaweicloud.com/python/3.8.19/Python-3.8.19.tar.xz && tar -xvf Python-3.8.19.tar.xz
+
+# WORKDIR  /root/Python-3.8.19
+# RUN ./configure --prefix=/usr/local && make && make install
+
+# WORKDIR /usr/local/bin/
+# RUN ln -s pip3 pip
+
+# WORKDIR  /app/sim/
+# RUN make install-dev
+
+# RUN wget https://developer.nvidia.com/isaac-gym-preview-4
+# # RUN tar -xvf 
+# RUN make install-third-party-external
+
+```
+
+Then, 
+
+Terminal1:
+```
+docker-compose up --build
+```
+
+```
+ARNING: Found orphan containers (a55a8ae7a762_docker_my_cuda_service_1) for this project. If you removed or renamed this service in your compose file, you can run this command with the --remove-orphans flag to clean it up.
+Building my-service
+[+] Building 1.6s (10/10) FINISHED                                                                       docker:default
+ => [internal] load build definition from Dockerfile                                                               0.2s
+ => => transferring dockerfile: 348B                                                                               0.0s
+ => [internal] load metadata for docker.io/nvidia/cuda:12.1.0-cudnn8-devel-ubuntu20.04                             0.0s
+ => [internal] load .dockerignore                                                                                  0.2s
+ => => transferring context: 2B                                                                                    0.0s
+ => [1/5] FROM docker.io/nvidia/cuda:12.1.0-cudnn8-devel-ubuntu20.04                                               0.0s
+ => [internal] load build context                                                                                  0.2s
+ => => transferring context: 34B                                                                                   0.0s
+ => CACHED [2/5] WORKDIR /app                                                                                      0.0s
+ => CACHED [3/5] COPY sources.list /etc/apt/sources.list                                                           0.0s
+ => CACHED [4/5] RUN apt update                                                                                    0.0s
+ => CACHED [5/5] WORKDIR  /app/sim/                                                                                0.0s
+ => exporting to image                                                                                             0.2s
+ => => exporting layers                                                                                            0.0s
+ => => writing image sha256:8e9c02e6c8b50dcbf7d6d1962d51de926126f132b65b65952ad8dfc74634f8c6                       0.0s
+ => => naming to docker.io/library/docker_my-service                                                               0.1s
+WARNING: Image for service my-service was built because it did not already exist. To rebuild this image you must use `docker-compose build` or `docker-compose up --build`.
+Creating docker_my-service_1 ... done
+Attaching to docker_my-service_1
+my-service_1  | 
+my-service_1  | ==========
+my-service_1  | == CUDA ==
+my-service_1  | ==========
+my-service_1  | 
+my-service_1  | CUDA Version 12.1.0
+my-service_1  | 
+my-service_1  | Container image Copyright (c) 2016-2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+my-service_1  | 
+my-service_1  | This container image and its contents are governed by the NVIDIA Deep Learning Container License.
+my-service_1  | By pulling and using the container, you accept the terms and conditions of this license:
+my-service_1  | https://developer.nvidia.com/ngc/nvidia-deep-learning-container-license
+my-service_1  | 
+my-service_1  | A copy of this license is made available in this container at /NGC-DL-CONTAINER-LICENSE for your convenience.
+my-service_1  | 
+my-service_1  | *************************
+my-service_1  | ** DEPRECATION NOTICE! **
+my-service_1  | *************************
+my-service_1  | THIS IMAGE IS DEPRECATED and is scheduled for DELETION.
+my-service_1  |     https://gitlab.com/nvidia/container-images/cuda/blob/master/doc/support-policy.md
+my-service_1  | 
+```
+
+Terminal2:
+
+```
+docker exec -it docker_zeroth-sim_1 /bin/bash
+```
+
+```
+gymuser@06aac36e0751:/app/sim# python3 sim/train.py --task=stompymicro --num_envs=4
+```

docker/docker-compose.yml

@@ -0,0 +1,24 @@
+# version: '3.8'
+
+services:
+  zeroth-sim:
+    build:
+      context: .  # Assuming the Dockerfile is in the current directory
+      dockerfile: Dockerfile
+    volumes:
+      - /home/hph/Codes/zeroth-bot:/app # Must have absolute path
+      - /tmp/.X11-unix:/tmp/.X11-unix
+    environment:
+      - DISPLAY=$DISPLAY
+    privileged: true
+    cap_add:
+      - SYS_PTRACE
+    shm_size: 6g
+    tty: true
+    stdin_open: true
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - capabilities: [gpu]
+              count: all

docker/nvidia_icd.json

@@ -0,0 +1,7 @@
+{
+    "file_format_version" : "1.0.0",
+    "ICD": {
+        "library_path": "libGLX_nvidia.so.0",
+        "api_version" : "1.1.95"
+    }
+}

docker/pip.conf

@@ -0,0 +1,3 @@
+[global]
+trusted-host=mirrors.aliyun.com
+index-url=http://mirrors.aliyun.com/pypi/simple/

docker/sources.list

@@ -0,0 +1,4 @@
+deb http://mirrors.ustc.edu.cn/ubuntu/ focal main restricted universe multiverse
+deb http://mirrors.ustc.edu.cn/ubuntu/ focal-updates main restricted universe multiverse
+deb http://mirrors.ustc.edu.cn/ubuntu/ focal-backports main restricted universe multiverse
+deb http://mirrors.ustc.edu.cn/ubuntu/ focal-security main restricted universe multiverse

sim/envs/humanoids/stompymicro_config.py

@@ -1,7 +1,5 @@
 """Defines the environment configuration for the Getting up task"""
 
-import numpy as np
-
 from sim.env import robot_urdf_path
 from sim.envs.base.legged_robot_config import (  # type: ignore
     LeggedRobotCfg,
@@ -40,7 +38,8 @@ class asset(LeggedRobotCfg.asset):
         file = str(robot_urdf_path(name))
 
         foot_name = ["foot_left", "foot_right"]
-        knee_name = ["left_knee_pitch_motor", "right_knee_pitch_motor"]
+        # knee_name = ["left_knee_pitch_motor", "right_knee_pitch_motor"]
+        knee_name = ["ankle_pitch_left", "ankle_pitch_right"]
 
         termination_height = 0.05
         default_feet_height = 0.02
@@ -150,7 +149,7 @@ class ranges:
             lin_vel_x = [-0.05, 0.23]  # min max [m/s]
             lin_vel_y = [-0.04, 0.04]  # min max [m/s]
             ang_vel_yaw = [-0.1, 0.1]  # min max [rad/s]
-            heading = [-np.pi, np.pi]  # min max [rad]
+            heading = [-3.14, 3.14]
 
     class rewards:
         base_height_target = Robot.height

sim/genesis/.gitignore

@@ -0,0 +1,3 @@
+/logs/
+/rsl_rl/
+zeroth_train_crab.py

sim/genesis/README.md

@@ -0,0 +1,34 @@
+# 进入genesis目录。
+`cd sim/genesis` 
+
+# 安装rsl_rl。
+```
+git clone https://github.com/leggedrobotics/rsl_rl
+cd rsl_rl && git checkout v2.2.0 && pip install -e .
+```
+
+# 安装tensorboard。
+`pip install tensorboard`
+
+安装完成后，通过运行以下命令开始训练：
+
+`python zeroth_train.py`
+
+要监控训练过程，请启动TensorBoard：
+
+`tensorboard --logdir logs`
+
+查看训练结果。
+
+`python zeroth_eval.py`
+
+模型转换。
+
+`cd genesis`
+
+`python3 utils/convert_to_onnx.py --cfg logs/zeroth-walking/cfgs.pkl --model ../../examples/model_100.pt --output ../../examples/model_100.onnx`
+
+注意⚠️
+Mac M系列芯片，使用micromamba替换conda使用，例如
+`micromamba activate genesis`
+然后再调用pip/python等命令