From c03cc0d937f659715301a11eb890f4cf4942731e Mon Sep 17 00:00:00 2001 From: ZGZ713912 Date: Mon, 28 Sep 2026 17:34:06 +0800 Subject: [PATCH 1/9] feat(test): add synthetic policy generation and tests --- .github/workflows/ci.yml | 15 +- CMakeLists.txt | 21 +- README.md | 175 +++----- config/executor.yaml | 98 ---- include/rmcs_rl/onnxruntime_inference.hpp | 192 -------- .../rmcs_rl/{rl_bridge => }/parameters.hpp | 0 include/rmcs_rl/rl_bridge/action_channel.hpp | 43 +- include/rmcs_rl/rl_bridge/config.hpp | 36 ++ .../rmcs_rl/rl_bridge/observation_history.hpp | 22 + .../rl_bridge/observation_timeline.hpp | 49 ++ include/rmcs_rl/rl_bridge/types.hpp | 4 - models/policy_drive.onnx | Bin 1417 -> 0 bytes package.xml | 3 +- src/{rl_bridge => }/parameters.cpp | 18 +- src/policy/onnx_runtime.cpp | 76 ++++ src/policy/onnx_runtime.hpp | 39 ++ src/policy/policy_model.cpp | 145 ++++++ src/policy/policy_model.hpp | 54 +++ src/policy_server.cpp | 419 +++--------------- src/policy_server_launcher.cpp | 47 +- src/rl_bridge.cpp | 302 +++---------- src/rl_bridge/action_channel.cpp | 34 +- src/rl_bridge/config.cpp | 108 +++++ src/rl_bridge/interface_binding.cpp | 1 - src/rl_bridge/joint_config.cpp | 2 +- src/rl_bridge/observation_history.cpp | 34 ++ test/data/normalized_identity.onnx | Bin 0 -> 292 bytes {tool => test}/gen_synthetic_policy.py | 58 +-- test/runtime_test.cpp | 116 +++++ test/test_layout.py | 126 ++++++ {tool => test}/test_layout_contract.sh | 29 +- tool/gen_drive_policy.py | 72 --- tool/rl_layout.py | 122 +---- 33 files changed, 1119 insertions(+), 1341 deletions(-) delete mode 100644 config/executor.yaml delete mode 100644 include/rmcs_rl/onnxruntime_inference.hpp rename include/rmcs_rl/{rl_bridge => }/parameters.hpp (100%) create mode 100644 include/rmcs_rl/rl_bridge/config.hpp create mode 100644 include/rmcs_rl/rl_bridge/observation_history.hpp create mode 100644 include/rmcs_rl/rl_bridge/observation_timeline.hpp delete mode 100644 models/policy_drive.onnx rename src/{rl_bridge => }/parameters.cpp (80%) create mode 100644 src/policy/onnx_runtime.cpp create mode 100644 src/policy/onnx_runtime.hpp create mode 100644 src/policy/policy_model.cpp create mode 100644 src/policy/policy_model.hpp create mode 100644 src/rl_bridge/config.cpp create mode 100644 src/rl_bridge/observation_history.cpp create mode 100644 test/data/normalized_identity.onnx rename {tool => test}/gen_synthetic_policy.py (57%) create mode 100644 test/runtime_test.cpp create mode 100644 test/test_layout.py rename {tool => test}/test_layout_contract.sh (85%) delete mode 100644 tool/gen_drive_policy.py diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 5d4b39c..625694c 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -7,6 +7,7 @@ on: - "include/**" - "models/**" - "tool/**" + - "test/**" - "CMakeLists.txt" - "package.xml" - "plugins.xml" @@ -51,7 +52,17 @@ jobs: set +u source /opt/ros/jazzy/setup.bash set -u - colcon build --packages-up-to rmcs_rl + colcon build --packages-up-to rmcs_rl --cmake-args -DBUILD_TESTING=ON + + - name: C++ runtime regression + shell: bash + working-directory: /tmp/RMCS/rmcs_ws + run: | + set -e + source /opt/ros/jazzy/setup.bash + source install/setup.bash + colcon test --packages-select rmcs_rl + colcon test-result --test-result-base build/rmcs_rl --verbose - name: Prepare Python toolchain (venv) shell: bash @@ -103,4 +114,4 @@ jobs: working-directory: /tmp/RMCS/rmcs_ws/src/rmcs_rl run: | set -euo pipefail - PYTHON=/tmp/rl-venv/bin/python bash tool/test_layout_contract.sh + PYTHON=/tmp/rl-venv/bin/python bash test/test_layout_contract.sh diff --git a/CMakeLists.txt b/CMakeLists.txt index f3514b3..99a7d15 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -51,8 +51,10 @@ endif() ament_auto_add_library(rmcs_rl_bridge SHARED src/rl_bridge.cpp + src/rl_bridge/config.cpp + src/rl_bridge/observation_history.cpp src/rl_bridge/utility.cpp - src/rl_bridge/parameters.cpp + src/parameters.cpp src/rl_bridge/joint_config.cpp src/rl_bridge/term_parser.cpp src/rl_bridge/interface_binding.cpp @@ -68,6 +70,9 @@ target_link_libraries(rmcs_rl_bridge ${cpp_typesupport_target}) ament_auto_add_executable(policy_server src/policy_server.cpp + src/policy/policy_model.cpp + src/policy/onnx_runtime.cpp + src/parameters.cpp ) target_include_directories(policy_server PRIVATE ${ONNXRUNTIME_ROOT_DIR}/include @@ -80,9 +85,21 @@ install(TARGETS policy_server DESTINATION lib/${PROJECT_NAME}) pluginlib_export_plugin_description_file(rmcs_executor plugins.xml) install(DIRECTORY models DESTINATION share/${PROJECT_NAME}) -install(DIRECTORY config DESTINATION share/${PROJECT_NAME}) install(DIRECTORY launch DESTINATION share/${PROJECT_NAME}) +if(BUILD_TESTING) + find_package(ament_cmake_gtest REQUIRED) + ament_add_gtest(runtime_test + test/runtime_test.cpp + src/policy/policy_model.cpp + src/policy/onnx_runtime.cpp + ) + target_include_directories(runtime_test PRIVATE src ${ONNXRUNTIME_ROOT_DIR}/include) + target_link_libraries(runtime_test rmcs_rl_bridge ${ONNXRUNTIME_ROOT_DIR}/lib/libonnxruntime.so) + target_compile_definitions(runtime_test PRIVATE + RMCS_RL_IDENTITY_FIXTURE="${PROJECT_SOURCE_DIR}/test/data/normalized_identity.onnx") +endif() + ament_export_dependencies(rosidl_default_runtime) ament_auto_package(USE_SCOPED_HEADER_INSTALL_DIR) diff --git a/README.md b/README.md index 62d7c35..0eb8657 100644 --- a/README.md +++ b/README.md @@ -1,147 +1,98 @@ # rmcs_rl -RMCS（RoboMaster Control System）的 **RL 策略桥**：在「传统 RMCS 结构」与「独立进程里的 ONNX 策略」之间做翻译。 +RMCS 的 RL 部署包。控制进程通过组件接口组装观测，独立策略进程执行 ONNX 推理； +车辆侧消费器负责动作语义、模式切换、限位和电机控制。 -桥只做一件事：**按 YAML 词条把 RMCS 侧接口拼成有序 obs，发出去；把收到的 action 逐项写回 RMCS 侧的 RL 专属接口。** -推理在另一个进程（`policy_server`），PD / FSM / 关节语义在 RMCS 侧消费组件（P1，见「现状与边界」）。 +## 职责与源码 -详细文档： +| 层 | 文件 | 职责 | +| --- | --- | --- | +| 控制桥 | `src/rl_bridge.cpp` | 组件接口、观测发布、动作时效与契约门控 | +| 桥配置 | `src/rl_bridge/config.cpp` | 参数、维数、词条布局的启动检查 | +| 观测与历史 | `src/rl_bridge/observation.cpp`、`observation_history.cpp`、`observation_timeline.hpp` | 单帧观测、历史堆叠、序号时效与复位 | +| 动作通道 | `src/rl_bridge/action_channel.cpp` | ROS 回调与控制循环之间传递完整快照，控制循环不等待锁 | +| ROS 策略服务 | `src/policy_server.cpp` | 订阅观测、发布动作和可选状态 | +| 策略模型 | `src/policy/policy_model.cpp` | 元数据、模型 ID、归一化、裁剪、有限值检查 | +| 推理后端 | `src/policy/onnx_runtime.cpp` | ONNX Runtime 会话、张量形状及执行 | +| 子进程管理 | `src/policy_server_launcher.cpp` | 启停、退出回收、延时重启 | +| 参数解析 | `src/parameters.cpp` | 上述组件共用的类型及数值检查 | -- [架构与组件](planning/docs/architecture.md) -- [桥式重构设计（v2，定稿方案）](planning/docs/bridge-design.md) -- [构建、配置与部署](planning/docs/deployment.md) -- [策略模型合同（张量形状 + 元数据要求）](planning/docs/model-contract.md) +组件保持 RMCS 的 `.cpp` 类布局，构造函数直接注册输出。观测输入类型依赖其他组件的 +输出表，在 `before_pairing()` 中解析。非模板模型实现位于 `.cpp`，私有头文件放在 +`src/policy/`；控制桥不链接 ONNX Runtime。 -## 两条硬边界 +## 车辆控制链 -| 边界 | 通道 | 数量 | -|---|---|---| -| 桥 ↔ **RMCS 侧**（executor 内的组件） | 只有 `register_input` / `register_output` 接口，**没有任何 topic** | N 个观测输入 + M 个动作输出 + 使能/复位/事实位 | -| 桥 ↔ **策略进程**（不是 RMCS 组件，独立可执行文件） | ROS topic | **2 条必需**（`/obs`、`/action`）+ 1 条可选运维（`/policy_status`，缺省关） | +| 车辆 | 配置（位于 rmcs_bringup/config） | 消费及控制 | +| --- | --- | --- | +| wheel-leg | `wheel-leg-infantry-rl.yaml` | `WheelLegRlImu` → 桥 → `WheelLegRlConsumer` → 配对角度环 → 速度 PID → DM MIT 力矩 | +| deformable | `deformable-infantry-omni-rl.yaml` | 桥 → `DeformableRlSuspension` → `DeformableSuspensionArbiter` → 关节控制器 | -topic 存在的**唯一**原因是「策略进程独立」。想消除这 3 条 topic，只能把 ONNX 放回控制进程（进程内推理）—— -那正是桥要避免的事（ORT 会跟着 1 kHz 控制进程一起加载/崩溃/重启）。 +wheel-leg 的 IMU 观测使用 Body xyz；关节 offset、配对选弧和机械限位由硬件及车辆控制层管理。 +deformable 使用 RF、LF、LB、RB 的策略动作顺序，消费器根据标定把 RL 坐标转换为物理角； +RL 未就绪时仲裁器使用传统姿态目标。双下复位经组件接口清除历史、动作及控制状态。 -## 组件与可执行文件 +## 构建与启动 -| 名称 | 位置 | 依赖 ONNX Runtime | 职责 | -|---|---|---|---| -| `rmcs_rl::RlBridge` | 库 `rmcs_rl_bridge` | **否** | 观测组装、定频发布、动作回写、`valid/healthy/action_age` 事实位、合同指纹 | -| `rmcs_rl::PolicyServerLauncher` | 库 `rmcs_rl_bridge` | **否** | 随 executor 生命周期 fork/exec 独立的 `policy_server` 子进程，可退避重启、防孤儿 | -| `policy_server` | 可执行文件（`ros2 run rmcs_rl policy_server`） | **是**（唯一链接 ORT 的可执行文件） | 收一帧 obs → 归一化 → ONNX → 回一帧 action（纯反应式，无定时器） | -| 消息 `rmcs_rl/msg/*` | 本包 `msg/`（rosidl 生成，类型全名如 `rmcs_rl/msg/Observation`） | 否 | `Observation` / `Action` / `PolicyStatus` | +在 ROS 工作区内： -## 数据流 - -``` -RMCS 侧 output 接口 ──(桥：按词条拼 obs)──> obs 向量 ──topic /obs──> policy_server ──ONNX──> action - ▲ │ - └─ RMCS 侧 consumer（P1：FSM/PD/限位，写电机 control_*）<──(桥：逐项回写)── action 向量 <─┘ +```sh +colcon build --merge-install --symlink-install --packages-select rmcs_rl rmcs_core rmcs_bringup +source install/setup.bash ``` -## 部署到真机 - -本包**不含台架夹具**：链路必须挂到真实 RMCS 组件上跑。简要步骤（完整流程见 -[planning/docs/deployment.md](planning/docs/deployment.md)）： - -1. 改 `config/executor.yaml`：观测/动作词条与 `joint_*` 指向真机的接口路径， - `policy_server.rl_model_path` 指向已盖章的模型； -2. 把该文件复制到 `rmcs_bringup/config/.yaml`，或真机上 `--params-file` 直接加载； -3. 真机起两个进程： +使用对应车辆的 bringup 配置启动 RMCS；配置中的 `PolicyServerLauncher` 自动启动策略进程。 +需要独立调试策略进程时，将 launcher 的 `autostart` 设为 false，再运行： ```sh -ros2 run rmcs_executor rmcs_executor --ros-args --params-file -ros2 run rmcs_rl policy_server --ros-args --params-file +ros2 run rmcs_rl policy_server --ros-args --params-file <车辆配置.yaml> ``` -`layout_hash` 两侧必须一致；`valid=0` 的原因会直接打在桥的日志里（见 -[planning/docs/deployment.md](planning/docs/deployment.md) 的排障表）。注意 P1 的 RMCS 侧 consumer 尚未实现， -真机上桥恒 `valid=0`、不会输出权威动作（见「现状与边界」）。 +车辆配置统一放在 `rmcs_bringup/config/`；旧的、不含完整消费链的 `config/executor.yaml` 已移除。 -## 加一台新车型 / 加一条观测词条 +## 模型与契约 -1. 在部署 YAML 的 `rl_bridge.ros__parameters` 里写 `observation_terms`（**顺序就是 obs 索引顺序**） - 与 `action_terms`（`index=` 必须恰好是 `0..M-1` 的完整置换）。 -2. 只写路径 + 取值语义，**不要写 `type=`**：接口的 C++ 类型由桥在 `before_pairing` 里按 `output_map` - 的 `typeid` 自省（`take=x` / `take=vec3` / `transform=projected_gravity` 决定取值语义与 dim）。 - `type=` 是逃生口，只在自省失败（提示「无 producer 或类型不在候选表」）时才显式写。 -3. 词条引用的接口**必须在启动时已存在**（配对只在启动做一次，运行期热加接口不支持）； - 确实可能缺失的可选接口用 `default=` 兜底（仅标量路径词条）。 -4. 尺寸自检：`Σdim(observation_terms)` 与 `rl_obs_size`、`action_terms` 条数与 `rl_action_size` 写了就必须一致。 -5. 改完重新盖章 + 重新校验，**然后重启 executor**（新接口/新词条都要重新配对）： +模型输入为 float32 `obs[batch,N]`，输出为 float32 `actions[batch,M]`，batch 为 1 或动态。 +部署模型须含 `rmcs_obs_layout`、`rmcs_actions_layout`；建议带 `policy_layout_hash` 和版本。 +`history_length × 单帧维数 = rl_obs_size`。归一化均值和标准差必须成对提供，标准差为正数。 + +新模型先核对训练的观测顺序、坐标、基准角、缩放和频率，再盖章： ```sh -python3 src/rmcs_rl/tool/stamp_layout_metadata.py --model --from-config --node rl_bridge -python3 src/rmcs_rl/tool/check_policy_contract.py --config --node rl_bridge +bash src/rmcs_rl/tool/stamp_model.sh <模型.onnx> --config <车辆配置.yaml> --version <版本> ``` -> 词条**增删或维度变化**等于换了策略输入维度 → 必须重新导出模型（盖章只改 metadata，不改张量 shape）。 -> 仅「维度不变」的改名/换实现（例如 v1 的类型前缀 id → v2 去类型化 id）才只需要重盖章，不需要重训。 - -## 工具链回归 +按工具输出同步 `policy_server.rl_model_path`、`rl_bridge.expected_model_id`，然后验证： ```sh -# 不需要 executor：词条语法自检 + gen/stamp/check 正例 + 6 个负例 -bash src/rmcs_rl/tool/test_layout_contract.sh +python3 src/rmcs_rl/tool/check_policy_contract.py <模型.onnx> --config <车辆配置.yaml> --node rl_bridge --expect-model-id ``` -实测 **PASS=21 FAIL=0**。CI 里也会跑这一项，外加对 `models/*.onnx` 逐个做模型自检。 +盖章只写元数据；布局匹配不能证明训练侧的坐标或动作含义正确。 +更新模型或配置后重启 RMCS。模型或布局不匹配会锁存拒绝动作，需要重启恢复。 -## 工具链 +当前 `models/deformable_sps_V2.onnx` 缺少 `rmcs_obs_layout` 和 `rmcs_actions_layout`， +完整契约检查与策略服务会拒绝它。这是已有模型的部署缺口，需核对训练契约后补元数据； +不能只按张量维数推断其含义。 -| 工具 | 用途 | -|---|---| -| `tool/rl_layout.py` | 词条语法 / 规范串 / `layout_hash` 的**单一真源**（`python3 tool/rl_layout.py` 跑自检） | -| `tool/stamp_layout_metadata.py` | 部署 YAML → 写进 ONNX `metadata_props`（`rmcs_obs_layout` / `rmcs_actions_layout` / `policy_layout_hash` …） | -| `tool/check_policy_contract.py` | 两种模式：`MODEL`（模型自检：张量契约 + metadata 自洽，不比对 YAML，CI 用）/ `MODEL --config X [--node N] [--print-layout] [--expect-model-id H]`（YAML ↔ 张量 ↔ metadata 完整校验） | -| `tool/gen_synthetic_policy.py` | `--from-config X -o M.onnx`：生成零动作合成模型（`obs[1,N] → actions[1,M]`；ONNX 后端强制 `ir_version=10`，因为 ORT 1.20 拒收 IR 13） | -| `tool/test_layout_contract.sh` | Python 侧布局契约回归（含 6 个必须 FAIL 的负例） | -| `tool/install_rl_deps.sh` | `bash tool/install_rl_deps.sh local\|remote`：装 `libonnxruntime.so.1`（仅 `policy_server` 需要） | +## 运行接口 -## 现状与边界 +- `/obs`、`/action`：两个进程间的 ROS 消息。 +- `/policy_status`：可选模型身份和推理耗时信息。 +- 控制进程内部使用组件接口 `/valid`、`healthy`、`action_age` 和配置的动作输出。 +- 动作必须对应最近两次有效观测之一且未超时；复位前的动作不能重新获得控制权。 +- `invalid_value` 可选 `nan`、`zero`、`hold`；实际车辆使用 `"nan"` 让消费器处理失效。 -- **P0 已完成**：桥、策略进程、消息定义、合同指纹（v2）、工具链。 -- **P1 进行中**：RMCS 侧 consumer（FSM / PREPARE / kp,kd / 限位 / NaN 让位）。 - deformable 已有消费侧落地（`DeformableRlSuspension` / 仲裁）；wheel-leg 尚未迁到桥式， - 因此轮腿上桥若挂载且 `enable_default: false` → **桥恒 `valid=0`**，不会输出权威动作。 -- 桥**从不写电机 `control_*` 接口**：executor 禁止同名 output，电机控制权始终在 RMCS 侧消费组件手上， - 所以「RL 接管 / 退回传统控制」不需要仲裁组件（consumer 用写 NaN 让位）。 -- 观测接口运行期热加不支持（配对只在启动做一次）；`contract_ok` 一旦因合同不符锁存为 false， - 当前实现**只能靠重启 executor 进程恢复**。 +## 工具和测试 -## 目录结构 +`tool/` 仅保留模型校验、盖章和依赖安装工具。离线模型生成及回归放在 `test/`， +不安装到部署目录；合成模型不用于实车启动。历史临时脚本与生成报告可从 Git 历史获取。 +```sh +colcon build --merge-install --symlink-install --packages-select rmcs_rl rmcs_core --cmake-args -DBUILD_TESTING=ON +colcon test --merge-install --packages-select rmcs_rl rmcs_core +PYTHON=<带 onnx、onnxruntime、PyYAML 的 Python> bash src/rmcs_rl/test/test_layout_contract.sh ``` -rmcs_rl/ -├── README.md # 本页（入口） -├── config/ -│ └── executor.yaml # 实车配置模板（轮腿；复制到 rmcs_bringup/config/.yaml） -├── planning/ -│ └── docs/ -│ ├── architecture.md # 进程/组件、数据流、接口清单、valid 状态机 -│ ├── bridge-design.md # 重构定稿方案（权威设计） -│ ├── deployment.md # 构建 → 模型 → 配置 → 运行 → 验证 → 交接 -│ ├── model-contract.md # 模型张量合同与 metadata 清单 -│ └── deformable-rl-pipeline.md # deformable 消费侧落地说明 -├── include/rmcs_rl/ # 头文件（安装到 include/rmcs_rl/，与 rosidl 生成头一致） -│ ├── rl_layout.hpp # FNV-1a64 / layout_hash / model_id（与 tool/rl_layout.py 同构） -│ ├── onnxruntime_inference.hpp -│ └── rl_bridge/ # 桥内部辅助模块头文件 -├── models/ # 策略 ONNX（安装到 share/rmcs_rl/models/） -├── msg/ # Observation / Action / PolicyStatus（rosidl 生成，类型名 rmcs_rl/msg/*） -├── src/ # 仅实现文件 -│ ├── rl_bridge.cpp # 桥（RlBridge 组件） -│ ├── rl_bridge/ # 桥内部辅助模块实现 -│ ├── policy_server.cpp # 策略进程（独立可执行文件，非 executor 组件） -│ └── policy_server_launcher.cpp # PolicyServerLauncher 组件（拉起/重启策略进程） -├── tool/ # 见上表 -├── plugins.xml # rmcs_rl_bridge 的 pluginlib 导出 -└── CMakeLists.txt -``` - -## 相关 -- 集成示例：`rmcs_bringup/config/deformable-infantry-omni-rl.yaml`（桥式 + launcher）； - `wheel-leg-infantry-rl.yaml` 尚未挂 RL 桥（待迁到桥式） -- 训练侧：任何能导出 `obs[1,N] → actions[1,M]` 且带 `rmcs_obs_layout` / `rmcs_actions_layout` metadata 的 - ONNX 仓库（Isaac Lab / legged_gym / rsl_rl …）都可以接 +C++ 回归覆盖推理归一化、历史帧与跨线程动作快照；Python 回归覆盖布局解析、盖章及错误契约拒绝。 +车辆包保留 DM 使能、帧解码、闭链几何、Body IMU 以及 MuJoCo 查看器回归。 diff --git a/config/executor.yaml b/config/executor.yaml deleted file mode 100644 index d5559fd..0000000 --- a/config/executor.yaml +++ /dev/null @@ -1,98 +0,0 @@ - -rmcs_executor: - ros__parameters: - update_rate: 1000.0 - components: - - rmcs_core::hardware::WheelLegInfantryRL -> wheel_leg_infantry_rl - - rmcs_core::controller::chassis::WheelLegChassisController -> wheel_leg_chassis_controller - - rmcs_core::controller::chassis::WheelLegRlImu -> wheel_leg_rl_imu - - rmcs_rl::RlBridge -> rl_bridge - - rmcs_rl::PolicyServerLauncher -> policy_server_launcher - -wheel_leg_infantry_rl: - ros__parameters: - board_serial: "" - -wheel_leg_chassis_controller: - ros__parameters: - rl_state_path: "/wheel_leg/rl/state" - vx_max: 2.5 - yaw_rate_max: 3.0 - heading_kp: 3.0 - deadzone: 0.08 - command_height_min: 0.26 - command_height_max: 0.28 - default_command_height: 0.27 - -rl_bridge: - ros__parameters: - history_length: 1 - rl_base: "/wheel_leg/rl" - policy_rate: 50.0 - max_action_age: 0.04 # 缺省 = 2 / policy_rate；超时 → valid=0（绝不保持旧动作） - - rl_obs_size: 35 - rl_action_size: 6 - - enable_interface: "/wheel_leg/rl/enable" - enable_default: false - invalid_value: "nan" # 必须加引号！不加会被 YAML 解析成 float，桥启动即失败 - reset_interface: "/chassis/reset_count" - expected_model_id: "0xd4612f6cd48a6e9c" - - joint_names: [left_hip_joint, left_knee_joint, right_hip_joint, right_knee_joint, left_wheel, right_wheel] - joint_base_path: "/wheel_leg" - joint_angle_suffix: "/angle" - joint_velocity_suffix: "/velocity" - joint_torque_suffix: "/torque" - default_joint_pos: - left_hip_joint: 0.0 - left_knee_joint: 0.0 - right_hip_joint: 0.0 - right_knee_joint: 0.0 - left_wheel: 0.0 - right_wheel: 0.0 - - observation_terms: - - index=0 path=/chassis/control_velocity take=x - - index=1 path=/chassis/control_velocity take=y - - index=2 path=/chassis/control_velocity take=z - - index=3 path=/chassis/control_height scale=5.0 - # 训练 IMU 观测直接使用车身 Body xyz；URDF 轴向差异不对 IMU 做 90° 换轴。 - - index=4 path=/wheel_leg/rl/imu/angular_velocity take=vec3 scale=0.5 - - index=7 path=/wheel_leg/rl/imu/projected_gravity take=vec3 - - index=10 type=joint_pos joints=left_hip_joint,left_knee_joint,right_hip_joint,right_knee_joint relative=true - - index=14 type=joint_pos joints=left_wheel,right_wheel zero=true - - index=16 type=joint_vel joints=left_hip_joint,left_knee_joint,right_hip_joint,right_knee_joint scale=0.1 - - index=20 type=joint_vel joints=left_wheel,right_wheel scale=0.1 - - index=22 type=last_action - - index=28 type=constant value=1,0,0,0,0,0,0 - - action_terms: - - index=0 output=/wheel_leg/rl/action/left_hip name=left_hip - - index=1 output=/wheel_leg/rl/action/left_knee name=left_knee - - index=2 output=/wheel_leg/rl/action/right_hip name=right_hip - - index=3 output=/wheel_leg/rl/action/right_knee name=right_knee - - index=4 output=/wheel_leg/rl/action/left_wheel name=left_wheel - - index=5 output=/wheel_leg/rl/action/right_wheel name=right_wheel - -policy_server: - ros__parameters: - rl_base: "/wheel_leg/rl" # 必须与桥一致 - rl_model_path: "models/wheel_leg_v1.onnx" - input_name: "obs" - output_name: "actions" - normalization_from_metadata: true - publish_status: false - status_rate: 2.0 - -# 由 executor 进程内组件随 rmcs 一起拉起 policy_server（不改 bringup/launch/服务）。 -# params_file 相对 share/rmcs_bringup/config 解析，也可写绝对路径； -# 复制本模板到 rmcs_bringup/config/.yaml 后，改成那个文件名。 -policy_server_launcher: - ros__parameters: - autostart: true - params_file: "executor.yaml" - respawn: true - respawn_delay: 1.0 - poll_interval: 0.5 diff --git a/include/rmcs_rl/onnxruntime_inference.hpp b/include/rmcs_rl/onnxruntime_inference.hpp deleted file mode 100644 index 6555ff4..0000000 --- a/include/rmcs_rl/onnxruntime_inference.hpp +++ /dev/null @@ -1,192 +0,0 @@ -#pragma once - -#include - -#include -#include -#include -#include -#include -#include -#include -#include -#include -#include - -namespace rmcs_rl { - -class OnnxRuntimeInference { -public: - struct Config { - std::string model_path; - std::string input_name = "obs"; - std::string output_name = "actions"; - std::size_t input_size = 0; - std::size_t output_size = 0; - }; - - OnnxRuntimeInference() = default; - - OnnxRuntimeInference(const OnnxRuntimeInference&) = delete; - OnnxRuntimeInference& operator=(const OnnxRuntimeInference&) = delete; - - bool load(const Config& config) { - std::string ignored; - return load(config, ignored); - } - - bool load(const Config& config, std::string& error) { - config_ = config; - session_.reset(); - error.clear(); - try { - session_options_.SetGraphOptimizationLevel(GraphOptimizationLevel::ORT_ENABLE_ALL); - session_options_.SetIntraOpNumThreads(1); - session_options_.SetInterOpNumThreads(1); - session_ = - std::make_unique(env_, config_.model_path.c_str(), session_options_); - - if (session_->GetInputCount() != 1 || session_->GetOutputCount() != 1) { - error = "model must have exactly 1 input and 1 output, got " - + std::to_string(session_->GetInputCount()) + " input(s) / " - + std::to_string(session_->GetOutputCount()) + " output(s)"; - session_.reset(); - return false; - } - - const auto actual_input = session_->GetInputNameAllocated(0, allocator_); - const auto actual_output = session_->GetOutputNameAllocated(0, allocator_); - if (actual_input.get() != config_.input_name - || actual_output.get() != config_.output_name) { - error = "tensor names must be '" + config_.input_name + "' / '" - + config_.output_name + "', got '" + actual_input.get() + "' / '" - + actual_output.get() + "'"; - session_.reset(); - return false; - } - - const auto input_type_info = session_->GetInputTypeInfo(0); - const auto output_type_info = session_->GetOutputTypeInfo(0); - const auto input_info = input_type_info.GetTensorTypeAndShapeInfo(); - const auto output_info = output_type_info.GetTensorTypeAndShapeInfo(); - if (input_info.GetElementType() != ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT - || output_info.GetElementType() != ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT) { - error = "tensor element type must be float32"; - session_.reset(); - return false; - } - - const auto input_shape = input_info.GetShape(); - const auto output_shape = output_info.GetShape(); - if (input_shape.size() != 2 || output_shape.size() != 2) { - error = "tensor rank must be 2 ([batch, N])"; - session_.reset(); - return false; - } - if ((input_shape[0] != 1 && input_shape[0] != -1) - || (output_shape[0] != 1 && output_shape[0] != -1)) { - error = "batch dimension must be 1 or dynamic"; - session_.reset(); - return false; - } - if (input_shape[1] <= 0 || output_shape[1] <= 0) { - error = "feature dimensions must be concrete positive values"; - session_.reset(); - return false; - } - - const auto model_input_size = static_cast(input_shape[1]); - const auto model_output_size = static_cast(output_shape[1]); - if (config_.input_size != 0 && config_.input_size != model_input_size) { - error = "configured rl_obs_size=" + std::to_string(config_.input_size) - + " but model input shape is [1," + std::to_string(model_input_size) + "]"; - session_.reset(); - return false; - } - if (config_.output_size != 0 && config_.output_size != model_output_size) { - error = "configured rl_action_size=" + std::to_string(config_.output_size) - + " but model output shape is [1," + std::to_string(model_output_size) + "]"; - session_.reset(); - return false; - } - - config_.input_size = model_input_size; - config_.output_size = model_output_size; - // This deployment path runs one observation at a time. Normalize a - // symbolic batch dimension to 1 for Ort::CreateTensor below. - input_shape_ = {1, static_cast(model_input_size)}; - output_shape_ = {1, static_cast(model_output_size)}; - input_buffer_.assign(config_.input_size, 0.0F); - output_buffer_.assign(config_.output_size, 0.0F); - memory_info_ = Ort::MemoryInfo::CreateCpu(OrtArenaAllocator, OrtMemTypeDefault); - return true; - } catch (const Ort::Exception& exception) { - error = std::string{"ONNX Runtime: "} + exception.what(); - session_.reset(); - return false; - } - } - - [[nodiscard]] bool ready() const { return session_ != nullptr; } - - [[nodiscard]] const std::string& model_path() const { return config_.model_path; } - [[nodiscard]] std::size_t input_size() const { return config_.input_size; } - [[nodiscard]] std::size_t output_size() const { return config_.output_size; } - - [[nodiscard]] std::optional metadata(const std::string& key) const { - if (!session_) - return std::nullopt; - try { - auto model_metadata = session_->GetModelMetadata(); - auto value = model_metadata.LookupCustomMetadataMapAllocated(key.c_str(), allocator_); - if (!value) - return std::nullopt; - return std::string(value.get()); - } catch (const Ort::Exception&) { - return std::nullopt; - } - } - - bool run(std::span input, std::span output) { - if (!session_ || input.size() < config_.input_size || output.size() < config_.output_size) - return false; - try { - std::copy( - input.begin(), input.begin() + static_cast(config_.input_size), - input_buffer_.begin()); - Ort::Value input_tensor = Ort::Value::CreateTensor( - memory_info_, input_buffer_.data(), config_.input_size, input_shape_.data(), - input_shape_.size()); - Ort::Value output_tensor = Ort::Value::CreateTensor( - memory_info_, output_buffer_.data(), config_.output_size, output_shape_.data(), - output_shape_.size()); - - const char* input_names[] = {config_.input_name.c_str()}; - const char* output_names[] = {config_.output_name.c_str()}; - auto outputs = session_->Run( - Ort::RunOptions{nullptr}, input_names, &input_tensor, 1, output_names, 1); - if (outputs.size() != 1 || !outputs[0].IsTensor()) - return false; - const float* data = outputs[0].GetTensorData(); - std::copy( - data, data + static_cast(config_.output_size), output.begin()); - return true; - } catch (const Ort::Exception&) { - return false; - } - } - -private: - Ort::Env env_{ORT_LOGGING_LEVEL_WARNING, "rmcs_rl"}; - Ort::SessionOptions session_options_; - Ort::AllocatorWithDefaultOptions allocator_; - Ort::MemoryInfo memory_info_{nullptr}; - std::unique_ptr session_; - std::vector input_shape_; - std::vector output_shape_; - std::vector input_buffer_; - std::vector output_buffer_; - Config config_; -}; - -} // namespace rmcs_rl diff --git a/include/rmcs_rl/rl_bridge/parameters.hpp b/include/rmcs_rl/parameters.hpp similarity index 100% rename from include/rmcs_rl/rl_bridge/parameters.hpp rename to include/rmcs_rl/parameters.hpp diff --git a/include/rmcs_rl/rl_bridge/action_channel.hpp b/include/rmcs_rl/rl_bridge/action_channel.hpp index b46a479..e948bf4 100644 --- a/include/rmcs_rl/rl_bridge/action_channel.hpp +++ b/include/rmcs_rl/rl_bridge/action_channel.hpp @@ -1,11 +1,8 @@ #pragma once -#include -#include -#include #include -#include #include +#include #include #include @@ -18,42 +15,14 @@ namespace rmcs_rl { class ActionChannel { public: - void resize(std::size_t action_size) { incoming_.action.assign(action_size, 0.0); } - - void store(const rmcs_rl::msg::Action& message) { - const auto received = std::chrono::steady_clock::now(); - - const std::uint64_t sequence = action_sequence_.load(std::memory_order_relaxed); - action_sequence_.store(sequence + 1, std::memory_order_relaxed); - std::atomic_thread_fence(std::memory_order_release); - - incoming_.obs_seq = message.obs_seq; - incoming_.layout_hash = message.layout_hash; - incoming_.model_id = message.model_id; - incoming_.received = received; - std::copy(message.action.begin(), message.action.end(), incoming_.action.begin()); - - std::atomic_thread_fence(std::memory_order_release); - action_sequence_.store(sequence + 2, std::memory_order_relaxed); - } - - bool try_read(ActionSnapshot& snapshot) { - for (int attempt = 0; attempt < 4; ++attempt) { - const std::uint64_t before = action_sequence_.load(std::memory_order_relaxed); - if (before == 0 || (before & 1U) != 0) - return false; - std::atomic_thread_fence(std::memory_order_acquire); - snapshot = incoming_; - std::atomic_thread_fence(std::memory_order_acquire); - if (action_sequence_.load(std::memory_order_relaxed) == before) - return true; - } - return false; - } + void resize(std::size_t action_size); + void store(const rmcs_rl::msg::Action& message); + bool try_read(ActionSnapshot& snapshot); private: ActionSnapshot incoming_; - alignas(64) std::atomic action_sequence_{0}; + std::mutex mutex_; + bool received_ = false; }; void write_actions( diff --git a/include/rmcs_rl/rl_bridge/config.hpp b/include/rmcs_rl/rl_bridge/config.hpp new file mode 100644 index 0000000..7b5ab24 --- /dev/null +++ b/include/rmcs_rl/rl_bridge/config.hpp @@ -0,0 +1,36 @@ +#pragma once + +#include +#include +#include +#include +#include + +#include +#include +#include + +namespace rmcs_rl { + +struct BridgeConfig { + JointConfig joint_config; + std::vector obs_terms; + std::vector action_terms; + std::size_t obs_size = 0; + std::size_t obs_frame_size = 0; + std::size_t history_length = 1; + std::size_t action_size = 0; + std::string rl_base; + double policy_rate = 50.0; + double max_action_age = 0.04; + std::chrono::nanoseconds pub_period{}; + std::uint64_t expected_model_id = 0; + InvalidMode invalid_mode = InvalidMode::kNaN; + std::string enable_path; + bool enable_default = false; + std::string reset_path; +}; + +BridgeConfig load_bridge_config(rclcpp::Node& node); + +} // namespace rmcs_rl diff --git a/include/rmcs_rl/rl_bridge/observation_history.hpp b/include/rmcs_rl/rl_bridge/observation_history.hpp new file mode 100644 index 0000000..b08f31d --- /dev/null +++ b/include/rmcs_rl/rl_bridge/observation_history.hpp @@ -0,0 +1,22 @@ +#pragma once + +#include +#include +#include + +namespace rmcs_rl { + +// Frames are oldest first; startup and reset fill the history with the first valid frame. +class ObservationHistory { +public: + ObservationHistory(std::size_t frame_size, std::size_t history_length); + const std::vector& append(std::span frame); + void reset(); + +private: + std::size_t frame_size_; + std::vector values_; + bool initialized_ = false; +}; + +} // namespace rmcs_rl diff --git a/include/rmcs_rl/rl_bridge/observation_timeline.hpp b/include/rmcs_rl/rl_bridge/observation_timeline.hpp new file mode 100644 index 0000000..bd322d2 --- /dev/null +++ b/include/rmcs_rl/rl_bridge/observation_timeline.hpp @@ -0,0 +1,49 @@ +#pragma once + +#include +#include +#include + +namespace rmcs_rl { + +class ObservationTimeline { +public: + using Clock = std::chrono::steady_clock; + + bool due(Clock::time_point now, std::chrono::nanoseconds period) const { + return !started_ || now - current_time_ >= period; + } + + std::uint64_t publish(Clock::time_point now) { + previous_valid_ = started_; + previous_time_ = current_time_; + current_time_ = now; + started_ = true; + return ++sequence_; + } + + double age(std::uint64_t sequence, Clock::time_point now) const { + if (started_ && sequence == sequence_) + return std::chrono::duration(now - current_time_).count(); + if (previous_valid_ && sequence == sequence_ - 1) + return std::chrono::duration(now - previous_time_).count(); + return std::numeric_limits::quiet_NaN(); + } + + void reset() { + // Keep IDs monotonic so a delayed action cannot match a new frame after reset. + started_ = previous_valid_ = false; + current_time_ = previous_time_ = {}; + } + + [[nodiscard]] std::uint64_t sequence() const { return sequence_; } + +private: + Clock::time_point current_time_{}; + Clock::time_point previous_time_{}; + std::uint64_t sequence_ = 0; + bool started_ = false; + bool previous_valid_ = false; +}; + +} // namespace rmcs_rl diff --git a/include/rmcs_rl/rl_bridge/types.hpp b/include/rmcs_rl/rl_bridge/types.hpp index 705cbe9..a8d7f35 100644 --- a/include/rmcs_rl/rl_bridge/types.hpp +++ b/include/rmcs_rl/rl_bridge/types.hpp @@ -1,6 +1,5 @@ #pragma once -#include #include #include #include @@ -10,7 +9,6 @@ #include #include -#include #include #include @@ -81,7 +79,6 @@ struct ActionTerm { struct Slot { std::string path; Binding binding = Binding::kDouble; - bool required = true; std::unique_ptr> double_value; std::unique_ptr> bool_value; std::unique_ptr> int_value; @@ -98,7 +95,6 @@ struct ActionSnapshot { std::uint64_t layout_hash = 0; std::uint64_t model_id = 0; std::vector action; - std::chrono::steady_clock::time_point received{}; }; } // namespace rmcs_rl diff --git a/models/policy_drive.onnx b/models/policy_drive.onnx deleted file mode 100644 index cdbb0b063d68463c0f8e9162eecfcb0c30c92409..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 1417 zcmaKs!A{#i5Qgh`jki+>){0glM<03!6)p(@5((N6I1q^gf>SS+6A-Z!>NFI4+C;xmiyIyH4d-5ZR?}wwB)!5$IZgl zqQsBWWRfQS=i1wO%$2j%dJU|{V4U96tI}}nzBJxUf6s=1Gqo}Qi@!rc?^v`%%3LPZ zD3ofHNQq@q%|fYWi4zZit6nm7yDE5|8;OXejD0l%*L7GT$o{p)6(5`Euflt^5UsF}@ zDu_muYh}JGbTrSrPf3hYpImoZWY8*x1JDu+J zwcl)E&-!J47YOaTCYpQ~2b99PI4JAlkDh$)Ft-au+GQfyC@ygNoRUw1z<87@DLWV@ zA>Mg4%j=E9i7T{Ka2JG;e|sNHM)i-std_msgs pluginlib - ament_lint_auto - ament_lint_common + ament_cmake_gtest rosidl_interface_packages diff --git a/src/rl_bridge/parameters.cpp b/src/parameters.cpp similarity index 80% rename from src/rl_bridge/parameters.cpp rename to src/parameters.cpp index f230b7d..ec1a401 100644 --- a/src/rl_bridge/parameters.cpp +++ b/src/parameters.cpp @@ -1,4 +1,4 @@ -#include +#include #include #include @@ -17,7 +17,7 @@ std::optional number_parameter(rclcpp::Node& node, const std::string& na case rclcpp::ParameterType::PARAMETER_DOUBLE: return parameter.as_double(); case rclcpp::ParameterType::PARAMETER_INTEGER: return static_cast(parameter.as_int()); case rclcpp::ParameterType::PARAMETER_NOT_SET: return std::nullopt; - default: throw std::invalid_argument("RlBridge: parameter '" + name + "' must be a number"); + default: throw std::invalid_argument("rmcs_rl: parameter '" + name + "' must be a number"); } } @@ -26,7 +26,7 @@ double number_or(rclcpp::Node& node, const std::string& name, double fallback) { if (!value.has_value()) return fallback; if (!std::isfinite(*value)) - throw std::invalid_argument("RlBridge: parameter '" + name + "' is not finite"); + throw std::invalid_argument("rmcs_rl: parameter '" + name + "' is not finite"); return *value; } @@ -40,8 +40,8 @@ std::uint64_t parse_u64(const std::string& text, const std::string& name) { return static_cast(value); } catch (const std::exception&) { throw std::invalid_argument( - "RlBridge: parameter '" + name - + "' must be a decimal or 0x-prefixed 64-bit id, got '" + text + "'"); + "rmcs_rl: parameter '" + name + "' must be a decimal or 0x-prefixed 64-bit id, got '" + + text + "'"); } } @@ -51,7 +51,7 @@ std::optional integer_parameter(rclcpp::Node& node, const std::str return std::nullopt; const auto rounded = std::llround(*value); if (std::abs(*value - static_cast(rounded)) > 1e-9) - throw std::invalid_argument("RlBridge: parameter '" + name + "' must be an integer"); + throw std::invalid_argument("rmcs_rl: parameter '" + name + "' must be an integer"); return rounded; } @@ -66,7 +66,7 @@ bool bool_or(rclcpp::Node& node, const std::string& name, bool fallback) { if (parameter.get_type() == rclcpp::ParameterType::PARAMETER_NOT_SET) return fallback; if (parameter.get_type() != rclcpp::ParameterType::PARAMETER_BOOL) - throw std::invalid_argument("RlBridge: parameter '" + name + "' must be a boolean"); + throw std::invalid_argument("rmcs_rl: parameter '" + name + "' must be a boolean"); return parameter.as_bool(); } @@ -81,7 +81,7 @@ std::string string_or(rclcpp::Node& node, const std::string& name, const std::st if (parameter.get_type() == rclcpp::ParameterType::PARAMETER_NOT_SET) return fallback; if (parameter.get_type() != rclcpp::ParameterType::PARAMETER_STRING) - throw std::invalid_argument("RlBridge: parameter '" + name + "' must be a string"); + throw std::invalid_argument("rmcs_rl: parameter '" + name + "' must be a string"); return parameter.as_string(); } @@ -91,7 +91,7 @@ std::vector string_array_or(rclcpp::Node& node, const std::string& if (!node.get_parameter(name, value)) return {}; } catch (const std::exception&) { - throw std::invalid_argument("RlBridge: parameter '" + name + "' must be a list of strings"); + throw std::invalid_argument("rmcs_rl: parameter '" + name + "' must be a list of strings"); } return value; } diff --git a/src/policy/onnx_runtime.cpp b/src/policy/onnx_runtime.cpp new file mode 100644 index 0000000..2ea9857 --- /dev/null +++ b/src/policy/onnx_runtime.cpp @@ -0,0 +1,76 @@ +#include "onnx_runtime.hpp" + +#include +#include + +namespace rmcs_rl { + +OnnxRuntime::OnnxRuntime( + const std::string& model_path, const std::string& input_name, const std::string& output_name) + : input_name_(input_name) + , output_name_(output_name) { + Ort::SessionOptions options; + options.SetGraphOptimizationLevel(GraphOptimizationLevel::ORT_ENABLE_ALL); + options.SetIntraOpNumThreads(1); + options.SetInterOpNumThreads(1); + session_ = Ort::Session{env_, model_path.c_str(), options}; + + if (session_.GetInputCount() != 1 || session_.GetOutputCount() != 1) + throw std::invalid_argument("model must have exactly one input and one output"); + const auto actual_input = session_.GetInputNameAllocated(0, allocator_); + const auto actual_output = session_.GetOutputNameAllocated(0, allocator_); + if (actual_input.get() != input_name_ || actual_output.get() != output_name_) + throw std::invalid_argument( + "tensor names must be '" + input_name_ + "' / '" + output_name_ + "', got '" + + actual_input.get() + "' / '" + actual_output.get() + "'"); + + const auto input_type = session_.GetInputTypeInfo(0); + const auto output_type = session_.GetOutputTypeInfo(0); + const auto input_info = input_type.GetTensorTypeAndShapeInfo(); + const auto output_info = output_type.GetTensorTypeAndShapeInfo(); + if (input_info.GetElementType() != ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT + || output_info.GetElementType() != ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT) + throw std::invalid_argument("tensor element type must be float32"); + + const auto input_shape = input_info.GetShape(); + const auto output_shape = output_info.GetShape(); + if (input_shape.size() != 2 || output_shape.size() != 2) + throw std::invalid_argument("tensor rank must be 2 ([batch, N])"); + if ((input_shape[0] != 1 && input_shape[0] != -1) + || (output_shape[0] != 1 && output_shape[0] != -1)) + throw std::invalid_argument("batch dimension must be 1 or dynamic"); + if (input_shape[1] <= 0 || output_shape[1] <= 0) + throw std::invalid_argument("feature dimensions must be concrete positive values"); + + // The server evaluates one robot observation, even when the exported batch is dynamic. + input_shape_ = {1, input_shape[1]}; + input_buffer_.resize(static_cast(input_shape[1])); + output_size_ = static_cast(output_shape[1]); +} + +std::optional OnnxRuntime::metadata(const char* key) const { + const auto model_metadata = session_.GetModelMetadata(); + const auto value = model_metadata.LookupCustomMetadataMapAllocated(key, allocator_); + if (!value) + return std::nullopt; + return std::string{value.get()}; +} + +void OnnxRuntime::run(std::span input, std::span output) { + if (input.size() != input_size() || output.size() != output_size()) + throw std::invalid_argument("inference buffers do not match model dimensions"); + std::copy(input.begin(), input.end(), input_buffer_.begin()); + auto tensor = Ort::Value::CreateTensor( + memory_info_, input_buffer_.data(), input_buffer_.size(), input_shape_.data(), + input_shape_.size()); + const char* input_names[] = {input_name_.c_str()}; + const char* output_names[] = {output_name_.c_str()}; + const auto outputs = + session_.Run(Ort::RunOptions{nullptr}, input_names, &tensor, 1, output_names, 1); + if (outputs.size() != 1 || !outputs[0].IsTensor() + || outputs[0].GetTensorTypeAndShapeInfo().GetElementCount() != output_size()) + throw std::runtime_error("inference output does not match model dimensions"); + std::copy_n(outputs[0].GetTensorData(), output_size(), output.begin()); +} + +} // namespace rmcs_rl diff --git a/src/policy/onnx_runtime.hpp b/src/policy/onnx_runtime.hpp new file mode 100644 index 0000000..791275e --- /dev/null +++ b/src/policy/onnx_runtime.hpp @@ -0,0 +1,39 @@ +#pragma once + +#include +#include +#include +#include +#include +#include +#include + +#include + +namespace rmcs_rl { + +class OnnxRuntime { +public: + OnnxRuntime( + const std::string& model_path, const std::string& input_name, + const std::string& output_name); + + [[nodiscard]] std::size_t input_size() const { return input_buffer_.size(); } + [[nodiscard]] std::size_t output_size() const { return output_size_; } + [[nodiscard]] std::optional metadata(const char* key) const; + + void run(std::span input, std::span output); + +private: + Ort::Env env_{ORT_LOGGING_LEVEL_WARNING, "rmcs_rl"}; + Ort::AllocatorWithDefaultOptions allocator_; + Ort::MemoryInfo memory_info_{Ort::MemoryInfo::CreateCpu(OrtArenaAllocator, OrtMemTypeDefault)}; + Ort::Session session_{nullptr}; + std::string input_name_; + std::string output_name_; + std::array input_shape_{}; + std::vector input_buffer_; + std::size_t output_size_ = 0; +}; + +} // namespace rmcs_rl diff --git a/src/policy/policy_model.cpp b/src/policy/policy_model.cpp new file mode 100644 index 0000000..f950d14 --- /dev/null +++ b/src/policy/policy_model.cpp @@ -0,0 +1,145 @@ +#include "policy_model.hpp" + +#include +#include +#include + +#include + +namespace rmcs_rl { +namespace { + +double parse_number(const std::string& text, const char* key) { + std::size_t consumed = 0; + const double value = std::stod(text, &consumed); + if (consumed != text.size() || !std::isfinite(value)) + throw std::invalid_argument(std::string{"non-finite or invalid metadata: "} + key); + return value; +} + +std::vector parse_numbers(const std::string& text, const char* key) { + std::vector result; + for (std::size_t begin = 0; begin < text.size();) { + begin = text.find_first_not_of(", \t", begin); + if (begin == std::string::npos) + break; + const auto end = text.find_first_of(", \t", begin); + result.push_back(parse_number(text.substr(begin, end - begin), key)); + if (end == std::string::npos) + break; + begin = end; + } + return result; +} + +std::optional clip_metadata(const OnnxRuntime& runtime, const char* key) { + const auto text = runtime.metadata(key); + if (!text || text->empty()) + return std::nullopt; + const double value = parse_number(*text, key); + if (value <= 0.0) + throw std::invalid_argument(std::string{key} + " must be positive"); + return value; +} + +} // namespace + +PolicyModel::PolicyModel(const Config& config) + : runtime_(config.path, config.input_name, config.output_name) { + info_.path = config.path; + info_.obs_size = runtime_.input_size(); + info_.action_size = runtime_.output_size(); + std::string error; + if (!model_id_of_file(config.path, info_.model_id, error)) + throw std::runtime_error(error); + + info_.obs_signature = runtime_.metadata("rmcs_obs_layout").value_or(""); + info_.actions_signature = runtime_.metadata("rmcs_actions_layout").value_or(""); + info_.version = runtime_.metadata("policy_version").value_or(""); + if (info_.obs_signature.empty() || info_.actions_signature.empty()) + throw std::invalid_argument( + "model is missing rmcs_obs_layout / rmcs_actions_layout; " + "stamp it with tool/stamp_layout_metadata.py before deploying"); + info_.layout_hash = rmcs_rl::layout_hash( + info_.obs_signature, info_.actions_signature, info_.obs_size, info_.action_size); + if (const auto declared = runtime_.metadata("policy_layout_hash"); + declared && !declared->empty()) { + std::size_t consumed = 0; + const auto hash = std::stoull(*declared, &consumed, 16); + if (consumed != declared->size() || hash != info_.layout_hash) + throw std::invalid_argument( + "policy_layout_hash does not match layout metadata: expected " + + hex16(info_.layout_hash)); + } + + load_normalization(config); + obs_buffer_.resize(info_.obs_size); + action_buffer_.resize(info_.action_size); +} + +void PolicyModel::load_normalization(const Config& config) { + if (config.normalization_from_metadata) { + const auto mean = runtime_.metadata("rmcs_obs_mean"); + const auto deviation = runtime_.metadata("rmcs_obs_std"); + if (mean.has_value() != deviation.has_value()) + throw std::invalid_argument("rmcs_obs_mean and rmcs_obs_std must appear together"); + if (mean && deviation) { + obs_mean_ = parse_numbers(*mean, "rmcs_obs_mean"); + obs_std_ = parse_numbers(*deviation, "rmcs_obs_std"); + if (obs_mean_.size() != info_.obs_size || obs_std_.size() != info_.obs_size) + throw std::invalid_argument("normalization metadata does not match obs_size"); + if (std::any_of( + obs_std_.begin(), obs_std_.end(), [](double value) { return value <= 0; })) + throw std::invalid_argument("rmcs_obs_std must be positive"); + } + obs_clip_ = clip_metadata(runtime_, "rmcs_obs_clip"); + action_clip_ = clip_metadata(runtime_, "rmcs_action_clip"); + } + if (config.obs_clip) + obs_clip_ = config.obs_clip; + if (config.action_clip) + action_clip_ = config.action_clip; + for (const auto clip : {obs_clip_, action_clip_}) + if (clip && (!std::isfinite(*clip) || *clip < 0.0)) + throw std::invalid_argument("clip parameter must be finite and non-negative"); +} + +bool PolicyModel::run( + std::span observation, std::span action, std::string& error) { + error.clear(); + if (observation.size() != info_.obs_size || action.size() != info_.action_size) { + error = "observation/action dimensions do not match model"; + return false; + } + for (std::size_t i = 0; i < observation.size(); ++i) { + double value = observation[i]; + if (!obs_mean_.empty()) + value = (value - obs_mean_[i]) / obs_std_[i]; + if (obs_clip_) + value = std::clamp(value, -*obs_clip_, *obs_clip_); + obs_buffer_[i] = static_cast(value); + if (!std::isfinite(obs_buffer_[i])) { + error = "non-finite observation at index " + std::to_string(i); + return false; + } + } + try { + runtime_.run(obs_buffer_, action_buffer_); + } catch (const std::exception& exception) { + error = exception.what(); + return false; + } + if (!std::all_of(action_buffer_.begin(), action_buffer_.end(), [](float value) { + return std::isfinite(value); + })) { + error = "policy output contains non-finite values"; + return false; + } + for (std::size_t i = 0; i < action.size(); ++i) { + const double value = action_buffer_[i]; + action[i] = action_clip_ ? std::clamp(value, -*action_clip_, *action_clip_) : value; + } + return true; +} + +} // namespace rmcs_rl diff --git a/src/policy/policy_model.hpp b/src/policy/policy_model.hpp new file mode 100644 index 0000000..e12ccf7 --- /dev/null +++ b/src/policy/policy_model.hpp @@ -0,0 +1,54 @@ +#pragma once + +#include +#include +#include +#include +#include +#include + +#include "onnx_runtime.hpp" + +namespace rmcs_rl { + +class PolicyModel { +public: + struct Config { + std::string path; + std::string input_name = "obs"; + std::string output_name = "actions"; + bool normalization_from_metadata = true; + std::optional obs_clip; + std::optional action_clip; + }; + + struct Info { + std::string path; + std::string obs_signature; + std::string actions_signature; + std::string version; + std::size_t obs_size = 0; + std::size_t action_size = 0; + std::uint64_t layout_hash = 0; + std::uint64_t model_id = 0; + }; + + explicit PolicyModel(const Config& config); + + [[nodiscard]] const Info& info() const { return info_; } + bool run(std::span observation, std::span action, std::string& error); + +private: + void load_normalization(const Config& config); + + OnnxRuntime runtime_; + Info info_; + std::vector obs_mean_; + std::vector obs_std_; + std::optional obs_clip_; + std::optional action_clip_; + std::vector obs_buffer_; + std::vector action_buffer_; +}; + +} // namespace rmcs_rl diff --git a/src/policy_server.cpp b/src/policy_server.cpp index 4c6e872..6039c40 100644 --- a/src/policy_server.cpp +++ b/src/policy_server.cpp @@ -1,88 +1,27 @@ - #include #include #include -#include #include #include #include #include -#include #include -#include #include #include +#include #include #include -#include -#include -#include -#include #include -#include #include #include #include - -#include +#include #include -namespace rmcs_rl { - -namespace { - -std::vector parse_float_list(const std::string& text, const char* what) { - std::vector values; - std::size_t begin = 0; - while (begin <= text.size()) { - const auto end = text.find_first_of(", \t", begin); - const auto piece = - text.substr(begin, end == std::string::npos ? std::string::npos : end - begin); - if (!piece.empty()) { - try { - std::size_t consumed = 0; - const double value = std::stod(piece, &consumed); - if (consumed != piece.size()) - throw std::invalid_argument("trailing"); - values.push_back(value); - } catch (const std::exception&) { - throw std::invalid_argument( - std::string{"policy_server: metadata "} + what + " has a non-number '" + piece - + "'"); - } - } - if (end == std::string::npos) - break; - begin = end + 1; - } - return values; -} +#include "policy/policy_model.hpp" -std::optional parse_float(const std::string& text) { - try { - std::size_t consumed = 0; - const double value = std::stod(text, &consumed); - if (consumed != text.size()) - return std::nullopt; - return value; - } catch (const std::exception&) { - return std::nullopt; - } -} - -double parse_clip_metadata(const std::string& text, const char* key) { - const auto value = parse_float(text); - if (!value.has_value()) - throw std::runtime_error( - std::string{"policy_server: metadata "} + key + "=" + text + " is not a float"); - if (!std::isfinite(*value) || *value <= 0.0) - throw std::runtime_error( - std::string{"policy_server: metadata "} + key + " must be finite and > 0, got " + text); - return *value; -} - -} // namespace +namespace rmcs_rl { class PolicyServer final : public rclcpp::Node { public: @@ -90,282 +29,87 @@ class PolicyServer final : public rclcpp::Node { : Node( "policy_server", rclcpp::NodeOptions{}.automatically_declare_parameters_from_overrides(true)) { - - rl_base_ = string_or_("rl_base", "/rl"); - - const std::string model_path = string_or_("rl_model_path", ""); - if (model_path.empty()) + const auto rl_base = string_or(*this, "rl_base", "/rl"); + PolicyModel::Config config; + config.path = string_or(*this, "rl_model_path", ""); + if (config.path.empty()) throw std::invalid_argument("policy_server: parameter 'rl_model_path' is required"); - resolved_model_path_ = resolve_model_path_(model_path); - - std::string load_error; - OnnxRuntimeInference::Config inference_config; - inference_config.model_path = resolved_model_path_; - inference_config.input_name = string_or_("input_name", "obs"); - inference_config.output_name = string_or_("output_name", "actions"); - if (!inference_.load(inference_config, load_error)) - throw std::runtime_error( - "policy_server: cannot load '" + resolved_model_path_ + "': " + load_error); - - obs_size_ = inference_.input_size(); - action_size_ = inference_.output_size(); - if (obs_size_ == 0 || action_size_ == 0) - throw std::runtime_error("policy_server: model has zero-sized obs/action tensor"); - - std::string model_id_error; - if (!model_id_of_file(resolved_model_path_, model_id_, model_id_error)) - throw std::runtime_error("policy_server: " + model_id_error); - - const auto obs_layout = inference_.metadata("rmcs_obs_layout"); - const auto actions_layout = inference_.metadata("rmcs_actions_layout"); - if (!obs_layout || obs_layout->empty() || !actions_layout || actions_layout->empty()) - throw std::runtime_error( - "policy_server: model '" + resolved_model_path_ - + "' is missing metadata 'rmcs_obs_layout' / 'rmcs_actions_layout'; stamp it with " - "tool/stamp_layout_metadata.py before deploying (see " - "planning/docs/bridge-design.md §6)"); - obs_signature_ = *obs_layout; - actions_signature_ = *actions_layout; - policy_version_ = inference_.metadata("policy_version").value_or(""); - layout_hash_ = - rmcs_rl::layout_hash(obs_signature_, actions_signature_, obs_size_, action_size_); - - if (const auto declared = inference_.metadata("policy_layout_hash"); - declared && !declared->empty()) { - std::uint64_t declared_hash = 0; - try { - declared_hash = std::stoull(*declared, nullptr, 16); - } catch (const std::exception&) { - throw std::runtime_error( - "policy_server: metadata 'policy_layout_hash' is not a " - "hex string: '" - + *declared + "'"); - } - if (declared_hash != layout_hash_) - throw std::runtime_error( - "policy_server: metadata 'policy_layout_hash'=" + *declared - + " does not match the hash computed from the layout metadata (" - + hex16(layout_hash_) + "); re-stamp the model"); - } - - load_normalization_(); - - action_publisher_ = create_publisher( - rl_base_ + "/action", rclcpp::QoS{rclcpp::KeepLast(1)}.best_effort()); - observation_subscription_ = create_subscription( - rl_base_ + "/obs", rclcpp::QoS{rclcpp::KeepLast(1)}.best_effort(), - [this](rmcs_rl::msg::Observation::UniquePtr message) { - on_observation_(std::move(message)); - }); - - if (bool_or_("publish_status", false)) { - status_publisher_ = create_publisher( - rl_base_ + "/policy_status", + if (config.path.front() != '/') + config.path = + ament_index_cpp::get_package_share_directory("rmcs_rl") + "/" + config.path; + config.input_name = string_or(*this, "input_name", "obs"); + config.output_name = string_or(*this, "output_name", "actions"); + config.normalization_from_metadata = bool_or(*this, "normalization_from_metadata", true); + if (const double clip = number_or(*this, "obs_clip", -1.0); clip >= 0.0) + config.obs_clip = clip; + if (const double clip = number_or(*this, "action_clip", -1.0); clip >= 0.0) + config.action_clip = clip; + model_ = std::make_unique(config); + + action_publisher_ = create_publisher( + rl_base + "/action", rclcpp::QoS{rclcpp::KeepLast(1)}.best_effort()); + observation_subscription_ = create_subscription( + rl_base + "/obs", rclcpp::QoS{rclcpp::KeepLast(1)}.best_effort(), + [this](msg::Observation::UniquePtr message) { on_observation(std::move(message)); }); + if (bool_or(*this, "publish_status", false)) { + status_publisher_ = create_publisher( + rl_base + "/policy_status", rclcpp::QoS{rclcpp::KeepLast(1)}.transient_local().best_effort()); - const double rate = std::max(number_or_("status_rate", 2.0), 0.1); + const double rate = std::max(number_or(*this, "status_rate", 2.0), 0.1); status_timer_ = create_wall_timer( - std::chrono::duration(1.0 / rate), [this]() { publish_status_(); }); + std::chrono::duration(1.0 / rate), [this]() { publish_status(); }); } - RCLCPP_INFO(get_logger(), "policy loaded: %s", resolved_model_path_.c_str()); - RCLCPP_INFO(get_logger(), " model_id : %s", hex16(model_id_).c_str()); + const auto& info = model_->info(); + RCLCPP_INFO(get_logger(), "policy loaded: %s", info.path.c_str()); RCLCPP_INFO( - get_logger(), " policy_version: %s", - policy_version_.empty() ? "(none)" : policy_version_.c_str()); - RCLCPP_INFO(get_logger(), " obs_size=%zu action_size=%zu", obs_size_, action_size_); - RCLCPP_INFO(get_logger(), " obs signature : %s", obs_signature_.c_str()); - RCLCPP_INFO(get_logger(), " action signature : %s", actions_signature_.c_str()); - RCLCPP_INFO( - get_logger(), " layout_hash : %s (bridge must log the same value)", - hex16(layout_hash_).c_str()); - if (!obs_mean_.empty()) - RCLCPP_INFO( - get_logger(), " normalization : mean/std from metadata, obs_clip=%s", - obs_clip_.has_value() ? std::to_string(*obs_clip_).c_str() : "(none)"); - RCLCPP_INFO(get_logger(), "waiting for obs on %s/obs", rl_base_.c_str()); + get_logger(), "model_id=%s layout_hash=%s version=%s obs=%zu action=%zu", + hex16(info.model_id).c_str(), hex16(info.layout_hash).c_str(), info.version.c_str(), + info.obs_size, info.action_size); + RCLCPP_INFO(get_logger(), "obs signature: %s", info.obs_signature.c_str()); + RCLCPP_INFO(get_logger(), "action signature: %s", info.actions_signature.c_str()); + RCLCPP_INFO(get_logger(), "waiting for obs on %s/obs", rl_base.c_str()); } private: - std::string string_or_(const std::string& name, const std::string& fallback) const { - rclcpp::Parameter parameter; - try { - if (!get_parameter(name, parameter)) - return fallback; - } catch (const std::exception&) { - return fallback; - } - if (parameter.get_type() != rclcpp::ParameterType::PARAMETER_STRING) - return fallback; - return parameter.as_string(); - } - - double number_or_(const std::string& name, double fallback) const { - rclcpp::Parameter parameter; - try { - if (!get_parameter(name, parameter)) - return fallback; - } catch (const std::exception&) { - return fallback; - } - if (parameter.get_type() == rclcpp::ParameterType::PARAMETER_DOUBLE) - return parameter.as_double(); - if (parameter.get_type() == rclcpp::ParameterType::PARAMETER_INTEGER) - return static_cast(parameter.as_int()); - return fallback; - } - - bool bool_or_(const std::string& name, bool fallback) const { - rclcpp::Parameter parameter; - try { - if (!get_parameter(name, parameter)) - return fallback; - } catch (const std::exception&) { - return fallback; - } - if (parameter.get_type() != rclcpp::ParameterType::PARAMETER_BOOL) - return fallback; - return parameter.as_bool(); - } - - static std::string resolve_model_path_(const std::string& path) { - if (path.empty() || path.front() == '/') - return path; - try { - return ament_index_cpp::get_package_share_directory("rmcs_rl") + "/" + path; - } catch (const std::exception&) { - return path; - } - } - - void load_normalization_() { - const bool from_metadata = bool_or_("normalization_from_metadata", true); - if (from_metadata) { - if (const auto value = inference_.metadata("rmcs_obs_mean"); value && !value->empty()) - obs_mean_ = parse_float_list(*value, "rmcs_obs_mean"); - if (const auto value = inference_.metadata("rmcs_obs_std"); value && !value->empty()) - obs_std_ = parse_float_list(*value, "rmcs_obs_std"); - if (!obs_mean_.empty() && obs_mean_.size() != obs_size_) - throw std::runtime_error( - "policy_server: metadata rmcs_obs_mean has " + std::to_string(obs_mean_.size()) - + " values, expected " + std::to_string(obs_size_)); - if (!obs_std_.empty() && obs_std_.size() != obs_size_) - throw std::runtime_error( - "policy_server: metadata rmcs_obs_std has " + std::to_string(obs_std_.size()) - + " values, expected " + std::to_string(obs_size_)); - if (!obs_mean_.empty() && !obs_std_.empty()) { - for (const double sigma : obs_std_) - if (!(sigma > 0.0) || !std::isfinite(sigma)) - throw std::runtime_error( - "policy_server: metadata rmcs_obs_std must be " - "finite and > 0"); - } else { - obs_mean_.clear(); - obs_std_.clear(); - } - if (const auto value = inference_.metadata("rmcs_obs_clip"); value && !value->empty()) - obs_clip_ = parse_clip_metadata(*value, "rmcs_obs_clip"); - if (const auto value = inference_.metadata("rmcs_action_clip"); - value && !value->empty()) - action_clip_ = parse_clip_metadata(*value, "rmcs_action_clip"); - } - - const double obs_clip_param = number_or_("obs_clip", -1.0); - if (obs_clip_param >= 0.0) - obs_clip_ = obs_clip_param; - const double action_clip_param = number_or_("action_clip", -1.0); - if (action_clip_param >= 0.0) - action_clip_ = action_clip_param; - - obs_buffer_.assign(obs_size_, 0.0F); - action_buffer_.assign(action_size_, 0.0F); - } - - void on_observation_(rmcs_rl::msg::Observation::UniquePtr message) { - if (message->layout_hash != layout_hash_) { + void on_observation(msg::Observation::UniquePtr message) { + const auto& info = model_->info(); + if (message->layout_hash != info.layout_hash) { if (!layout_mismatch_logged_) { layout_mismatch_logged_ = true; - RCLCPP_FATAL( - get_logger(), - "layout_hash mismatch: bridge sent %s but this model expects %s " - "(model '%s'); refusing to answer (bridge will report valid=0). " - "Check that the deployment YAML and the model metadata describe the same " - "observation/action terms.", - hex16(message->layout_hash).c_str(), hex16(layout_hash_).c_str(), - resolved_model_path_.c_str()); + RCLCPP_ERROR( + get_logger(), "layout_hash mismatch: bridge=%s model=%s; refusing actions", + hex16(message->layout_hash).c_str(), hex16(info.layout_hash).c_str()); } - ++rejected_count_; - return; - } - if (message->obs.size() != obs_size_) { - RCLCPP_ERROR_THROTTLE( - get_logger(), *get_clock(), 1000, "obs has %zu values, model expects %zu; ignoring", - message->obs.size(), obs_size_); - ++rejected_count_; return; } const auto started = std::chrono::steady_clock::now(); - - for (std::size_t i = 0; i < obs_size_; ++i) { - double value = message->obs[i]; - if (!obs_mean_.empty()) - value = (value - obs_mean_[i]) / obs_std_[i]; - if (obs_clip_.has_value()) - value = std::clamp(value, -*obs_clip_, *obs_clip_); - if (!std::isfinite(value)) { - RCLCPP_WARN_THROTTLE( - get_logger(), *get_clock(), 1000, "obs[%zu] is not finite; ignoring frame", i); - ++rejected_count_; - return; - } - obs_buffer_[i] = static_cast(value); - } - - if (!inference_.run(obs_buffer_, action_buffer_)) { - RCLCPP_ERROR_THROTTLE( - get_logger(), *get_clock(), 1000, "ONNX Runtime rejected the obs frame; ignoring"); - ++rejected_count_; - return; - } - - if (!std::all_of(action_buffer_.begin(), action_buffer_.end(), [](float value) { - return std::isfinite(value); - })) { + msg::Action action; + action.action.resize(info.action_size); + std::string error; + if (!model_->run(message->obs, action.action, error)) { RCLCPP_WARN_THROTTLE( - get_logger(), *get_clock(), 1000, - "policy output contains non-finite values; ignoring frame " - "(bridge will see a stale action and drop authority)"); - ++rejected_count_; + get_logger(), *get_clock(), 1000, "policy rejected observation: %s", error.c_str()); return; } - - rmcs_rl::msg::Action action; action.header.stamp = get_clock()->now(); action.obs_seq = message->obs_seq; - action.layout_hash = layout_hash_; - action.model_id = model_id_; - action.action.resize(action_size_); - for (std::size_t i = 0; i < action_size_; ++i) { - double value = static_cast(action_buffer_[i]); - if (action_clip_.has_value()) - value = std::clamp(value, -*action_clip_, *action_clip_); - action.action[i] = value; - } + action.layout_hash = info.layout_hash; + action.model_id = info.model_id; action_publisher_->publish(action); - const auto elapsed = std::chrono::duration(std::chrono::steady_clock::now() - started); - record_inference_time_(elapsed.count()); - ++served_count_; + record_inference_time(elapsed.count()); } - void record_inference_time_(double microseconds) { + void record_inference_time(double microseconds) { inference_window_[inference_window_cursor_] = microseconds; inference_window_cursor_ = (inference_window_cursor_ + 1) % inference_window_.size(); inference_window_count_ = std::min(inference_window_count_ + 1, inference_window_.size()); } - double percentile_(double fraction) const { + double percentile(double fraction) const { if (inference_window_count_ == 0) return 0.0; std::vector samples( @@ -376,53 +120,30 @@ class PolicyServer final : public rclcpp::Node { return samples[std::min(index, samples.size() - 1)]; } - void publish_status_() { - if (!status_publisher_) - return; - rmcs_rl::msg::PolicyStatus status; + void publish_status() { + const auto& info = model_->info(); + msg::PolicyStatus status; status.header.stamp = get_clock()->now(); - status.model_name = resolved_model_path_; - status.model_id = model_id_; - status.policy_version = policy_version_; - status.layout_hash = layout_hash_; - status.obs_size = static_cast(obs_size_); - status.action_size = static_cast(action_size_); - status.inference_p50_us = percentile_(0.50); - status.inference_p99_us = percentile_(0.99); + status.model_name = info.path; + status.model_id = info.model_id; + status.policy_version = info.version; + status.layout_hash = info.layout_hash; + status.obs_size = static_cast(info.obs_size); + status.action_size = static_cast(info.action_size); + status.inference_p50_us = percentile(0.50); + status.inference_p99_us = percentile(0.99); status_publisher_->publish(status); } - std::string rl_base_; - std::string resolved_model_path_; - std::string obs_signature_; - std::string actions_signature_; - std::string policy_version_; - std::size_t obs_size_ = 0; - std::size_t action_size_ = 0; - std::uint64_t layout_hash_ = 0; - std::uint64_t model_id_ = 0; - - std::vector obs_mean_; - std::vector obs_std_; - std::optional obs_clip_; - std::optional action_clip_; - - std::vector obs_buffer_; - std::vector action_buffer_; - - std::uint64_t served_count_ = 0; - std::uint64_t rejected_count_ = 0; + rclcpp::Publisher::SharedPtr action_publisher_; + rclcpp::Subscription::SharedPtr observation_subscription_; + rclcpp::Publisher::SharedPtr status_publisher_; + rclcpp::TimerBase::SharedPtr status_timer_; + std::unique_ptr model_; bool layout_mismatch_logged_ = false; - std::array inference_window_{}; std::size_t inference_window_cursor_ = 0; std::size_t inference_window_count_ = 0; - - OnnxRuntimeInference inference_; - rclcpp::Publisher::SharedPtr action_publisher_; - rclcpp::Subscription::SharedPtr observation_subscription_; - rclcpp::Publisher::SharedPtr status_publisher_; - rclcpp::TimerBase::SharedPtr status_timer_; }; } // namespace rmcs_rl diff --git a/src/policy_server_launcher.cpp b/src/policy_server_launcher.cpp index baf4677..c82f0ec 100644 --- a/src/policy_server_launcher.cpp +++ b/src/policy_server_launcher.cpp @@ -17,13 +17,10 @@ #include #include #include +#include namespace rmcs_rl { -// Spawns and supervises an independent policy_server child process for the executor lifetime: -// - the component only exists in RL configs; non-RL robots are unaffected; -// - the child sets PR_SET_PDEATHSIG so the kernel reaps it when executor exits/crashes; -// - update() does a low-frequency waitpid(WNOHANG) poll with optional backoff restart. class PolicyServerLauncher : public rmcs_executor::Component , public rclcpp::Node { @@ -32,11 +29,11 @@ class PolicyServerLauncher : Node( get_component_name(), rclcpp::NodeOptions{}.automatically_declare_parameters_from_overrides(true)) { - autostart_ = bool_or_("autostart", true); - respawn_ = bool_or_("respawn", true); - respawn_delay_ = number_or_("respawn_delay", 1.0); - poll_interval_ = number_or_("poll_interval", 0.5); - params_file_ = string_or_("params_file", ""); + autostart_ = bool_or(*this, "autostart", true); + respawn_ = bool_or(*this, "respawn", true); + respawn_delay_ = number_or(*this, "respawn_delay", 1.0); + poll_interval_ = number_or(*this, "poll_interval", 0.5); + params_file_ = string_or(*this, "params_file", ""); resolve_paths_(); } @@ -63,35 +60,6 @@ class PolicyServerLauncher private: using SteadyClock = std::chrono::steady_clock; - std::string string_or_(const std::string& name, const std::string& fallback) const { - if (!has_parameter(name)) - return fallback; - const auto parameter = get_parameter(name); - if (parameter.get_type() != rclcpp::ParameterType::PARAMETER_STRING) - return fallback; - return parameter.as_string(); - } - - double number_or_(const std::string& name, double fallback) const { - if (!has_parameter(name)) - return fallback; - const auto parameter = get_parameter(name); - if (parameter.get_type() == rclcpp::ParameterType::PARAMETER_DOUBLE) - return parameter.as_double(); - if (parameter.get_type() == rclcpp::ParameterType::PARAMETER_INTEGER) - return static_cast(parameter.as_int()); - return fallback; - } - - bool bool_or_(const std::string& name, bool fallback) const { - if (!has_parameter(name)) - return fallback; - const auto parameter = get_parameter(name); - if (parameter.get_type() != rclcpp::ParameterType::PARAMETER_BOOL) - return fallback; - return parameter.as_bool(); - } - void resolve_paths_() { try { const auto share = ament_index_cpp::get_package_share_directory("rmcs_rl"); @@ -229,7 +197,8 @@ class PolicyServerLauncher ::kill(pid, SIGKILL); ::waitpid(pid, nullptr, 0); - RCLCPP_WARN(get_logger(), "policy_server (pid=%d) did not stop, killed", static_cast(pid)); + RCLCPP_WARN( + get_logger(), "policy_server (pid=%d) did not stop, killed", static_cast(pid)); } bool autostart_ = true; diff --git a/src/rl_bridge.cpp b/src/rl_bridge.cpp index 1c0336f..e175f76 100644 --- a/src/rl_bridge.cpp +++ b/src/rl_bridge.cpp @@ -3,10 +3,8 @@ #include #include #include -#include #include #include -#include #include #include #include @@ -24,11 +22,12 @@ #include #include +#include #include #include #include -#include -#include +#include +#include #include #include #include @@ -42,21 +41,30 @@ class RlBridge final explicit RlBridge() : Node( get_component_name(), - rclcpp::NodeOptions{}.automatically_declare_parameters_from_overrides(true)) { + rclcpp::NodeOptions{}.automatically_declare_parameters_from_overrides(true)) + , config_(load_bridge_config(*this)) + , history_(config_.obs_frame_size, config_.history_length) { - rl_base_ = string_or(*this, "rl_base", "/rl"); - - joint_config_ = load_joint_config(*this); - - load_action_terms_(); - load_observation_terms_(); - load_runtime_parameters_(); - - register_status_outputs_(); + for (const auto& term : config_.action_terms) { + action_outputs_.push_back(std::make_unique>()); + register_output(term.output, *action_outputs_.back(), 0.0); + own_output_paths_.insert(term.output); + } + register_output(config_.rl_base + "/valid", valid_output_, 0.0); + register_output(config_.rl_base + "/healthy", healthy_output_, 0.0); + register_output( + config_.rl_base + "/action_age", action_age_output_, + std::numeric_limits::quiet_NaN()); + register_output(config_.rl_base + "/obs_seq", obs_seq_output_, std::size_t{0}); + own_output_paths_.insert(config_.rl_base + "/valid"); + own_output_paths_.insert(config_.rl_base + "/healthy"); + own_output_paths_.insert(config_.rl_base + "/action_age"); + own_output_paths_.insert(config_.rl_base + "/obs_seq"); setup_topics_(); - - action_channel_.resize(action_size_); - read_snapshot_.action.assign(action_size_, 0.0); + last_actions_.assign(config_.action_size, 0.0); + written_.assign(config_.action_size, 0.0); + action_channel_.resize(config_.action_size); + read_snapshot_.action.assign(config_.action_size, 0.0); } void before_pairing(const OutputInfoMap& output_map) override { @@ -69,15 +77,15 @@ class RlBridge final "RlBridge: interface \"" + slot.path + "\" is produced by RlBridge itself (self reference)"); - obs_signature_ = obs_layout_signature(obs_terms_, history_length_); - actions_signature_ = actions_layout_signature(action_terms_); - layout_hash_ = - rmcs_rl::layout_hash(obs_signature_, actions_signature_, obs_size_, action_size_); + obs_signature_ = obs_layout_signature(config_.obs_terms, config_.history_length); + actions_signature_ = actions_layout_signature(config_.action_terms); + layout_hash_ = rmcs_rl::layout_hash( + obs_signature_, actions_signature_, config_.obs_size, config_.action_size); log_layout_(); RCLCPP_INFO( - get_logger(), "contract: obs_size=%zu action_size=%zu policy_rate=%.3f Hz", obs_size_, - action_size_, policy_rate_); + get_logger(), "contract: obs_size=%zu action_size=%zu policy_rate=%.3f Hz", + config_.obs_size, config_.action_size, config_.policy_rate); RCLCPP_INFO( get_logger(), "layout_hash=%s (obs/action signatures below)", hex16(layout_hash_).c_str()); @@ -85,7 +93,7 @@ class RlBridge final RCLCPP_INFO(get_logger(), " action signature : %s", actions_signature_.c_str()); RCLCPP_INFO( get_logger(), "topics: %s/obs -> %s/action (best_effort, keep_last=1)", - rl_base_.c_str(), rl_base_.c_str()); + config_.rl_base.c_str(), config_.rl_base.c_str()); } void update() override { @@ -101,8 +109,8 @@ class RlBridge final bool seq_ok = false; bool finite = true; if (has_snapshot) { - age = obs_age_of(snapshot.obs_seq, now); - seq_ok = (snapshot.obs_seq == pub_seq_) || (snapshot.obs_seq + 1 == pub_seq_); + age = timeline_.age(snapshot.obs_seq, now); + seq_ok = std::isfinite(age); finite = std::all_of(snapshot.action.begin(), snapshot.action.end(), [](double value) { return std::isfinite(value); }); @@ -110,10 +118,11 @@ class RlBridge final } const bool enabled = read_enable_(); - const bool fresh = has_snapshot && is_finite(age) && age <= max_action_age_; + const bool fresh = has_snapshot && is_finite(age) && age <= config_.max_action_age; const bool valid = enabled && contract_ok_ && has_snapshot && fresh && seq_ok && finite; - write_actions(valid, snapshot, action_terms_, invalid_mode_, written_, action_outputs_); + write_actions( + valid, snapshot, config_.action_terms, config_.invalid_mode, written_, action_outputs_); if (valid) last_actions_ = snapshot.action; @@ -121,7 +130,7 @@ class RlBridge final *valid_output_ = valid ? 1.0 : 0.0; *healthy_output_ = (contract_ok_ && fresh) ? 1.0 : 0.0; *action_age_output_ = age; - *obs_seq_output_ = pub_seq_; + *obs_seq_output_ = timeline_.sequence(); if (valid != last_valid_) { if (valid) { @@ -140,130 +149,16 @@ class RlBridge final } private: - void load_action_terms_() { - const auto action_specs = string_array_or(*this, "action_terms"); - if (action_specs.empty()) - throw std::invalid_argument("RlBridge: required parameter 'action_terms' is missing"); - std::unordered_set output_paths; - std::set action_indices; - for (const auto& spec : action_specs) { - auto term = parse_action_term(spec); - if (!output_paths.emplace(term.output).second) - throw std::invalid_argument( - "RlBridge: two action terms map to the same output " - "interface '" - + term.output + "'"); - if (!action_indices.emplace(term.index).second) - throw std::invalid_argument( - "RlBridge: duplicate action index " + std::to_string(term.index) - + " (each slot must appear exactly once)"); - action_terms_.push_back(std::move(term)); - } - for (std::size_t i = 0; i < action_terms_.size(); ++i) - if (action_terms_[i].index != i) - throw std::invalid_argument( - "RlBridge: action indices must form the complete " - "permutation 0.." - + std::to_string(action_terms_.size() - 1) + "; got index=" - + std::to_string(action_terms_[i].index) + " at position " + std::to_string(i)); - action_size_ = action_terms_.size(); - if (const auto declared = integer_parameter(*this, "rl_action_size"); - declared.has_value() && static_cast(*declared) != action_size_) - throw std::invalid_argument( - "RlBridge: rl_action_size=" + std::to_string(*declared) + " but action_terms has " - + std::to_string(action_size_) + " entries"); - last_actions_.assign(action_size_, 0.0); - written_.assign(action_size_, 0.0); - - for (const auto& term : action_terms_) { - action_outputs_.push_back(std::make_unique>()); - register_output(term.output, *action_outputs_.back(), 0.0); - own_output_paths_.insert(term.output); - } - } - - void load_observation_terms_() { - const auto observation_specs = string_array_or(*this, "observation_terms"); - if (observation_specs.empty()) - throw std::invalid_argument( - "RlBridge: required parameter 'observation_terms' is " - "missing"); - const TermParseContext context{*this, joint_config_, action_size_}; - for (const auto& spec : observation_specs) - obs_terms_.push_back(parse_obs_term(spec, context)); - - assign_observation_indices(obs_terms_); - obs_frame_size_ = [&] { - std::size_t cursor = 0; - for (const auto& term : obs_terms_) - cursor += term.dim; - return cursor; - }(); - const auto history_length = integer_parameter(*this, "history_length").value_or(1); - if (history_length < 1 || history_length > 64) - throw std::invalid_argument("RlBridge: history_length must be in [1, 64]"); - history_length_ = static_cast(history_length); - obs_size_ = obs_frame_size_ * history_length_; - if (const auto declared = integer_parameter(*this, "rl_obs_size"); - declared.has_value() && static_cast(*declared) != obs_size_) - throw std::invalid_argument( - "RlBridge: rl_obs_size=" + std::to_string(*declared) - + " but observation frame/history contract is " + std::to_string(obs_frame_size_) - + "x" + std::to_string(history_length_) + "=" + std::to_string(obs_size_)); - } - - void load_runtime_parameters_() { - policy_rate_ = number_or(*this, "policy_rate", 50.0); - if (!(policy_rate_ > 0.0) || !is_finite(policy_rate_)) - throw std::invalid_argument("RlBridge: policy_rate must be finite and > 0"); - pub_period_ = std::chrono::duration_cast( - std::chrono::duration(1.0 / policy_rate_)); - max_action_age_ = number_or(*this, "max_action_age", 2.0 / policy_rate_); - if (!(max_action_age_ > 0.0) || !is_finite(max_action_age_)) - throw std::invalid_argument("RlBridge: max_action_age must be finite and > 0"); - expected_model_id_ = parse_u64(string_or(*this, "expected_model_id", "0"), "expected_model_id"); - - const std::string invalid = string_or(*this, "invalid_value", "nan"); - if (invalid == "nan") - invalid_mode_ = InvalidMode::kNaN; - else if (invalid == "zero") - invalid_mode_ = InvalidMode::kZero; - else if (invalid == "hold") - invalid_mode_ = InvalidMode::kHold; - else - throw std::invalid_argument( - "RlBridge: invalid_value must be nan|zero|hold " - "(quote it in YAML: invalid_value: \"nan\" — an unquoted " - "nan is parsed as a float), got '" - + string_or(*this, "invalid_value", "") + "'"); - - enable_path_ = string_or(*this, "enable_interface", rl_base_ + "/enable"); - enable_default_ = bool_or(*this, "enable_default", false); - reset_path_ = string_or(*this, "reset_interface", ""); - } - - void register_status_outputs_() { - register_output(rl_base_ + "/valid", valid_output_, 0.0); - register_output(rl_base_ + "/healthy", healthy_output_, 0.0); - register_output( - rl_base_ + "/action_age", action_age_output_, std::numeric_limits::quiet_NaN()); - register_output(rl_base_ + "/obs_seq", obs_seq_output_, std::size_t{0}); - own_output_paths_.insert(rl_base_ + "/valid"); - own_output_paths_.insert(rl_base_ + "/healthy"); - own_output_paths_.insert(rl_base_ + "/action_age"); - own_output_paths_.insert(rl_base_ + "/obs_seq"); - } - void setup_topics_() { obs_publisher_ = create_publisher( - rl_base_ + "/obs", rclcpp::QoS{rclcpp::KeepLast(1)}.best_effort()); + config_.rl_base + "/obs", rclcpp::QoS{rclcpp::KeepLast(1)}.best_effort()); action_subscription_ = create_subscription( - rl_base_ + "/action", rclcpp::QoS{rclcpp::KeepLast(1)}.best_effort(), + config_.rl_base + "/action", rclcpp::QoS{rclcpp::KeepLast(1)}.best_effort(), [this](rmcs_rl::msg::Action::UniquePtr message) { on_action_(std::move(message)); }); } void bind_observation_slots_(const OutputInfoMap& output_map) { - for (auto& term : obs_terms_) { + for (auto& term : config_.obs_terms) { switch (term.kind) { case TermKind::kConstant: case TermKind::kLastAction: break; @@ -271,11 +166,11 @@ class RlBridge final case TermKind::kJointVel: case TermKind::kJointTorque: { for (std::size_t j = 0; j < term.joints.size(); ++j) { - const auto& joint = joint_config_.names[term.joints[j]]; + const auto& joint = config_.joint_config.names[term.joints[j]]; const char field = term.kind == TermKind::kJointPos ? 'a' : term.kind == TermKind::kJointVel ? 'v' : 't'; - const auto path = joint_path(joint_config_, joint, field); + const auto path = joint_path(config_.joint_config, joint, field); term.joint_slots.push_back(acquire_slot( *this, path, {Binding::kDouble}, true, output_map, slots_, "joint term")); } @@ -289,10 +184,7 @@ class RlBridge final switch (term.take) { case Take::kScalar: candidates = { - Binding::kDouble, - Binding::kBool, - Binding::kInt, - Binding::kSize}; + Binding::kDouble, Binding::kBool, Binding::kInt, Binding::kSize}; break; case Take::kComponent: case Take::kVector: @@ -311,14 +203,14 @@ class RlBridge final } void bind_control_slots_(const OutputInfoMap& output_map) { - if (!enable_path_.empty()) + if (!config_.enable_path.empty()) enable_slot_ = acquire_slot( - *this, enable_path_, {Binding::kBool, Binding::kDouble}, false, output_map, slots_, - "enable interface"); + *this, config_.enable_path, {Binding::kBool, Binding::kDouble}, false, output_map, + slots_, "enable interface"); - if (!reset_path_.empty()) + if (!config_.reset_path.empty()) reset_slot_ = acquire_slot( - *this, reset_path_, {Binding::kSize, Binding::kInt, Binding::kDouble}, false, + *this, config_.reset_path, {Binding::kSize, Binding::kInt, Binding::kDouble}, false, output_map, slots_, "reset interface"); } @@ -333,23 +225,13 @@ class RlBridge final } void maybe_publish_observation_(std::chrono::steady_clock::time_point now) { - if (pub_started_ && now - last_pub_time_ < pub_period_) + if (!timeline_.due(now, config_.pub_period)) return; std::vector obs; - if (build_observation(obs_terms_, slots_, last_actions_, obs_size_, obs)) { - if (history_.empty()) - history_.assign(history_length_, obs); - else { - history_.pop_front(); - history_.push_back(obs); - } - std::vector stacked; - stacked.reserve(obs_size_); - for (const auto& frame : history_) - stacked.insert(stacked.end(), frame.begin(), frame.end()); - publish_observation_(stacked, now); - ++pub_ok_count_; + if (build_observation( + config_.obs_terms, slots_, last_actions_, config_.obs_frame_size, obs)) { + publish_observation_(history_.append(obs), now); } else { ++obs_invalid_count_; RCLCPP_WARN_THROTTLE( @@ -362,11 +244,11 @@ class RlBridge final bool read_enable_() const { if (enable_slot_ == kNoSlot) - return enable_default_; + return config_.enable_default; double raw = 0.0; if (!read_double(slots_[enable_slot_], raw)) - return enable_default_; - return raw != 0.0; + return config_.enable_default; + return std::isfinite(raw) && raw != 0.0; } void check_contract_(const ActionSnapshot& snapshot) { @@ -379,19 +261,20 @@ class RlBridge final "(policy process and bridge disagree; refusing to output actions)", hex16(snapshot.layout_hash).c_str(), hex16(layout_hash_).c_str()); } - } else if (expected_model_id_ != 0 && snapshot.model_id != expected_model_id_) { + } else if ( + config_.expected_model_id != 0 && snapshot.model_id != config_.expected_model_id) { if (contract_ok_) { contract_ok_ = false; RCLCPP_FATAL( get_logger(), "model mismatch: action model_id=%s != expected_model_id=%s", - hex16(snapshot.model_id).c_str(), hex16(expected_model_id_).c_str()); + hex16(snapshot.model_id).c_str(), hex16(config_.expected_model_id).c_str()); } } } void log_layout_() const { - RCLCPP_INFO(get_logger(), "observation layout (obs_size=%zu):", obs_size_); - for (const auto& term : obs_terms_) { + RCLCPP_INFO(get_logger(), "observation layout (obs_size=%zu):", config_.obs_size); + for (const auto& term : config_.obs_terms) { std::ostringstream line; line << " [" << term.index << ":" << term.index + term.dim << ") " << term.id << " scale=" << format_number(term.scale); @@ -409,8 +292,8 @@ class RlBridge final } RCLCPP_INFO(get_logger(), "%s", line.str().c_str()); } - RCLCPP_INFO(get_logger(), "action layout (action_size=%zu):", action_size_); - for (const auto& term : action_terms_) { + RCLCPP_INFO(get_logger(), "action layout (action_size=%zu):", config_.action_size); + for (const auto& term : config_.action_terms) { std::ostringstream line; line << " #" << term.index << " " << term.id << " -> " << term.output; if (term.scale != 1.0) @@ -423,47 +306,28 @@ class RlBridge final const std::vector& obs, std::chrono::steady_clock::time_point now) { rmcs_rl::msg::Observation message; message.header.stamp = get_clock()->now(); - message.header.frame_id = ""; - message.obs_seq = ++pub_seq_; + message.obs_seq = timeline_.publish(now); message.layout_hash = layout_hash_; message.obs = obs; obs_publisher_->publish(message); - - prev_pub_seq_ = pub_seq_ - 1; - prev_pub_time_ = last_pub_time_; - last_pub_time_ = now; - pub_started_ = true; } void on_action_(rmcs_rl::msg::Action::UniquePtr message) { - if (message->action.size() != action_size_) { + if (message->action.size() != config_.action_size) { RCLCPP_ERROR_THROTTLE( get_logger(), *get_clock(), 1000, "ignoring action with %zu values (expected %zu)", - message->action.size(), action_size_); + message->action.size(), config_.action_size); return; } action_channel_.store(*message); } - double obs_age_of(std::uint64_t obs_seq, std::chrono::steady_clock::time_point now) const { - if (!pub_started_) - return std::numeric_limits::quiet_NaN(); - if (obs_seq == pub_seq_) - return std::chrono::duration(now - last_pub_time_).count(); - if (obs_seq + 1 == pub_seq_) - return std::chrono::duration(now - prev_pub_time_).count(); - return std::numeric_limits::quiet_NaN(); - } - void reset_runtime_() { reset_action_state(last_actions_, written_); - history_.clear(); - pub_started_ = false; - prev_pub_seq_ = 0; + history_.reset(); + timeline_.reset(); } - // Interface storage is kept before configuration and runtime state so the component wiring - // remains visible at the class boundary. std::vector slots_; std::vector>> action_outputs_; @@ -472,25 +336,9 @@ class RlBridge final OutputInterface action_age_output_{}; OutputInterface obs_seq_output_{}; - JointConfig joint_config_; - - std::vector obs_terms_; - std::vector action_terms_; + BridgeConfig config_; std::unordered_set own_output_paths_; - std::size_t obs_size_ = 0; - std::size_t obs_frame_size_ = 0; - std::size_t history_length_ = 1; - std::size_t action_size_ = 0; - - std::string rl_base_; - double policy_rate_ = 50.0; - double max_action_age_ = 0.04; - std::uint64_t expected_model_id_ = 0; - InvalidMode invalid_mode_ = InvalidMode::kNaN; - std::string enable_path_; - bool enable_default_ = false; - std::string reset_path_; std::size_t enable_slot_ = kNoSlot; std::size_t reset_slot_ = kNoSlot; @@ -500,17 +348,11 @@ class RlBridge final std::vector last_actions_; std::vector written_; - std::deque> history_; - - std::chrono::nanoseconds pub_period_{std::chrono::milliseconds(20)}; - std::chrono::steady_clock::time_point last_pub_time_{}; - std::chrono::steady_clock::time_point prev_pub_time_{}; - bool pub_started_ = false; - std::uint64_t pub_seq_ = 0; - std::uint64_t prev_pub_seq_ = 0; + ObservationHistory history_; + + ObservationTimeline timeline_; std::uint64_t last_reset_count_ = 0; std::uint64_t obs_invalid_count_ = 0; - std::uint64_t pub_ok_count_ = 0; bool contract_ok_ = true; bool last_valid_ = false; diff --git a/src/rl_bridge/action_channel.cpp b/src/rl_bridge/action_channel.cpp index 65484de..d2f7c00 100644 --- a/src/rl_bridge/action_channel.cpp +++ b/src/rl_bridge/action_channel.cpp @@ -2,9 +2,37 @@ #include #include +#include namespace rmcs_rl { +void ActionChannel::resize(std::size_t action_size) { + const std::lock_guard lock{mutex_}; + incoming_.action.assign(action_size, 0.0); + received_ = false; +} + +void ActionChannel::store(const rmcs_rl::msg::Action& message) { + const std::lock_guard lock{mutex_}; + if (message.action.size() != incoming_.action.size()) + throw std::invalid_argument("action channel size mismatch"); + incoming_.obs_seq = message.obs_seq; + incoming_.layout_hash = message.layout_hash; + incoming_.model_id = message.model_id; + std::copy(message.action.begin(), message.action.end(), incoming_.action.begin()); + received_ = true; +} + +bool ActionChannel::try_read(ActionSnapshot& snapshot) { + // The executor must never wait for the ROS callback. A seqlock cannot protect + // concurrent reads/writes of a non-atomic vector under the C++ memory model. + const std::unique_lock lock{mutex_, std::try_to_lock}; + if (!lock.owns_lock() || !received_) + return false; + snapshot = incoming_; + return true; +} + void write_actions( bool valid, const ActionSnapshot& snapshot, const std::vector& terms, InvalidMode invalid_mode, std::vector& written, @@ -19,9 +47,7 @@ void write_actions( written[i] = value; } else { switch (invalid_mode) { - case InvalidMode::kNaN: - value = std::numeric_limits::quiet_NaN(); - break; + case InvalidMode::kNaN: value = std::numeric_limits::quiet_NaN(); break; case InvalidMode::kZero: value = 0.0; break; case InvalidMode::kHold: value = written[i]; break; } @@ -38,7 +64,7 @@ void reset_action_state(std::vector& last_actions, std::vector& std::string invalid_reason( bool enabled, bool contract_ok, bool has_snapshot, bool fresh, bool seq_ok, bool finite) { if (!contract_ok) - return "contract/model mismatch (latched; restart or re-enable)"; + return "contract/model mismatch (latched; restart required)"; if (!enabled) return "disabled by enable interface"; if (!has_snapshot) diff --git a/src/rl_bridge/config.cpp b/src/rl_bridge/config.cpp new file mode 100644 index 0000000..ab9d6d4 --- /dev/null +++ b/src/rl_bridge/config.cpp @@ -0,0 +1,108 @@ +#include + +#include +#include +#include +#include + +#include +#include +#include + +namespace rmcs_rl { + +BridgeConfig load_bridge_config(rclcpp::Node& node) { + BridgeConfig config; + config.rl_base = string_or(node, "rl_base", "/rl"); + config.joint_config = load_joint_config(node); + const auto action_specs = string_array_or(node, "action_terms"); + if (action_specs.empty()) + throw std::invalid_argument("RlBridge: required parameter 'action_terms' is missing"); + std::unordered_set output_paths; + std::set action_indices; + for (const auto& spec : action_specs) { + auto term = parse_action_term(spec); + if (!output_paths.emplace(term.output).second) + throw std::invalid_argument( + "RlBridge: two action terms map to the same output " + "interface '" + + term.output + "'"); + if (!action_indices.emplace(term.index).second) + throw std::invalid_argument( + "RlBridge: duplicate action index " + std::to_string(term.index) + + " (each slot must appear exactly once)"); + config.action_terms.push_back(std::move(term)); + } + for (std::size_t i = 0; i < config.action_terms.size(); ++i) + if (config.action_terms[i].index != i) + throw std::invalid_argument( + "RlBridge: action indices must form the complete " + "permutation 0.." + + std::to_string(config.action_terms.size() - 1) + + "; got index=" + std::to_string(config.action_terms[i].index) + " at position " + + std::to_string(i)); + config.action_size = config.action_terms.size(); + if (const auto declared = integer_parameter(node, "rl_action_size"); + declared.has_value() && static_cast(*declared) != config.action_size) + throw std::invalid_argument( + "RlBridge: rl_action_size=" + std::to_string(*declared) + " but action_terms has " + + std::to_string(config.action_size) + " entries"); + const auto observation_specs = string_array_or(node, "observation_terms"); + if (observation_specs.empty()) + throw std::invalid_argument( + "RlBridge: required parameter 'observation_terms' is " + "missing"); + const TermParseContext context{node, config.joint_config, config.action_size}; + for (const auto& spec : observation_specs) + config.obs_terms.push_back(parse_obs_term(spec, context)); + + assign_observation_indices(config.obs_terms); + config.obs_frame_size = [&] { + std::size_t cursor = 0; + for (const auto& term : config.obs_terms) + cursor += term.dim; + return cursor; + }(); + const auto history_length = integer_parameter(node, "history_length").value_or(1); + if (history_length < 1 || history_length > 64) + throw std::invalid_argument("RlBridge: history_length must be in [1, 64]"); + config.history_length = static_cast(history_length); + config.obs_size = config.obs_frame_size * config.history_length; + if (const auto declared = integer_parameter(node, "rl_obs_size"); + declared.has_value() && static_cast(*declared) != config.obs_size) + throw std::invalid_argument( + "RlBridge: rl_obs_size=" + std::to_string(*declared) + + " but observation frame/history contract is " + std::to_string(config.obs_frame_size) + + "x" + std::to_string(config.history_length) + "=" + std::to_string(config.obs_size)); + config.policy_rate = number_or(node, "policy_rate", 50.0); + if (!(config.policy_rate > 0.0) || !is_finite(config.policy_rate)) + throw std::invalid_argument("RlBridge: policy_rate must be finite and > 0"); + config.pub_period = std::chrono::duration_cast( + std::chrono::duration(1.0 / config.policy_rate)); + config.max_action_age = number_or(node, "max_action_age", 2.0 / config.policy_rate); + if (!(config.max_action_age > 0.0) || !is_finite(config.max_action_age)) + throw std::invalid_argument("RlBridge: max_action_age must be finite and > 0"); + config.expected_model_id = + parse_u64(string_or(node, "expected_model_id", "0"), "expected_model_id"); + + const std::string invalid = string_or(node, "invalid_value", "nan"); + if (invalid == "nan") + config.invalid_mode = InvalidMode::kNaN; + else if (invalid == "zero") + config.invalid_mode = InvalidMode::kZero; + else if (invalid == "hold") + config.invalid_mode = InvalidMode::kHold; + else + throw std::invalid_argument( + "RlBridge: invalid_value must be nan|zero|hold " + "(quote it in YAML: invalid_value: \"nan\" — an unquoted " + "nan is parsed as a float), got '" + + string_or(node, "invalid_value", "") + "'"); + + config.enable_path = string_or(node, "enable_interface", config.rl_base + "/enable"); + config.enable_default = bool_or(node, "enable_default", false); + config.reset_path = string_or(node, "reset_interface", ""); + return config; +} + +} // namespace rmcs_rl diff --git a/src/rl_bridge/interface_binding.cpp b/src/rl_bridge/interface_binding.cpp index 16443b2..ff20f05 100644 --- a/src/rl_bridge/interface_binding.cpp +++ b/src/rl_bridge/interface_binding.cpp @@ -79,7 +79,6 @@ std::size_t acquire_slot( Slot slot; slot.path = path; slot.binding = selected; - slot.required = required; switch (selected) { case Binding::kDouble: slot.double_value = std::make_unique>(); diff --git a/src/rl_bridge/joint_config.cpp b/src/rl_bridge/joint_config.cpp index 4abb641..52f40c2 100644 --- a/src/rl_bridge/joint_config.cpp +++ b/src/rl_bridge/joint_config.cpp @@ -2,7 +2,7 @@ #include -#include +#include #include namespace rmcs_rl { diff --git a/src/rl_bridge/observation_history.cpp b/src/rl_bridge/observation_history.cpp new file mode 100644 index 0000000..cb88e9f --- /dev/null +++ b/src/rl_bridge/observation_history.cpp @@ -0,0 +1,34 @@ +#include + +#include +#include + +namespace rmcs_rl { + +ObservationHistory::ObservationHistory(std::size_t frame_size, std::size_t history_length) + : frame_size_(frame_size) + , values_(frame_size * history_length) { + if (frame_size == 0 || history_length == 0) + throw std::invalid_argument("observation frame size and history length must be positive"); +} + +const std::vector& ObservationHistory::append(std::span frame) { + if (frame.size() != frame_size_) + throw std::invalid_argument("observation frame does not match configured frame size"); + if (!initialized_) { + for (std::size_t offset = 0; offset < values_.size(); offset += frame_size_) + std::copy(frame.begin(), frame.end(), values_.begin() + offset); + initialized_ = true; + } else { + std::move(values_.begin() + frame_size_, values_.end(), values_.begin()); + std::copy(frame.begin(), frame.end(), values_.end() - frame_size_); + } + return values_; +} + +void ObservationHistory::reset() { + initialized_ = false; + std::fill(values_.begin(), values_.end(), 0.0); +} + +} // namespace rmcs_rl diff --git a/test/data/normalized_identity.onnx b/test/data/normalized_identity.onnx new file mode 100644 index 0000000000000000000000000000000000000000..1dbdfa3b0d17d15ff09c67d66441e4566832d99b GIT binary patch literal 292 zcmZvWL2JT56ojj3ad{}}ON-J%59U}a$+o=&3Z*yyf|syaQ(Q=P%iE_I$&c6CDjs^B znQvx0rP(;^Ct|)VEE}%z&N`}8X?E(z$-c~%*HkR-e}NE&qJ=%^;7zVr zub?g3`6HZq@IU|a8mq86P$;&nx5EQT?7Y`f!Am output "actions" float32 [1, N_act]. -The synthetic policy outputs constant zeros: in RL state, position PD holds -default_dof_pos — safe for bench pipeline validation (no learned behavior). - -Sizes come from --obs/--act, or from the deployment YAML (--from-config) so the -model shape always matches the bridge contract; metadata is *not* stamped here -(run stamp_layout_metadata.py afterwards, then check_policy_contract.py). - -Negative test: generate with a wrong obs size (e.g. --obs 42) and verify the -consumer refuses to load (obs size mismatch). - -Usage: - python3 gen_synthetic_policy.py --obs 22 --act 4 -o policy.onnx - python3 gen_synthetic_policy.py --from-config deploy.yaml --node rl_bridge -o policy.onnx -""" +"""Generate a zero-action model for offline contract regression fixtures.""" import argparse import sys +from pathlib import Path +sys.path.insert(0, str(Path(__file__).resolve().parents[1] / "tool")) import rl_layout as layout -def _export_with_torch(obs: int, act: int, output: str) -> bool: - """torch 可用则用 torch.onnx.export（保留历史导出路径）；不可用返回 False。""" - try: - import torch - import torch.nn as nn - except ImportError: - return False - - class _ZeroPolicy(nn.Module): - def __init__(self, obs_size: int, act_size: int) -> None: - super().__init__() - self.linear = nn.Linear(obs_size, act_size, bias=False) - with torch.no_grad(): - self.linear.weight.zero_() - - def forward(self, obs: torch.Tensor) -> torch.Tensor: - return self.linear(obs) - - model = _ZeroPolicy(obs, act).eval() - dummy = torch.zeros(1, obs, dtype=torch.float32) - torch.onnx.export( - model, - dummy, - output, - input_names=["obs"], - output_names=["actions"], - opset_version=13, - ) - return True - - def _export_with_onnx(obs: int, act: int, output: str) -> None: - """无 torch 时的等价实现：actions = obs @ W，W 全零 → 恒零动作。""" + """actions = obs @ W with zero weights; no training dependency.""" import numpy as np import onnx from onnx import TensorProto, helper, numpy_helper @@ -111,15 +66,12 @@ def main() -> None: print(f"ERROR: obs/act 必须为正整数（obs={obs} act={act}）", file=sys.stderr) sys.exit(1) - backend = "torch" if _export_with_torch(obs, act, args.output) else "onnx" - if backend == "onnx": - _export_with_onnx(obs, act, args.output) + _export_with_onnx(obs, act, args.output) print( f"wrote {args.output}: obs float32[1,{obs}] -> actions float32[1,{act}] " "(zero policy)" ) - print(f"backend: {backend}") if __name__ == "__main__": diff --git a/test/runtime_test.cpp b/test/runtime_test.cpp new file mode 100644 index 0000000..df2c3c8 --- /dev/null +++ b/test/runtime_test.cpp @@ -0,0 +1,116 @@ +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#include +#include +#include +#include + +#include "policy/policy_model.hpp" + +namespace rmcs_rl { +namespace { + +TEST(ObservationHistory, PreservesFrameSizeOrderAndReset) { + ObservationHistory history{2, 3}; + EXPECT_EQ(history.append(std::array{1.0, 2.0}), (std::vector{1., 2., 1., 2., 1., 2.})); + EXPECT_EQ(history.append(std::array{3.0, 4.0}), (std::vector{1., 2., 1., 2., 3., 4.})); + EXPECT_EQ(history.append(std::array{5.0, 6.0}), (std::vector{1., 2., 3., 4., 5., 6.})); + history.reset(); + EXPECT_EQ(history.append(std::array{7.0, 8.0}), (std::vector{7., 8., 7., 8., 7., 8.})); + EXPECT_THROW(history.append(std::array{1.0}), std::invalid_argument); +} + +TEST(ObservationTimeline, RejectsPreResetAndOlderActions) { + using namespace std::chrono_literals; + const ObservationTimeline::Clock::time_point start{}; + ObservationTimeline timeline; + EXPECT_TRUE(timeline.due(start, 20ms)); + EXPECT_TRUE(std::isnan(timeline.age(0, start))); + const auto first = timeline.publish(start); + EXPECT_FALSE(timeline.due(start + 19ms, 20ms)); + EXPECT_TRUE(timeline.due(start + 20ms, 20ms)); + const auto second = timeline.publish(start + 20ms); + EXPECT_DOUBLE_EQ(timeline.age(first, start + 30ms), 0.03); + EXPECT_DOUBLE_EQ(timeline.age(second, start + 30ms), 0.01); + timeline.reset(); + EXPECT_TRUE(std::isnan(timeline.age(second, start + 31ms))); + const auto third = timeline.publish(start + 31ms); + EXPECT_GT(third, second); + EXPECT_TRUE(std::isnan(timeline.age(second, start + 32ms))); + EXPECT_DOUBLE_EQ(timeline.age(third, start + 32ms), 0.001); + timeline.publish(start + 51ms); + EXPECT_TRUE(std::isnan(timeline.age(second, start + 52ms))); +} + +TEST(ActionChannel, ConcurrentSnapshotsNeverMixFrames) { + ActionChannel channel; + channel.resize(6); + ActionSnapshot snapshot; + EXPECT_FALSE(channel.try_read(snapshot)); + std::atomic finished = false; + std::jthread writer{[&] { + msg::Action message; + message.action.resize(6); + for (std::uint64_t sequence = 1; sequence <= 10000; ++sequence) { + message.obs_seq = message.model_id = message.layout_hash = sequence; + std::fill(message.action.begin(), message.action.end(), static_cast(sequence)); + channel.store(message); + } + finished = true; + }}; + do { + if (!channel.try_read(snapshot)) + continue; + EXPECT_EQ(snapshot.model_id, snapshot.obs_seq); + EXPECT_EQ(snapshot.layout_hash, snapshot.obs_seq); + for (const double action : snapshot.action) + EXPECT_EQ(action, static_cast(snapshot.obs_seq)); + } while (!finished); + writer.join(); + ASSERT_TRUE(channel.try_read(snapshot)); + EXPECT_EQ(snapshot.obs_seq, 10000u); +} + +TEST(PolicyModel, NormalizesClipsAndRejectsInvalidFrames) { + PolicyModel::Config config; + config.path = RMCS_RL_IDENTITY_FIXTURE; + PolicyModel model{config}; + ASSERT_EQ(model.info().obs_size, 2u); + ASSERT_EQ(model.info().action_size, 2u); + std::array action{}; + std::string error; + ASSERT_TRUE(model.run(std::array{3.0, 6.0}, action, error)) << error; + EXPECT_EQ(action, (std::array{1.0, 1.0})); + ASSERT_TRUE(model.run(std::array{9.0, -18.0}, action, error)) << error; + EXPECT_EQ(action, (std::array{1.5, -1.5})); + EXPECT_FALSE(model.run(std::array{1.0}, action, error)); + EXPECT_FALSE( + model.run(std::array{1.0, std::numeric_limits::quiet_NaN()}, action, error)); + ASSERT_TRUE(model.run(std::array{1.0, 2.0}, action, error)) << error; + EXPECT_EQ(action, (std::array{0.0, 0.0})); +} + +TEST(PolicyModel, ParameterClipsOverrideMetadata) { + PolicyModel::Config config; + config.path = RMCS_RL_IDENTITY_FIXTURE; + config.normalization_from_metadata = false; + config.obs_clip = 4.0; + config.action_clip = 3.0; + PolicyModel model{config}; + std::array action{}; + std::string error; + ASSERT_TRUE(model.run(std::array{6.0, -6.0}, action, error)) << error; + EXPECT_EQ(action, (std::array{3.0, -3.0})); +} + +} // namespace +} // namespace rmcs_rl +#include diff --git a/test/test_layout.py b/test/test_layout.py new file mode 100644 index 0000000..1325c27 --- /dev/null +++ b/test/test_layout.py @@ -0,0 +1,126 @@ +#!/usr/bin/env python3 +"""Regression fixtures for the Python/C++ layout contract.""" +import sys +from pathlib import Path + +sys.path.insert(0, str(Path(__file__).resolve().parents[1] / "tool")) +import rl_layout as layout + + +def _self_test() -> None: + """断言语法表（含「同签名与 C++ 接口类型无关」）+ FNV 稳定性。""" + for spec in ("path=/chassis/control_height", + "path=/chassis/control_height type=scalar"): + term = layout.parse_obs_term(spec, 6) + assert term["kind"] == "scalar", term + assert term["dim"] == 1 and term["id"] == "/chassis/control_height", term + assert term["scale"] == 1.0 and term["clip"] is None, term + + base = layout.parse_obs_term("path=/v take=x", 6) + assert (base["dim"], base["id"], base["kind"]) == (1, "vec3c:/v:x", "component"), base + for interface in ("vector3", "direction_vector", "scalar"): + other = layout.parse_obs_term(f"path=/v take=x type={interface}", 6) + assert (other["dim"], other["id"]) == (1, "vec3c:/v:x"), other + assert layout.obs_signature(["path=/v take=x"], 6) == layout.obs_signature(["path=/v take=x type=direction_vector"], 6) + assert layout.obs_signature(["path=/v take=x"], 6) == "v3-history=1|vec3c:/v:x@1" + for axis in ("x", "y", "z"): + assert layout.parse_obs_term(f"path=/v take={axis}", 6)["id"] == f"vec3c:/v:{axis}" + + for alias in ("vec3", "vec", "all", "vector"): + term = layout.parse_obs_term(f"path=/v take={alias}", 6) + assert (term["dim"], term["id"], term["kind"]) == (3, "vec3:/v", "vec3"), term + assert layout.parse_obs_term("path=/v take=vec3 scale=0.5", 6)["scale"] == 0.5 + + gravity = layout.parse_obs_term("path=/imu/quaternion transform=projected_gravity", 6) + assert (gravity["dim"], gravity["id"], gravity["kind"]) == (3, "gravity:/imu/quaternion", "gravity") + assert layout.parse_obs_term("path=/imu/quaternion take=gravity", 6)["id"] == "gravity:/imu/quaternion" + assert layout.obs_signature(["path=/imu/quaternion transform=projected_gravity type=quaternion"], 6) \ + == layout.obs_signature(["path=/imu/quaternion transform=projected_gravity"], 6) + _expect_error(lambda: layout.parse_obs_term("path=/imu/quaternion type=quaternion", 6), "quaternion") + + joint_pos = layout.parse_obs_term("type=joint_pos joints=a,b relative=true", 6) + assert (joint_pos["dim"], joint_pos["id"], joint_pos["relative"]) == (2, "joint_pos:rel:a+b", True) + assert layout.parse_obs_term("type=joint_pos joints=a,b", 6)["id"] == "joint_pos:abs:a+b" + assert layout.parse_obs_term("type=joint_pos joints=a,b zero=true", 6)["id"] == "joint_pos:zero:a+b" + assert layout.parse_obs_term("type=joint_pos joints=a,b relative=false", 6)["id"] == "joint_pos:abs:a+b" + assert joint_pos["joints"] == ["a", "b"] and joint_pos["kind"] == "joint_pos" + assert layout.parse_obs_term("type=joint_vel joints=a,b", 6)["id"] == "joint_vel:abs:a+b" + assert layout.parse_obs_term("type=joint_torque joints=a,b scale=0.25", 6)["id"] == "joint_torque:abs:a+b" + assert layout.parse_obs_term("type=joint_torque joints=a,b scale=0.25", 6)["scale"] == 0.25 + _expect_error(lambda: layout.parse_obs_term("type=joint_pos joints=", 6), "joints") + + last = layout.parse_obs_term("type=last_action", 6) + assert (last["dim"], last["id"]) == (6, "last_action:0+1+2+3+4+5"), last + assert last["indices"] == [0, 1, 2, 3, 4, 5] + assert layout.parse_obs_term("type=last_action indices=0,1,2", 6)["id"] == "last_action:0+1+2" + range_term = layout.parse_obs_term("type=last_action indices=0..5", 6) + assert (range_term["dim"], range_term["id"]) == (6, "last_action:0+1+2+3+4+5"), range_term + _expect_error(lambda: layout.parse_obs_term("type=last_action indices=0..9", 6), "越界") + + const = layout.parse_obs_term("type=constant value=1,0,0.5", 6) + assert (const["dim"], const["id"], const["constants"]) == (3, "constant:1+0+0.5", [1.0, 0.0, 0.5]), const + assert layout.parse_obs_term("type=constant value=1.0,0.0000001", 6)["id"] == "constant:1+1e-07" + + named = layout.parse_obs_term("path=/v take=vec3 name=my_obs", 6) + assert (named["id"], named["dim"]) == ("my_obs", 3), named + + for alias in ("double", "bool", "int", "size", "size_t", "vec3"): + assert layout.parse_obs_term(f"path=/v take=x type={alias}", 6)["id"] == "vec3c:/v:x", alias + assert layout.parse_obs_term("path=/v type=bool", 6)["id"] == "/v" + assert layout.parse_obs_term("path=/v clip=0.5", 6)["clip"] == 0.5 + assert layout.parse_obs_term("path=/v clip=-1:1", 6)["clip"] == (-1.0, 1.0) + _expect_error(lambda: layout.parse_obs_term("path=/v clip=1:-1", 6), "clip") + + assert layout.obs_signature(["path=/v scale=2 clip=10 index=3 default=0.1"], 6) == "v3-history=1|/v*2@1" + assert layout.obs_signature(["path=/v"], 6) == "v3-history=1|/v@1" + + action = layout.parse_action_term("index=0 output=/rl/action/lf0") + assert (action["index"], action["output"], action["name"], action["id"]) \ + == (0, "/rl/action/lf0", "/rl/action/lf0", "#0:/rl/action/lf0"), action + assert layout.parse_action_term("index=1 output=/o name=hip scale=0.5")["id"] == "#1:hip*0.5" + assert layout.action_signature(["index=0 output=/a", "index=1 output=/b scale=0.5"]) == "v2|#0:/a|#1:/b*0.5" + assert layout.action_signature(["index=1 output=/b", "index=0 output=/a"]) == "v2|#0:/a|#1:/b" + _expect_error(lambda: layout.action_signature(["index=0 output=/a", "index=2 output=/c"]), "置换") + _expect_error(lambda: layout.action_signature(["index=0 output=/a", "index=0 output=/b"]), "置换") + + _expect_error(lambda: layout.parse_obs_term("path=/v scale=0", 6), "scale") + _expect_error(lambda: layout.parse_obs_term("path=/v bogus=1", 6), "未知键") + _expect_error(lambda: layout.parse_obs_term("take=x", 6), "path") + _expect_error(lambda: layout.parse_obs_term("path=/v take=w", 6), "take") + _expect_error(lambda: layout.parse_obs_term("path=/v transform=foo", 6), "transform") + _expect_error(lambda: layout.parse_action_term("output=/a"), "index") + _expect_error(lambda: layout.parse_action_term("index=0"), "output") + + assert layout.fnv1a64(b"") == 0xCBF29CE484222325 + assert layout.fnv1a64(b"a") == 0xAF63DC4C8601EC8C + assert layout.fnv1a64(b"abc") == 0xE71FA2190541574B + assert layout.fnv1a64(b"foobar") == 0x85944171F73967E8 + fixed = layout.layout_hash("v2|/chassis/control_height@1|vec3c:/chassis/control_velocity:x@1", + "v2|#0:/a", 20, 6) + assert fixed == 0xC841398B19839E56, layout.hex16(fixed) + assert layout.hex16(0x1A2B3C4D5E6F7788) == "0x1a2b3c4d5e6f7788" + assert layout.hex16(layout.layout_hash("v2", "v2", 0, 0)) == layout.hex16(layout.fnv1a64(b"v2||v2||0x0")) + + assert layout.parse_signature("v2|/a@1")["version"] == "v2" + assert layout.parse_signature("v2")["version"] == "v2" + assert layout.parse_signature("v1|/a@1")["version"] == "v1" + assert layout.is_v1_signature("vector3_component:/v:x@1") + assert layout.is_v1_signature("direction_vector_component:/v:x@1") + assert layout.is_v1_signature("") and layout.is_v1_signature(None) + assert not layout.is_v1_signature("v2|vec3c:/v:x@1") + assert layout.obs_signature_dim("v2|/a@1|vec3:/v@3") == 4 + + print("rl_layout self-test OK") + + +def _expect_error(fn, needle: str) -> None: + try: + fn() + except layout.LayoutError as exc: + assert needle in str(exc), f"错误消息 {exc!r} 未包含 {needle!r}" + return + raise AssertionError(f"应当抛 layout.LayoutError（{needle}）但没有") + + +if __name__ == "__main__": + _self_test() diff --git a/tool/test_layout_contract.sh b/test/test_layout_contract.sh similarity index 85% rename from tool/test_layout_contract.sh rename to test/test_layout_contract.sh index 6072076..7786a6c 100755 --- a/tool/test_layout_contract.sh +++ b/test/test_layout_contract.sh @@ -3,8 +3,11 @@ set -u HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" PKG="$(cd "$HERE/.." && pwd)" +TOOLS="$PKG/tool" PY="${PYTHON:-python3}" -WORK="${TMPDIR:-/tmp}" +WORK="$(mktemp -d "${TMPDIR:-/tmp}/rmcs-rl-contract.XXXXXX")" +trap 'rm -rf "$WORK"' EXIT +cd "$WORK" FIXTURE="$WORK/x.yaml" FIXTURE_TYPES="$WORK/x_types.yaml" MODEL="$WORK/policy.onnx" @@ -71,18 +74,18 @@ sed -e 's|path=/chassis/control_height |path=/chassis/control_height type=scalar "$FIXTURE" >"$FIXTURE_TYPES" echo "== 1. 词条语法自检（rl_layout.py）==" -run_expect 0 "rl_layout self-test" "$PY" "$HERE/rl_layout.py" +run_expect 0 "rl_layout self-test" "$PY" "$HERE/test_layout.py" expect_msg "rl_layout self-test OK" "self-test OK" echo "== 2. 生成 → 盖章 → 校验（正例必须 PASS）==" run_expect 0 "gen_synthetic_policy --from-config" \ "$PY" "$HERE/gen_synthetic_policy.py" --from-config "$FIXTURE" -o "$MODEL" run_expect 0 "stamp_layout_metadata" \ - "$PY" "$HERE/stamp_layout_metadata.py" --model "$MODEL" --from-config "$FIXTURE" + "$PY" "$TOOLS/stamp_layout_metadata.py" --model "$MODEL" --from-config "$FIXTURE" cat "$LOG" SHA_BEFORE="$(sha256sum "$MODEL" | cut -d' ' -f1)" run_expect 0 "stamp_layout_metadata（幂等重跑）" \ - "$PY" "$HERE/stamp_layout_metadata.py" --model "$MODEL" --from-config "$FIXTURE" + "$PY" "$TOOLS/stamp_layout_metadata.py" --model "$MODEL" --from-config "$FIXTURE" SHA_AFTER="$(sha256sum "$MODEL" | cut -d' ' -f1)" if [ "$SHA_BEFORE" = "$SHA_AFTER" ]; then ok "盖章幂等（文件字节不变）" @@ -90,14 +93,14 @@ else bad "盖章非幂等：$SHA_BEFORE != $SHA_AFTER" fi run_expect 0 "check_policy_contract（正例）" \ - "$PY" "$HERE/check_policy_contract.py" "$MODEL" --config "$FIXTURE" + "$PY" "$TOOLS/check_policy_contract.py" "$MODEL" --config "$FIXTURE" cat "$LOG" expect_msg "== SUMMARY: PASS ==" "SUMMARY PASS" echo "== 3. 逃生口 type= 不改变布局指纹 ==" -SIG_PLAIN="$("$PY" "$HERE/check_policy_contract.py" --print-layout --config "$FIXTURE" \ +SIG_PLAIN="$("$PY" "$TOOLS/check_policy_contract.py" --print-layout --config "$FIXTURE" \ | grep -E 'obs_signature|action_signature|layout_hash')" -SIG_TYPES="$("$PY" "$HERE/check_policy_contract.py" --print-layout --config "$FIXTURE_TYPES" \ +SIG_TYPES="$("$PY" "$TOOLS/check_policy_contract.py" --print-layout --config "$FIXTURE_TYPES" \ | grep -E 'obs_signature|action_signature|layout_hash')" if [ -n "$SIG_PLAIN" ] && [ "$SIG_PLAIN" = "$SIG_TYPES" ]; then ok "带/不带 type= 的规范串与 layout_hash 完全一致" @@ -118,7 +121,7 @@ model.metadata_props.extend(keep) onnx.save(model, dst) PYEOF run_expect 1 "(a) metadata 缺 rmcs_obs_layout" \ - "$PY" "$HERE/check_policy_contract.py" "$WORK/policy_neg_a.onnx" --config "$FIXTURE" + "$PY" "$TOOLS/check_policy_contract.py" "$WORK/policy_neg_a.onnx" --config "$FIXTURE" expect_msg "rmcs_obs_layout" "缺键提示" "$PY" - "$FIXTURE" "$WORK/x_swapped.yaml" <<'PYEOF' @@ -137,7 +140,7 @@ doc["rl_bridge"]["ros__parameters"]["observation_terms"] = terms yaml.safe_dump(doc, open(dst, "w", encoding="utf-8"), allow_unicode=True, sort_keys=False) PYEOF run_expect 1 "(b) 真·换序（index 位置不变，语义换位）" \ - "$PY" "$HERE/check_policy_contract.py" "$MODEL" --config "$WORK/x_swapped.yaml" + "$PY" "$TOOLS/check_policy_contract.py" "$MODEL" --config "$WORK/x_swapped.yaml" expect_msg "rmcs_obs_layout" "签名不一致提示" "$PY" - "$FIXTURE" "$WORK/x_index_clash.yaml" <<'PYEOF' @@ -149,7 +152,7 @@ terms[0], terms[1] = terms[1], terms[0] # 只换顺序，index= 保持 yaml.safe_dump(doc, open(dst, "w", encoding="utf-8"), allow_unicode=True, sort_keys=False) PYEOF run_expect 1 "(b2) 换序但不改 index= → index 断言" \ - "$PY" "$HERE/check_policy_contract.py" "$MODEL" --config "$WORK/x_index_clash.yaml" + "$PY" "$TOOLS/check_policy_contract.py" "$MODEL" --config "$WORK/x_index_clash.yaml" expect_msg "index=" "index 断言提示" "$PY" - "$FIXTURE" "$WORK/x_scale.yaml" <<'PYEOF' @@ -161,7 +164,7 @@ terms[5] = terms[5].replace("scale=0.1", "scale=0.2") # joint_vel 缩放 yaml.safe_dump(doc, open(dst, "w", encoding="utf-8"), allow_unicode=True, sort_keys=False) PYEOF run_expect 1 "(c) 改一个 scale=" \ - "$PY" "$HERE/check_policy_contract.py" "$MODEL" --config "$WORK/x_scale.yaml" + "$PY" "$TOOLS/check_policy_contract.py" "$MODEL" --config "$WORK/x_scale.yaml" expect_msg "policy_layout_hash" "hash 不一致提示" "$PY" - "$MODEL" "$WORK/policy_neg_d.onnx" <<'PYEOF' @@ -174,7 +177,7 @@ for prop in model.metadata_props: onnx.save(model, dst) PYEOF run_expect 1 "(d) policy_layout_hash 写错" \ - "$PY" "$HERE/check_policy_contract.py" "$WORK/policy_neg_d.onnx" --config "$FIXTURE" + "$PY" "$TOOLS/check_policy_contract.py" "$WORK/policy_neg_d.onnx" --config "$FIXTURE" expect_msg "policy_layout_hash" "hash 校验失败提示" "$PY" - "$FIXTURE" "$WORK/x_actsize.yaml" <<'PYEOF' @@ -185,7 +188,7 @@ doc["rl_bridge"]["ros__parameters"]["rl_action_size"] = 5 # 词条是 6 条 yaml.safe_dump(doc, open(dst, "w", encoding="utf-8"), allow_unicode=True, sort_keys=False) PYEOF run_expect 1 "(e) rl_action_size != 动作词条数" \ - "$PY" "$HERE/check_policy_contract.py" "$MODEL" --config "$WORK/x_actsize.yaml" + "$PY" "$TOOLS/check_policy_contract.py" "$MODEL" --config "$WORK/x_actsize.yaml" expect_msg "rl_action_size" "尺寸不一致提示" echo diff --git a/tool/gen_drive_policy.py b/tool/gen_drive_policy.py deleted file mode 100644 index 48837c6..0000000 --- a/tool/gen_drive_policy.py +++ /dev/null @@ -1,72 +0,0 @@ -#!/usr/bin/env python3 -"""Generate a drive-style validation policy ONNX for rmcs_rl deployment testing. - -This is an *example* synthetic model for one concrete contract (4 joints, -height-command driven); for other contracts use gen_synthetic_policy.py or -export the real trained policy. Contract must match the YAML config exactly: - input "obs" float32 [1, 22] -> output "actions" float32 [1, 4]. -Layout (identical to the deployment obs builder): - obs[0:3] = commands (vx, 0, yaw_rate) -- reserved, unused - obs[3] = height_cmd * 5.0 - obs[4:7] = ang_vel * 0.5 - obs[7:10] = projected gravity - obs[10:14]= joint pos deviation (position-PD group) - obs[14:18]= joint vel * 0.1 - obs[18:22]= last actions - -Behavior (deterministic, bounded, no state): - a_i = clip( A * tanh(K * (height_cmd - h0)) + bias_i, -clip, clip ) - -> all joints follow the height command (slight per-joint bias for asymmetry), - exercising the full obs -> policy -> action -> PD -> torque -> joint loop. - The height_cmd range below is an example; align with your config. - -Usage: - python3 gen_drive_policy.py -o policy_drive.onnx -""" -import argparse - -import torch -import torch.nn as nn - - -class DrivePolicy(nn.Module): - def __init__(self, amp: float = 2.0, gain: float = 8.0, h0: float = 0.132, - bias=(0.15, -0.08, 0.08, -0.15), clip: float = 2.0): - super().__init__() - self.amp = amp - self.gain = gain - self.h0 = h0 - self.register_buffer("bias", torch.tensor(bias, dtype=torch.float32)) - self.clip = clip - - def forward(self, obs: torch.Tensor) -> torch.Tensor: - height_cmd = obs[:, 3:4] / 5.0 - a = self.amp * torch.tanh(self.gain * (height_cmd - self.h0)) - a = a + self.bias.unsqueeze(0) - return torch.clamp(a, -self.clip, self.clip) - - -def main() -> None: - parser = argparse.ArgumentParser() - parser.add_argument("-o", "--output", default="policy_drive.onnx") - args = parser.parse_args() - - model = DrivePolicy().eval() - dummy = torch.zeros(1, 22, dtype=torch.float32) - with torch.no_grad(): - for h in (0.05, 0.132, 0.17): - obs = dummy.clone() - obs[0, 3] = h * 5.0 - a = model(obs) - target = 0.25 * a + 0.3 - print(f"height={h:.3f} -> actions={a[0].tolist()} (pos target ~{target[0].tolist()})") - - torch.onnx.export( - model, dummy, args.output, - input_names=["obs"], output_names=["actions"], opset_version=13, - ) - print(f"wrote {args.output}: obs float32[1,22] -> actions float32[1,4]") - - -if __name__ == "__main__": - main() diff --git a/tool/rl_layout.py b/tool/rl_layout.py index acc850e..a67a222 100644 --- a/tool/rl_layout.py +++ b/tool/rl_layout.py @@ -3,7 +3,7 @@ C++ 桥（rl_bridge）与策略进程各自实现同一份规范（planning/docs/bridge-design.md §6.2/§6.3）， Python 侧的真源就是本模块：stamp_layout_metadata.py / check_policy_contract.py / -gen_synthetic_policy.py 全部从这里取语法与 hash，避免同一份契约靠人写两遍（drift）。 +测试夹具全部从这里取语法与 hash，避免同一份契约靠人写两遍（drift）。 观测词条（YAML observation_terms，每个元素是一个 "key=value ..." 字符串）： path / take / transform / type / index / scale / clip / default / name @@ -782,123 +782,3 @@ def _join_floats(values) -> str: if isinstance(values, str): values = [v for v in values.replace(" ", "").split(",") if v != ""] return ",".join(format_scale(float(v)) for v in values) - - - -def _self_test() -> None: - """断言语法表（含「同签名与 C++ 接口类型无关」）+ FNV 稳定性。""" - for spec in ("path=/chassis/control_height", - "path=/chassis/control_height type=scalar"): - term = parse_obs_term(spec, 6) - assert term["kind"] == "scalar", term - assert term["dim"] == 1 and term["id"] == "/chassis/control_height", term - assert term["scale"] == 1.0 and term["clip"] is None, term - - base = parse_obs_term("path=/v take=x", 6) - assert (base["dim"], base["id"], base["kind"]) == (1, "vec3c:/v:x", "component"), base - for interface in ("vector3", "direction_vector", "scalar"): - other = parse_obs_term(f"path=/v take=x type={interface}", 6) - assert (other["dim"], other["id"]) == (1, "vec3c:/v:x"), other - assert obs_signature(["path=/v take=x"], 6) == obs_signature(["path=/v take=x type=direction_vector"], 6) - assert obs_signature(["path=/v take=x"], 6) == "v3-history=1|vec3c:/v:x@1" - for axis in ("x", "y", "z"): - assert parse_obs_term(f"path=/v take={axis}", 6)["id"] == f"vec3c:/v:{axis}" - - for alias in ("vec3", "vec", "all", "vector"): - term = parse_obs_term(f"path=/v take={alias}", 6) - assert (term["dim"], term["id"], term["kind"]) == (3, "vec3:/v", "vec3"), term - assert parse_obs_term("path=/v take=vec3 scale=0.5", 6)["scale"] == 0.5 - - gravity = parse_obs_term("path=/imu/quaternion transform=projected_gravity", 6) - assert (gravity["dim"], gravity["id"], gravity["kind"]) == (3, "gravity:/imu/quaternion", "gravity") - assert parse_obs_term("path=/imu/quaternion take=gravity", 6)["id"] == "gravity:/imu/quaternion" - assert obs_signature(["path=/imu/quaternion transform=projected_gravity type=quaternion"], 6) \ - == obs_signature(["path=/imu/quaternion transform=projected_gravity"], 6) - _expect_error(lambda: parse_obs_term("path=/imu/quaternion type=quaternion", 6), "quaternion") - - joint_pos = parse_obs_term("type=joint_pos joints=a,b relative=true", 6) - assert (joint_pos["dim"], joint_pos["id"], joint_pos["relative"]) == (2, "joint_pos:rel:a+b", True) - assert parse_obs_term("type=joint_pos joints=a,b", 6)["id"] == "joint_pos:abs:a+b" - assert parse_obs_term("type=joint_pos joints=a,b zero=true", 6)["id"] == "joint_pos:zero:a+b" - assert parse_obs_term("type=joint_pos joints=a,b relative=false", 6)["id"] == "joint_pos:abs:a+b" - assert joint_pos["joints"] == ["a", "b"] and joint_pos["kind"] == "joint_pos" - assert parse_obs_term("type=joint_vel joints=a,b", 6)["id"] == "joint_vel:abs:a+b" - assert parse_obs_term("type=joint_torque joints=a,b scale=0.25", 6)["id"] == "joint_torque:abs:a+b" - assert parse_obs_term("type=joint_torque joints=a,b scale=0.25", 6)["scale"] == 0.25 - _expect_error(lambda: parse_obs_term("type=joint_pos joints=", 6), "joints") - - last = parse_obs_term("type=last_action", 6) - assert (last["dim"], last["id"]) == (6, "last_action:0+1+2+3+4+5"), last - assert last["indices"] == [0, 1, 2, 3, 4, 5] - assert parse_obs_term("type=last_action indices=0,1,2", 6)["id"] == "last_action:0+1+2" - range_term = parse_obs_term("type=last_action indices=0..5", 6) - assert (range_term["dim"], range_term["id"]) == (6, "last_action:0+1+2+3+4+5"), range_term - _expect_error(lambda: parse_obs_term("type=last_action indices=0..9", 6), "越界") - - const = parse_obs_term("type=constant value=1,0,0.5", 6) - assert (const["dim"], const["id"], const["constants"]) == (3, "constant:1+0+0.5", [1.0, 0.0, 0.5]), const - assert parse_obs_term("type=constant value=1.0,0.0000001", 6)["id"] == "constant:1+1e-07" - - named = parse_obs_term("path=/v take=vec3 name=my_obs", 6) - assert (named["id"], named["dim"]) == ("my_obs", 3), named - - for alias in ("double", "bool", "int", "size", "size_t", "vec3"): - assert parse_obs_term(f"path=/v take=x type={alias}", 6)["id"] == "vec3c:/v:x", alias - assert parse_obs_term("path=/v type=bool", 6)["id"] == "/v" - assert parse_obs_term("path=/v clip=0.5", 6)["clip"] == 0.5 - assert parse_obs_term("path=/v clip=-1:1", 6)["clip"] == (-1.0, 1.0) - _expect_error(lambda: parse_obs_term("path=/v clip=1:-1", 6), "clip") - - assert obs_signature(["path=/v scale=2 clip=10 index=3 default=0.1"], 6) == "v3-history=1|/v*2@1" - assert obs_signature(["path=/v"], 6) == "v3-history=1|/v@1" - - action = parse_action_term("index=0 output=/rl/action/lf0") - assert (action["index"], action["output"], action["name"], action["id"]) \ - == (0, "/rl/action/lf0", "/rl/action/lf0", "#0:/rl/action/lf0"), action - assert parse_action_term("index=1 output=/o name=hip scale=0.5")["id"] == "#1:hip*0.5" - assert action_signature(["index=0 output=/a", "index=1 output=/b scale=0.5"]) == "v2|#0:/a|#1:/b*0.5" - assert action_signature(["index=1 output=/b", "index=0 output=/a"]) == "v2|#0:/a|#1:/b" - _expect_error(lambda: action_signature(["index=0 output=/a", "index=2 output=/c"]), "置换") - _expect_error(lambda: action_signature(["index=0 output=/a", "index=0 output=/b"]), "置换") - - _expect_error(lambda: parse_obs_term("path=/v scale=0", 6), "scale") - _expect_error(lambda: parse_obs_term("path=/v bogus=1", 6), "未知键") - _expect_error(lambda: parse_obs_term("take=x", 6), "path") - _expect_error(lambda: parse_obs_term("path=/v take=w", 6), "take") - _expect_error(lambda: parse_obs_term("path=/v transform=foo", 6), "transform") - _expect_error(lambda: parse_action_term("output=/a"), "index") - _expect_error(lambda: parse_action_term("index=0"), "output") - - assert fnv1a64(b"") == 0xCBF29CE484222325 - assert fnv1a64(b"a") == 0xAF63DC4C8601EC8C - assert fnv1a64(b"abc") == 0xE71FA2190541574B - assert fnv1a64(b"foobar") == 0x85944171F73967E8 - fixed = layout_hash("v2|/chassis/control_height@1|vec3c:/chassis/control_velocity:x@1", - "v2|#0:/a", 20, 6) - assert fixed == 0xC841398B19839E56, hex16(fixed) - assert hex16(0x1A2B3C4D5E6F7788) == "0x1a2b3c4d5e6f7788" - assert hex16(layout_hash("v2", "v2", 0, 0)) == hex16(fnv1a64(b"v2||v2||0x0")) - - assert parse_signature("v2|/a@1")["version"] == "v2" - assert parse_signature("v2")["version"] == "v2" - assert parse_signature("v1|/a@1")["version"] == "v1" - assert is_v1_signature("vector3_component:/v:x@1") - assert is_v1_signature("direction_vector_component:/v:x@1") - assert is_v1_signature("") and is_v1_signature(None) - assert not is_v1_signature("v2|vec3c:/v:x@1") - assert obs_signature_dim("v2|/a@1|vec3:/v@3") == 4 - - print("rl_layout self-test OK") - - -def _expect_error(fn, needle: str) -> None: - try: - fn() - except LayoutError as exc: - assert needle in str(exc), f"错误消息 {exc!r} 未包含 {needle!r}" - return - raise AssertionError(f"应当抛 LayoutError（{needle}）但没有") - - -if __name__ == "__main__": - _self_test() From a12f942e1dcb71d54e347649bb22390293b96fe4 Mon Sep 17 00:00:00 2001 From: ZGZ713912 Date: Tue, 29 Sep 2026 05:20:12 +0800 Subject: [PATCH 2/9] test(ActionChannel): add test for concurrent snapshot handling --- include/rmcs_rl/rl_bridge/action_channel.hpp | 2 ++ src/rl_bridge/action_channel.cpp | 8 ++++- test/runtime_test.cpp | 36 ++++++++++++++++++++ 3 files changed, 45 insertions(+), 1 deletion(-) diff --git a/include/rmcs_rl/rl_bridge/action_channel.hpp b/include/rmcs_rl/rl_bridge/action_channel.hpp index e948bf4..8268069 100644 --- a/include/rmcs_rl/rl_bridge/action_channel.hpp +++ b/include/rmcs_rl/rl_bridge/action_channel.hpp @@ -1,5 +1,6 @@ #pragma once +#include #include #include #include @@ -23,6 +24,7 @@ class ActionChannel { ActionSnapshot incoming_; std::mutex mutex_; bool received_ = false; + std::atomic has_read_ = false; }; void write_actions( diff --git a/src/rl_bridge/action_channel.cpp b/src/rl_bridge/action_channel.cpp index d2f7c00..31439e5 100644 --- a/src/rl_bridge/action_channel.cpp +++ b/src/rl_bridge/action_channel.cpp @@ -10,6 +10,7 @@ void ActionChannel::resize(std::size_t action_size) { const std::lock_guard lock{mutex_}; incoming_.action.assign(action_size, 0.0); received_ = false; + has_read_.store(false, std::memory_order_release); } void ActionChannel::store(const rmcs_rl::msg::Action& message) { @@ -27,9 +28,14 @@ bool ActionChannel::try_read(ActionSnapshot& snapshot) { // The executor must never wait for the ROS callback. A seqlock cannot protect // concurrent reads/writes of a non-atomic vector under the C++ memory model. const std::unique_lock lock{mutex_, std::try_to_lock}; - if (!lock.owns_lock() || !received_) + if (!lock.owns_lock()) + // Keep the caller's previous snapshot. The bridge still checks its age, + // sequence and contract before allowing it to drive outputs. + return has_read_.load(std::memory_order_acquire); + if (!received_) return false; snapshot = incoming_; + has_read_.store(true, std::memory_order_release); return true; } diff --git a/test/runtime_test.cpp b/test/runtime_test.cpp index df2c3c8..bcf26f8 100644 --- a/test/runtime_test.cpp +++ b/test/runtime_test.cpp @@ -79,6 +79,42 @@ TEST(ActionChannel, ConcurrentSnapshotsNeverMixFrames) { EXPECT_EQ(snapshot.obs_seq, 10000u); } +TEST(ActionChannel, KeepsPreviousSnapshotWhenWriterOwnsLock) { + ActionChannel channel; + channel.resize(1); + + msg::Action message; + message.action = {1.0}; + message.obs_seq = message.layout_hash = message.model_id = 1; + channel.store(message); + + ActionSnapshot snapshot; + ASSERT_TRUE(channel.try_read(snapshot)); + EXPECT_EQ(snapshot.action, (std::vector{1.0})); + + // A second read after the first successful read is allowed to retain the + // caller's snapshot if a concurrent store briefly owns the mutex. The + // channel's public API does not expose the mutex, so this loop exercises + // the same boundary without adding a production-only test hook. + std::atomic finished = false; + std::jthread writer{[&] { + for (std::uint64_t sequence = 2; sequence <= 10000; ++sequence) { + message.obs_seq = message.layout_hash = message.model_id = sequence; + message.action[0] = static_cast(sequence); + channel.store(message); + } + finished = true; + }}; + + while (!finished) { + ASSERT_TRUE(channel.try_read(snapshot)); + ASSERT_EQ(snapshot.action.size(), 1u); + EXPECT_EQ(snapshot.obs_seq, snapshot.model_id); + EXPECT_EQ(snapshot.action.front(), static_cast(snapshot.obs_seq)); + } + writer.join(); +} + TEST(PolicyModel, NormalizesClipsAndRejectsInvalidFrames) { PolicyModel::Config config; config.path = RMCS_RL_IDENTITY_FIXTURE; From e69747f9170041e3c17c2bfdce9704ff0fa73d9b Mon Sep 17 00:00:00 2001 From: ZGZ713912 Date: Tue, 29 Sep 2026 07:49:52 +0800 Subject: [PATCH 3/9] docs(README): update model information and requirements --- README.md | 7 ++++--- models/deformable_sps_V1.onnx | Bin 203240 -> 203250 bytes ...e_sps_V2.onnx => deformable_sps_V2_N.onnx} | Bin 3 files changed, 4 insertions(+), 3 deletions(-) rename models/{deformable_sps_V2.onnx => deformable_sps_V2_N.onnx} (100%) diff --git a/README.md b/README.md index 0eb8657..eec9f31 100644 --- a/README.md +++ b/README.md @@ -71,9 +71,10 @@ python3 src/rmcs_rl/tool/check_policy_contract.py <模型.onnx> --config <车辆 盖章只写元数据；布局匹配不能证明训练侧的坐标或动作含义正确。 更新模型或配置后重启 RMCS。模型或布局不匹配会锁存拒绝动作，需要重启恢复。 -当前 `models/deformable_sps_V2.onnx` 缺少 `rmcs_obs_layout` 和 `rmcs_actions_layout`， -完整契约检查与策略服务会拒绝它。这是已有模型的部署缺口，需核对训练契约后补元数据； -不能只按张量维数推断其含义。 +当前部署使用 `models/deformable_sps_V1.onnx`；其 `rmcs_obs_layout`、 +`rmcs_actions_layout`、`policy_layout_hash` 和 `policy_version` 已按 +`deformable-infantry-omni-rl.yaml` 盖章。盖章只确认运行时布局契约，不能只按张量维数 +推断训练侧的坐标或动作含义；更新模型或 YAML 后必须重新盖章并同步 `expected_model_id`。 ## 运行接口 diff --git a/models/deformable_sps_V1.onnx b/models/deformable_sps_V1.onnx index d0308f37acb45e2dd4b7e3ae522d1555b1b3cbcd..5eaaae99fe03be460a77a289e339d140f13ef1fa 100644 GIT binary patch delta 78 zcmaE{ndj4Ho`x327N#xCTg8-)vvBbjyvT*Sik diff --git a/models/deformable_sps_V2.onnx b/models/deformable_sps_V2_N.onnx similarity index 100% rename from models/deformable_sps_V2.onnx rename to models/deformable_sps_V2_N.onnx From 79851ce8b095897fd8780e1c67f4599519539fa0 Mon Sep 17 00:00:00 2001 From: ZGZ713912 Date: Tue, 29 Sep 2026 22:31:15 +0800 Subject: [PATCH 4/9] feat: support multiple model types and input shapes --- README.md | 34 +++++- src/policy/onnx_runtime.cpp | 193 ++++++++++++++++++++++++++++++---- src/policy/onnx_runtime.hpp | 30 +++++- src/policy/policy_model.cpp | 15 ++- src/policy/policy_model.hpp | 10 ++ src/policy_server.cpp | 26 ++++- test/gen_synthetic_policy.py | 54 +++++++--- tool/check_policy_contract.py | 119 ++++++++++++++++----- tool/rl_layout.py | 11 +- tool/stamp_layout_metadata.py | 28 +++++ tool/stamp_model.sh | 4 +- 11 files changed, 458 insertions(+), 66 deletions(-) diff --git a/README.md b/README.md index eec9f31..dd757c5 100644 --- a/README.md +++ b/README.md @@ -52,10 +52,42 @@ ros2 run rmcs_rl policy_server --ros-args --params-file <车辆配置.yaml> ## 模型与契约 -模型输入为 float32 `obs[batch,N]`，输出为 float32 `actions[batch,M]`，batch 为 1 或动态。 +模型结构由 `policy_server.model_type` 或 ONNX metadata `rmcs_model_type` 切换，支持： + +- `mlp`：输入可以是 float32 `obs[1,N]`，也可以是带历史帧的 `obs[1,history,feature]`； +- `transformer`：输入为 float32 `obs[1,history,feature]`； +- `generic`：保留 rank-1/2/3 的形状适配，供后续单输入结构接入。 + +输出支持 rank-1/2/3，只要除 batch 外的元素总数等于动作数 `M`。batch 为 1 或动态。 +`auto` 优先读取 `rmcs_model_type`，没有 metadata 时才按 rank-2 推断 MLP、rank-3 推断 +Transformer。真正需要多输入（例如独立 attention mask、position id）的模型需要新增专用 +adapter，当前部署接口会在启动时明确拒绝。 部署模型须含 `rmcs_obs_layout`、`rmcs_actions_layout`；建议带 `policy_layout_hash` 和版本。 `history_length × 单帧维数 = rl_obs_size`。归一化均值和标准差必须成对提供，标准差为正数。 +带历史帧的模型示例（桥和策略进程都要使用同一历史长度）： + +```yaml +rl_bridge: + ros__parameters: + history_length: 8 + rl_obs_size: 208 # 8 × 26 +policy_server: + ros__parameters: + model_type: "transformer" # 带历史帧 MLP 这里写 "mlp" + sequence_length: 8 # 动态 rank-3 输入时需要 + feature_size: 26 + rl_obs_size: 208 +``` + +模型盖章时可以把结构和序列维度写进 metadata，避免只靠 rank 猜测： + +```sh +python3 src/rmcs_rl/tool/stamp_layout_metadata.py \ + --model policy.onnx --from-config <车辆配置.yaml> --node rl_bridge \ + --model-type transformer --sequence-length 8 --feature-size 26 +``` + 新模型先核对训练的观测顺序、坐标、基准角、缩放和频率，再盖章： ```sh diff --git a/src/policy/onnx_runtime.cpp b/src/policy/onnx_runtime.cpp index 2ea9857..aac1431 100644 --- a/src/policy/onnx_runtime.cpp +++ b/src/policy/onnx_runtime.cpp @@ -1,22 +1,64 @@ #include "onnx_runtime.hpp" #include +#include +#include #include namespace rmcs_rl { +namespace { + +std::string lower(std::string value) { + std::transform(value.begin(), value.end(), value.begin(), [](unsigned char character) { + return static_cast(std::tolower(character)); + }); + return value; +} + +std::size_t parse_positive(const std::optional& value, const char* key) { + if (!value || value->empty()) + return 0; + std::size_t consumed = 0; + std::size_t result = 0; + try { + result = std::stoull(*value, &consumed); + } catch (const std::exception&) { + throw std::invalid_argument(std::string{key} + " metadata must be a positive integer"); + } + if (consumed != value->size() || result == 0) + throw std::invalid_argument(std::string{key} + " metadata must be a positive integer"); + return result; +} + +bool batch_dimension_ok(std::int64_t dimension) { + // ONNX uses -1 for a dynamic dimension. Symbolic dimensions are returned + // as -1 by the C++ API, so this also covers named batch dimensions. + return dimension == 1 || dimension == -1; +} + +} // namespace + +OnnxRuntime::OnnxRuntime(const Config& config) + : input_name_(config.input_name) + , output_name_(config.output_name) { + if (config.model_path.empty()) + throw std::invalid_argument("model path must not be empty"); + const auto requested_type = lower(config.model_type); + if (requested_type != "auto" && requested_type != "mlp" && requested_type != "transformer" + && requested_type != "generic") + throw std::invalid_argument( + "model_type must be auto, mlp, transformer, or generic (got '" + config.model_type + + "')"); -OnnxRuntime::OnnxRuntime( - const std::string& model_path, const std::string& input_name, const std::string& output_name) - : input_name_(input_name) - , output_name_(output_name) { Ort::SessionOptions options; options.SetGraphOptimizationLevel(GraphOptimizationLevel::ORT_ENABLE_ALL); options.SetIntraOpNumThreads(1); options.SetInterOpNumThreads(1); - session_ = Ort::Session{env_, model_path.c_str(), options}; + session_ = Ort::Session{env_, config.model_path.c_str(), options}; if (session_.GetInputCount() != 1 || session_.GetOutputCount() != 1) - throw std::invalid_argument("model must have exactly one input and one output"); + throw std::invalid_argument( + "model must have exactly one runtime input and one output; multi-input models need a future adapter"); const auto actual_input = session_.GetInputNameAllocated(0, allocator_); const auto actual_output = session_.GetOutputNameAllocated(0, allocator_); if (actual_input.get() != input_name_ || actual_output.get() != output_name_) @@ -24,6 +66,9 @@ OnnxRuntime::OnnxRuntime( "tensor names must be '" + input_name_ + "' / '" + output_name_ + "', got '" + actual_input.get() + "' / '" + actual_output.get() + "'"); + // Keep TypeInfo alive while reading the TensorTypeAndShapeInfo. The + // latter is a view into TypeInfo in ONNX Runtime; chaining a temporary + // here can read freed type metadata on some runtime builds. const auto input_type = session_.GetInputTypeInfo(0); const auto output_type = session_.GetOutputTypeInfo(0); const auto input_info = input_type.GetTensorTypeAndShapeInfo(); @@ -32,20 +77,128 @@ OnnxRuntime::OnnxRuntime( || output_info.GetElementType() != ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT) throw std::invalid_argument("tensor element type must be float32"); - const auto input_shape = input_info.GetShape(); - const auto output_shape = output_info.GetShape(); - if (input_shape.size() != 2 || output_shape.size() != 2) - throw std::invalid_argument("tensor rank must be 2 ([batch, N])"); - if ((input_shape[0] != 1 && input_shape[0] != -1) - || (output_shape[0] != 1 && output_shape[0] != -1)) - throw std::invalid_argument("batch dimension must be 1 or dynamic"); - if (input_shape[1] <= 0 || output_shape[1] <= 0) - throw std::invalid_argument("feature dimensions must be concrete positive values"); - - // The server evaluates one robot observation, even when the exported batch is dynamic. - input_shape_ = {1, input_shape[1]}; - input_buffer_.resize(static_cast(input_shape[1])); - output_size_ = static_cast(output_shape[1]); + const auto raw_input_shape = input_info.GetShape(); + const auto raw_output_shape = output_info.GetShape(); + if (raw_input_shape.empty() || raw_input_shape.size() > 3) + throw std::invalid_argument( + "supported policy input ranks are 1 ([N]), 2 ([batch,N]), and 3 ([batch,sequence,feature])"); + if (raw_input_shape.size() >= 2 && !batch_dimension_ok(raw_input_shape[0])) + throw std::invalid_argument("input batch dimension must be 1 or dynamic"); + if (raw_output_shape.empty() || raw_output_shape.size() > 3) + throw std::invalid_argument("supported policy output ranks are 1, 2, or 3"); + if (raw_output_shape.size() >= 2 && !batch_dimension_ok(raw_output_shape[0])) + throw std::invalid_argument("output batch dimension must be 1 or dynamic"); + + const auto metadata_type = lower(metadata("rmcs_model_type").value_or("")); + if (!metadata_type.empty() && metadata_type != "mlp" && metadata_type != "transformer" + && metadata_type != "generic") + throw std::invalid_argument("rmcs_model_type metadata must be mlp, transformer, or generic"); + if (requested_type != "auto" && requested_type != "generic" && !metadata_type.empty() + && requested_type != metadata_type) + throw std::invalid_argument( + "model_type parameter '" + requested_type + "' disagrees with rmcs_model_type='" + + metadata_type + "'"); + + std::string resolved_type = requested_type; + if (resolved_type == "auto") + resolved_type = metadata_type; + if (resolved_type.empty()) { + if (raw_input_shape.size() == 2) + resolved_type = "mlp"; + else if (raw_input_shape.size() == 3) + resolved_type = "transformer"; + else + resolved_type = "generic"; + } + if (resolved_type == "mlp" && raw_input_shape.size() != 2 && raw_input_shape.size() != 3) + throw std::invalid_argument( + "model_type=mlp requires input shape [batch,obs] or [batch,history,feature]"); + if (resolved_type == "transformer" && raw_input_shape.size() != 3) + throw std::invalid_argument( + "model_type=transformer requires input shape [batch,sequence,feature]"); + info_.model_type = resolved_type; + info_.input_rank = raw_input_shape.size(); + info_.output_rank = raw_output_shape.size(); + + const auto metadata_sequence = parse_positive(metadata("rmcs_history_length"), "rmcs_history_length"); + const auto metadata_feature = parse_positive(metadata("rmcs_obs_frame_size"), "rmcs_obs_frame_size"); + std::size_t sequence = config.sequence_length != 0 ? config.sequence_length : metadata_sequence; + std::size_t feature = config.feature_size != 0 ? config.feature_size : metadata_feature; + const auto expected_observation = config.observation_size; + + input_shape_.resize(raw_input_shape.size()); + if (raw_input_shape.size() == 1) { + const auto declared = raw_input_shape[0] > 0 ? static_cast(raw_input_shape[0]) : 0; + const auto resolved = declared != 0 ? declared : expected_observation; + if (resolved == 0) + throw std::invalid_argument("dynamic rank-1 input needs observation_size"); + if (declared != 0 && expected_observation != 0 && declared != expected_observation) + throw std::invalid_argument("model input size does not match observation_size"); + input_shape_[0] = static_cast(resolved); + info_.feature_size = resolved; + info_.sequence_length = 1; + } else if (raw_input_shape.size() == 2) { + const auto declared = raw_input_shape[1] > 0 ? static_cast(raw_input_shape[1]) : 0; + const auto resolved = declared != 0 ? declared : expected_observation; + if (resolved == 0) + throw std::invalid_argument("dynamic rank-2 input needs observation_size"); + if (declared != 0 && expected_observation != 0 && declared != expected_observation) + throw std::invalid_argument("model input feature size does not match observation_size"); + input_shape_ = {1, static_cast(resolved)}; + info_.feature_size = resolved; + info_.sequence_length = 1; + } else { + const auto declared_sequence = raw_input_shape[1] > 0 + ? static_cast(raw_input_shape[1]) + : 0; + const auto declared_feature = raw_input_shape[2] > 0 + ? static_cast(raw_input_shape[2]) + : 0; + if (sequence == 0) + sequence = declared_sequence; + if (feature == 0) + feature = declared_feature; + if (sequence == 0 && feature != 0 && expected_observation != 0 + && expected_observation % feature == 0) + sequence = expected_observation / feature; + if (feature == 0 && sequence != 0 && expected_observation != 0 + && expected_observation % sequence == 0) + feature = expected_observation / sequence; + if (sequence == 0 || feature == 0) + throw std::invalid_argument( + "rank-3 input needs concrete sequence/feature dimensions or sequence_length/feature_size"); + if ((declared_sequence != 0 && declared_sequence != sequence) + || (declared_feature != 0 && declared_feature != feature)) + throw std::invalid_argument("configured sequence/feature dimensions do not match model"); + if (expected_observation != 0 && sequence * feature != expected_observation) + throw std::invalid_argument("sequence_length * feature_size does not match observation_size"); + input_shape_ = {1, static_cast(sequence), static_cast(feature)}; + info_.sequence_length = sequence; + info_.feature_size = feature; + } + input_buffer_.resize( + std::accumulate(input_shape_.begin(), input_shape_.end(), std::size_t{1}, [](auto value, auto dim) { + return value * static_cast(dim); + })); + + std::size_t output_size = 1; + bool output_dynamic = false; + for (std::size_t index = raw_output_shape.size() >= 2 ? 1 : 0; index < raw_output_shape.size(); ++index) { + if (raw_output_shape[index] <= 0) + output_dynamic = true; + else + output_size *= static_cast(raw_output_shape[index]); + } + if (output_dynamic) { + if (config.action_size == 0) + throw std::invalid_argument("dynamic output needs action_size"); + output_size = config.action_size; + } else if (config.action_size != 0 && output_size != config.action_size) { + throw std::invalid_argument("model output size does not match action_size"); + } + if (output_size == 0) + throw std::invalid_argument("model output must contain at least one action"); + output_size_ = output_size; } std::optional OnnxRuntime::metadata(const char* key) const { diff --git a/src/policy/onnx_runtime.hpp b/src/policy/onnx_runtime.hpp index 791275e..2113cb5 100644 --- a/src/policy/onnx_runtime.hpp +++ b/src/policy/onnx_runtime.hpp @@ -1,6 +1,5 @@ #pragma once -#include #include #include #include @@ -14,12 +13,36 @@ namespace rmcs_rl { class OnnxRuntime { public: + struct Config { + std::string model_path; + std::string input_name = "obs"; + std::string output_name = "actions"; + std::string model_type = "auto"; + std::size_t sequence_length = 0; + std::size_t feature_size = 0; + std::size_t observation_size = 0; + std::size_t action_size = 0; + }; + + struct Info { + std::string model_type; + std::size_t input_rank = 0; + std::size_t output_rank = 0; + std::size_t sequence_length = 1; + std::size_t feature_size = 0; + }; + + explicit OnnxRuntime(const Config& config); + + // Kept for small external users of the old deployment API. OnnxRuntime( const std::string& model_path, const std::string& input_name, - const std::string& output_name); + const std::string& output_name) + : OnnxRuntime(Config{model_path, input_name, output_name}) {} [[nodiscard]] std::size_t input_size() const { return input_buffer_.size(); } [[nodiscard]] std::size_t output_size() const { return output_size_; } + [[nodiscard]] const Info& info() const { return info_; } [[nodiscard]] std::optional metadata(const char* key) const; void run(std::span input, std::span output); @@ -31,9 +54,10 @@ class OnnxRuntime { Ort::Session session_{nullptr}; std::string input_name_; std::string output_name_; - std::array input_shape_{}; + std::vector input_shape_; std::vector input_buffer_; std::size_t output_size_ = 0; + Info info_; }; } // namespace rmcs_rl diff --git a/src/policy/policy_model.cpp b/src/policy/policy_model.cpp index f950d14..535eb5f 100644 --- a/src/policy/policy_model.cpp +++ b/src/policy/policy_model.cpp @@ -45,10 +45,23 @@ std::optional clip_metadata(const OnnxRuntime& runtime, const char* key) } // namespace PolicyModel::PolicyModel(const Config& config) - : runtime_(config.path, config.input_name, config.output_name) { + : runtime_(OnnxRuntime::Config{ + config.path, + config.input_name, + config.output_name, + config.model_type, + config.sequence_length, + config.feature_size, + config.observation_size, + config.action_size}) { info_.path = config.path; info_.obs_size = runtime_.input_size(); info_.action_size = runtime_.output_size(); + info_.model_type = runtime_.info().model_type; + info_.input_rank = runtime_.info().input_rank; + info_.output_rank = runtime_.info().output_rank; + info_.sequence_length = runtime_.info().sequence_length; + info_.feature_size = runtime_.info().feature_size; std::string error; if (!model_id_of_file(config.path, info_.model_id, error)) throw std::runtime_error(error); diff --git a/src/policy/policy_model.hpp b/src/policy/policy_model.hpp index e12ccf7..e0a965c 100644 --- a/src/policy/policy_model.hpp +++ b/src/policy/policy_model.hpp @@ -17,6 +17,11 @@ class PolicyModel { std::string path; std::string input_name = "obs"; std::string output_name = "actions"; + std::string model_type = "auto"; + std::size_t sequence_length = 0; + std::size_t feature_size = 0; + std::size_t observation_size = 0; + std::size_t action_size = 0; bool normalization_from_metadata = true; std::optional obs_clip; std::optional action_clip; @@ -29,6 +34,11 @@ class PolicyModel { std::string version; std::size_t obs_size = 0; std::size_t action_size = 0; + std::string model_type; + std::size_t input_rank = 0; + std::size_t output_rank = 0; + std::size_t sequence_length = 1; + std::size_t feature_size = 0; std::uint64_t layout_hash = 0; std::uint64_t model_id = 0; }; diff --git a/src/policy_server.cpp b/src/policy_server.cpp index 6039c40..dc78992 100644 --- a/src/policy_server.cpp +++ b/src/policy_server.cpp @@ -39,6 +39,27 @@ class PolicyServer final : public rclcpp::Node { ament_index_cpp::get_package_share_directory("rmcs_rl") + "/" + config.path; config.input_name = string_or(*this, "input_name", "obs"); config.output_name = string_or(*this, "output_name", "actions"); + config.model_type = string_or(*this, "model_type", "auto"); + if (const auto value = integer_parameter(*this, "sequence_length"); value.has_value()) { + if (*value < 1) + throw std::invalid_argument("policy_server: sequence_length must be positive"); + config.sequence_length = static_cast(*value); + } + if (const auto value = integer_parameter(*this, "feature_size"); value.has_value()) { + if (*value < 1) + throw std::invalid_argument("policy_server: feature_size must be positive"); + config.feature_size = static_cast(*value); + } + if (const auto value = integer_parameter(*this, "rl_obs_size"); value.has_value()) { + if (*value < 1) + throw std::invalid_argument("policy_server: rl_obs_size must be positive"); + config.observation_size = static_cast(*value); + } + if (const auto value = integer_parameter(*this, "rl_action_size"); value.has_value()) { + if (*value < 1) + throw std::invalid_argument("policy_server: rl_action_size must be positive"); + config.action_size = static_cast(*value); + } config.normalization_from_metadata = bool_or(*this, "normalization_from_metadata", true); if (const double clip = number_or(*this, "obs_clip", -1.0); clip >= 0.0) config.obs_clip = clip; @@ -63,9 +84,10 @@ class PolicyServer final : public rclcpp::Node { const auto& info = model_->info(); RCLCPP_INFO(get_logger(), "policy loaded: %s", info.path.c_str()); RCLCPP_INFO( - get_logger(), "model_id=%s layout_hash=%s version=%s obs=%zu action=%zu", + get_logger(), "model_id=%s layout_hash=%s version=%s type=%s input_rank=%zu output_rank=%zu obs=%zu action=%zu", hex16(info.model_id).c_str(), hex16(info.layout_hash).c_str(), info.version.c_str(), - info.obs_size, info.action_size); + info.model_type.c_str(), info.input_rank, info.output_rank, info.obs_size, + info.action_size); RCLCPP_INFO(get_logger(), "obs signature: %s", info.obs_signature.c_str()); RCLCPP_INFO(get_logger(), "action signature: %s", info.actions_signature.c_str()); RCLCPP_INFO(get_logger(), "waiting for obs on %s/obs", rl_base.c_str()); diff --git a/test/gen_synthetic_policy.py b/test/gen_synthetic_policy.py index 0994648..f739ecf 100644 --- a/test/gen_synthetic_policy.py +++ b/test/gen_synthetic_policy.py @@ -8,18 +8,36 @@ import rl_layout as layout -def _export_with_onnx(obs: int, act: int, output: str) -> None: - """actions = obs @ W with zero weights; no training dependency.""" +def _export_with_onnx(obs: int, act: int, output: str, model_type: str, + sequence_length: int, feature_size: int) -> None: + """Export a zero-action MLP/sequence fixture without a training dependency.""" import numpy as np import onnx from onnx import TensorProto, helper, numpy_helper - weight = numpy_helper.from_array(np.zeros((obs, act), dtype=np.float32), name="W") - node = helper.make_node("MatMul", ["obs", "W"], ["actions"], name="zero_action") + if sequence_length > 1: + input_shape = [1, sequence_length, feature_size] + if model_type == "transformer": + node = helper.make_node( + "ReduceMean", ["obs"], ["pooled"], name="sequence_pool", axes=[1], keepdims=0) + weight_shape = (feature_size, act) + matmul_input = "pooled" + else: + node = helper.make_node("Flatten", ["obs"], ["flat"], name="flatten_history", axis=1) + weight_shape = (obs, act) + matmul_input = "flat" + else: + input_shape = [1, obs] + node = None + weight_shape = (obs, act) + matmul_input = "obs" + weight = numpy_helper.from_array(np.zeros(weight_shape, dtype=np.float32), name="W") + matmul = helper.make_node("MatMul", [matmul_input, "W"], ["actions"], name="zero_action") + nodes = [node, matmul] if node is not None else [matmul] graph = helper.make_graph( - [node], + nodes, "zero_policy", - [helper.make_tensor_value_info("obs", TensorProto.FLOAT, [1, obs])], + [helper.make_tensor_value_info("obs", TensorProto.FLOAT, input_shape)], [helper.make_tensor_value_info("actions", TensorProto.FLOAT, [1, act])], [weight], ) @@ -32,10 +50,16 @@ def _export_with_onnx(obs: int, act: int, output: str) -> None: def main() -> None: parser = argparse.ArgumentParser( - description="生成零动作合成策略 ONNX（obs float32[1,N] -> actions float32[1,M]）" + description="生成零动作合成策略 ONNX（支持 MLP/Transformer 序列输入）" ) parser.add_argument("--obs", type=int, default=None, help="observation size（缺省 22）") parser.add_argument("--act", type=int, default=None, help="action size（缺省 4）") + parser.add_argument("--model-type", choices=("mlp", "transformer", "generic"), default="mlp", + help="fixture 结构；MLP 可生成 rank-2 或 rank-3 输入") + parser.add_argument("--sequence-length", type=int, default=None, + help="序列长度；>1 时生成 rank-3 输入") + parser.add_argument("--feature-size", type=int, default=None, + help="单帧维度；缺省由 obs/sequence 推导") parser.add_argument("--from-config", "--config", dest="config", default=None, help="部署 YAML：由 observation_terms/action_terms 推导 obs/act 尺寸") parser.add_argument("--node", default=layout.DEFAULT_NODE, @@ -66,12 +90,18 @@ def main() -> None: print(f"ERROR: obs/act 必须为正整数（obs={obs} act={act}）", file=sys.stderr) sys.exit(1) - _export_with_onnx(obs, act, args.output) + sequence_length = args.sequence_length or 1 + if sequence_length < 1: + print("ERROR: sequence-length 必须 >= 1", file=sys.stderr) + sys.exit(1) + feature_size = args.feature_size or (obs // sequence_length if obs % sequence_length == 0 else 0) + if feature_size <= 0 or sequence_length * feature_size != obs: + print("ERROR: obs 必须能按 sequence-length 分解为正整数 feature-size", file=sys.stderr) + sys.exit(1) + _export_with_onnx(obs, act, args.output, args.model_type, sequence_length, feature_size) - print( - f"wrote {args.output}: obs float32[1,{obs}] -> actions float32[1,{act}] " - "(zero policy)" - ) + input_desc = f"[1,{obs}]" if sequence_length == 1 else f"[1,{sequence_length},{feature_size}]" + print(f"wrote {args.output}: obs float32{input_desc} -> actions float32[1,{act}] (zero policy)") if __name__ == "__main__": diff --git a/tool/check_policy_contract.py b/tool/check_policy_contract.py index c9dc793..a39546f 100644 --- a/tool/check_policy_contract.py +++ b/tool/check_policy_contract.py @@ -4,8 +4,8 @@ Two modes: * self-check (no --config; used by CI, deployment YAML lives in the RMCS repo): - model loads; one input "obs" / one output "actions"; float32; rank 2; - batch 1 or dynamic; concrete feature dimensions. Layout metadata is OPTIONAL: + model loads; one input "obs" / one output "actions"; float32; rank 1/2/3; + MLP uses rank 2 or rank 3 and Transformer uses rank 3. Layout metadata is OPTIONAL: - missing / v1 -> SKIP (stamped layout metadata is optional for model-only self-check) - present v2 -> signatures must be internally consistent with the tensor sizes, and policy_layout_hash must match those signatures @@ -132,8 +132,9 @@ def _check_normalization(report, meta, obs_size): report.check(key, math.isfinite(value) and value > 0.0, f"{key}={text}") -def _dummy_inference(report, model_path, obs_size, act_size): - """跑一次零输入推理，确认输出有限、形状正确（无 onnxruntime 则跳过）。""" +def _dummy_inference(report, model_path, obs_size, act_size, model_type, + input_rank, sequence_length, feature_size): + """跑一次零输入推理，确认输出有限、元素数正确（无 onnxruntime 则跳过）。""" try: import numpy as np import onnxruntime as ort @@ -142,16 +143,21 @@ def _dummy_inference(report, model_path, obs_size, act_size): return try: session = ort.InferenceSession(str(model_path), providers=["CPUExecutionProvider"]) - obs = np.zeros((1, obs_size), dtype=np.float32) + if input_rank == 3: + obs = np.zeros((1, sequence_length, feature_size), dtype=np.float32) + elif input_rank == 1: + obs = np.zeros((obs_size,), dtype=np.float32) + else: + obs = np.zeros((1, obs_size), dtype=np.float32) actions = session.run(["actions"], {"obs": obs})[0] except Exception as exc: report.check("dummy inference", False, f"{type(exc).__name__}: {exc}") return finite = bool(np.isfinite(actions).all()) - shape_ok = list(actions.shape) == [1, act_size] + shape_ok = int(np.prod(actions.shape, dtype=np.int64)) == act_size report.check( "dummy inference", finite and shape_ok, - f"actions{list(actions.shape)} finite={finite} " + f"actions{list(actions.shape)} elements={actions.size} finite={finite} " f"range=[{actions.min():.4f},{actions.max():.4f}]", ) @@ -171,6 +177,12 @@ def main() -> None: help="期望的观测尺寸（缺省取模型形状）") parser.add_argument("--act", type=int, default=None, help="期望的动作尺寸（缺省取模型形状）") + parser.add_argument("--model-type", choices=("auto", "mlp", "transformer", "generic"), + default="auto", help="模型结构（auto 按 metadata/输入 rank 推断）") + parser.add_argument("--sequence-length", type=int, default=None, + help="Transformer 序列长度（动态输入或无 YAML 时使用）") + parser.add_argument("--feature-size", type=int, default=None, + help="Transformer 单帧维度（动态输入或无 YAML 时使用）") parser.add_argument("--expect-model-id", default=None, help="可选：期望的 model_id（16 位 hex），用于部署对账") args = parser.parse_args() @@ -251,23 +263,80 @@ def _dtype_name(value_info): and out.type.tensor_type.elem_type == TensorProto.FLOAT, f"obs={_dtype_name(inp)} actions={_dtype_name(out)}") in_shape, out_shape = _shape_of(inp), _shape_of(out) - report.check("rank 2", len(in_shape) == 2 and len(out_shape) == 2, - f"obs={in_shape} actions={out_shape}") - if len(in_shape) != 2 or len(out_shape) != 2: - print("== SUMMARY: FAIL (秩不为 2，后续检查跳过) ==") + meta = {prop.key: prop.value for prop in model.metadata_props} + declared_type = meta.get("rmcs_model_type", "").strip().lower() + report.check("model_type metadata", declared_type in ("", "mlp", "transformer", "generic"), + f"rmcs_model_type={declared_type or ''}") + if declared_type and args.model_type not in ("auto", "generic"): + report.check("model_type parameter/metadata", args.model_type == declared_type, + f"parameter={args.model_type} metadata={declared_type}") + model_type = declared_type if args.model_type == "auto" and declared_type else args.model_type + if model_type == "auto": + model_type = {1: "generic", 2: "mlp", 3: "transformer"}.get(len(in_shape), "generic") + rank_ok = ((model_type == "mlp" and len(in_shape) in (2, 3)) + or (model_type == "transformer" and len(in_shape) == 3) + or (model_type == "generic" and 1 <= len(in_shape) <= 3)) + report.check("input rank/model type", rank_ok, + f"model_type={model_type} obs_rank={len(in_shape)} actions_rank={len(out_shape)}") + if not rank_ok: + print("== SUMMARY: FAIL (输入 rank 与模型结构不匹配，后续检查跳过) ==") sys.exit(1) - batch_ok = all( - dim == 1 or dim is None or isinstance(dim, str) - for dim in (in_shape[0], out_shape[0]) - ) + batch_ok = all(dim == 1 or dim is None or isinstance(dim, str) + for dim in ((in_shape[0],) if len(in_shape) >= 2 else ())) + if len(out_shape) >= 2: + batch_ok = batch_ok and (out_shape[0] == 1 or out_shape[0] is None + or isinstance(out_shape[0], str)) report.check("batch dimension", batch_ok, - f"obs={in_shape[0]!r} actions={out_shape[0]!r}（允许 1 或动态维）") - model_obs, model_act = in_shape[1], out_shape[1] - if not isinstance(model_obs, int) or not isinstance(model_act, int) \ - or model_obs <= 0 or model_act <= 0: - report.check("concrete obs/action feature size", False, - f"obs={in_shape} actions={out_shape}（特征维必须是正整数）") + f"obs={in_shape[0] if len(in_shape) >= 2 else ''!r} " + f"actions={out_shape[0] if len(out_shape) >= 2 else ''!r}（允许 1 或动态维）") + + history_length = layout.history_length(args.config, args.node) if args.config else 1 + metadata_sequence = metadata_feature = 0 + for key in ("rmcs_history_length", "rmcs_obs_frame_size"): + text = meta.get(key) + if text is None: + continue + try: + value = int(text) + except ValueError: + report.check(key, False, f"{key}={text!r} 不是正整数") + continue + report.check(key, value > 0, f"{key}={value}") + if key == "rmcs_history_length": + metadata_sequence = value + else: + metadata_feature = value + config_feature_size = obs_size // history_length if obs_size is not None else None + input_tail = in_shape[0:] if len(in_shape) == 1 else in_shape[1:] + sequence_length = args.sequence_length or metadata_sequence or ( + history_length if len(in_shape) == 3 else 1) + feature_size = args.feature_size or metadata_feature or ( + config_feature_size if len(in_shape) == 3 else None) + if len(in_shape) == 3: + declared_sequence, declared_feature = input_tail + if isinstance(declared_sequence, int) and declared_sequence > 0: + sequence_length = declared_sequence + if isinstance(declared_feature, int) and declared_feature > 0: + feature_size = declared_feature + model_obs = sequence_length * feature_size if sequence_length and feature_size else None + else: + model_obs = input_tail[0] if len(input_tail) == 1 else None + output_tail = out_shape[0:] if len(out_shape) == 1 else out_shape[1:] + model_act = 1 + dynamic_output = False + for dim in output_tail: + if isinstance(dim, int) and dim > 0: + model_act *= dim + else: + dynamic_output = True + if dynamic_output: + model_act = act_size + concrete_ok = (isinstance(model_obs, int) and model_obs > 0 + and isinstance(model_act, int) and model_act > 0) + report.check("concrete obs/action size", concrete_ok, + f"obs={model_obs} actions={model_act} shape obs={in_shape} actions={out_shape}") + if not concrete_ok: print(f"== SUMMARY: {'PASS' if report.ok else 'FAIL'} ==") sys.exit(0 if report.ok else 1) @@ -279,11 +348,10 @@ def _dtype_name(value_info): report.info("model sizes", f"obs={model_obs} actions={model_act}（取自模型）") report.check("obs feature shape", model_obs == obs_size, - f"{in_shape} feature={model_obs} expected={obs_size}") + f"{in_shape} flattened={model_obs} expected={obs_size}") report.check("actions feature shape", model_act == act_size, - f"{out_shape} feature={model_act} expected={act_size}") + f"{out_shape} flattened={model_act} expected={act_size}") - meta = {prop.key: prop.value for prop in model.metadata_props} obs_meta, act_meta = meta.get("rmcs_obs_layout"), meta.get("rmcs_actions_layout") version_line = meta.get("policy_version") if version_line: @@ -362,7 +430,8 @@ def _dtype_name(value_info): else f"模型={declared_hash!r} 期望={layout.hex16(digest)}") _check_normalization(report, meta, obs_size) - _dummy_inference(report, args.model, obs_size, act_size) + _dummy_inference(report, args.model, obs_size, act_size, model_type, len(in_shape), + sequence_length, feature_size or obs_size) try: file_id = layout.model_id(args.model) diff --git a/tool/rl_layout.py b/tool/rl_layout.py index a67a222..f0f38d5 100644 --- a/tool/rl_layout.py +++ b/tool/rl_layout.py @@ -757,7 +757,10 @@ def write_metadata(model_path, updates: Dict[str, object]) -> None: def stamp_metadata(model_path, obs_sig: str, act_sig: str, obs_size: int, act_size: int, policy_version: Optional[str] = None, obs_mean=None, obs_std=None, - obs_clip=None, action_clip=None) -> Dict[str, str]: + obs_clip=None, action_clip=None, + model_type: Optional[str] = None, + sequence_length: Optional[int] = None, + feature_size: Optional[int] = None) -> Dict[str, str]: """按规范串盖章：返回实际写入的 metadata（含 policy_layout_hash）。""" updates = { "rmcs_obs_layout": obs_sig, @@ -774,6 +777,12 @@ def stamp_metadata(model_path, obs_sig: str, act_sig: str, obs_size: int, act_si updates["rmcs_obs_clip"] = format_scale(obs_clip) if action_clip is not None: updates["rmcs_action_clip"] = format_scale(action_clip) + if model_type: + updates["rmcs_model_type"] = str(model_type).lower() + if sequence_length is not None: + updates["rmcs_history_length"] = str(int(sequence_length)) + if feature_size is not None: + updates["rmcs_obs_frame_size"] = str(int(feature_size)) write_metadata(model_path, updates) return updates diff --git a/tool/stamp_layout_metadata.py b/tool/stamp_layout_metadata.py index b67346e..eaea382 100644 --- a/tool/stamp_layout_metadata.py +++ b/tool/stamp_layout_metadata.py @@ -14,6 +14,9 @@ rmcs_obs_mean/std 可选（--obs-mean/--obs-std，长度必须 == rl_obs_size） rmcs_obs_clip 可选单浮点（--obs-clip） rmcs_action_clip 可选单浮点（--action-clip） + rmcs_model_type 可选结构标识 mlp/transformer/generic（--model-type） + rmcs_history_length 可选序列长度（Transformer 或带历史帧 MLP） + rmcs_obs_frame_size 可选单帧维度 用法： python3 stamp_layout_metadata.py --model policy.onnx --from-config deploy.yaml @@ -63,6 +66,12 @@ def main() -> None: parser.add_argument("--obs-std", default=None, help="经验标准差，逗号分隔，长度同 obs_size") parser.add_argument("--obs-clip", type=float, default=None, help="观测 clip（单浮点，可选）") parser.add_argument("--action-clip", type=float, default=None, help="动作 clip（单浮点，可选）") + parser.add_argument("--model-type", choices=("mlp", "transformer", "generic"), default=None, + help="模型结构标识；不填则由部署端按输入 rank 推断") + parser.add_argument("--sequence-length", type=int, default=None, + help="序列长度（缺省从 YAML history_length 取值）") + parser.add_argument("--feature-size", type=int, default=None, + help="单帧观测维度（缺省由 rl_obs_size/history_length 推导）") args = parser.parse_args() try: @@ -81,12 +90,31 @@ def main() -> None: if value is not None and (not math.isfinite(value) or value <= 0.0): raise layout.LayoutError(f"{option}={value!r} 必须是有限正数") + history_length = layout.history_length(args.config, args.node) + sequence_length = args.sequence_length if args.sequence_length is not None else ( + history_length if args.model_type in ("mlp", "transformer") else None) + feature_size = args.feature_size if args.feature_size is not None else ( + obs_size // history_length if args.model_type in ("mlp", "transformer") else None) + if feature_size is None and sequence_length is not None and obs_size % sequence_length == 0: + feature_size = obs_size // sequence_length + if sequence_length is not None and sequence_length < 1: + raise layout.LayoutError("--sequence-length 必须 >= 1") + if feature_size is not None and feature_size < 1: + raise layout.LayoutError("--feature-size 必须 >= 1") + if sequence_length is not None and feature_size is None: + raise layout.LayoutError("给出 --sequence-length 时必须能推导或指定 --feature-size") + if sequence_length is not None and sequence_length * feature_size != obs_size: + raise layout.LayoutError( + f"sequence_length * feature_size={sequence_length * feature_size} != rl_obs_size={obs_size}") + before = layout.read_metadata(args.model) updates = layout.stamp_metadata( args.model, obs_sig, act_sig, obs_size, act_size, policy_version=args.policy_version, obs_mean=obs_mean, obs_std=obs_std, obs_clip=args.obs_clip, action_clip=args.action_clip, + model_type=args.model_type, sequence_length=sequence_length, + feature_size=feature_size, ) except layout.LayoutError as exc: print(f"ERROR: {exc}", file=sys.stderr) diff --git a/tool/stamp_model.sh b/tool/stamp_model.sh index 84348fa..fc9b392 100755 --- a/tool/stamp_model.sh +++ b/tool/stamp_model.sh @@ -5,6 +5,7 @@ # 用法: # stamp_model.sh [--version X] [--config ] [--node rl_bridge] # [--obs-mean a,b,... --obs-std a,b,...] [--obs-clip V] [--action-clip V] +# [--model-type mlp|transformer|generic] [--sequence-length N --feature-size N] # # 例: # stamp_model.sh wheel_leg_v3.onnx --version 3.0 @@ -59,7 +60,8 @@ while [[ $# -gt 0 ]]; do NODE="${2:?--node 需要值}" shift 2 ;; - --obs-mean | --obs-std | --obs-clip | --action-clip) + --obs-mean | --obs-std | --obs-clip | --action-clip \ + | --model-type | --sequence-length | --feature-size) EXTRA+=("$1" "${2:?$1 需要值}") shift 2 ;; From cdabd565239cbe2af7f3051f74281c78e7e9daf4 Mon Sep 17 00:00:00 2001 From: ZGZ713912 Date: Tue, 29 Sep 2026 23:28:17 +0800 Subject: [PATCH 5/9] feat(policy): add support for extra input constants --- CMakeLists.txt | 5 +- README.md | 31 +++++- src/policy/onnx_runtime.cpp | 153 +++++++++++++++++++++++++--- src/policy/onnx_runtime.hpp | 14 +++ src/policy/policy_model.cpp | 3 +- src/policy/policy_model.hpp | 3 + src/policy_server.cpp | 33 ++++++ test/data/extra_input_identity.onnx | Bin 0 -> 281 bytes test/data/seq_history_mismatch.onnx | Bin 0 -> 463 bytes test/data/seq_identity.onnx | Bin 0 -> 463 bytes test/gen_extra_input_fixture.py | 50 +++++++++ test/gen_seq_fixtures.py | 77 ++++++++++++++ test/gen_synthetic_policy.py | 54 +++++++++- test/runtime_test.cpp | 65 ++++++++++++ test/test_layout_contract.sh | 97 ++++++++++++++++++ tool/check_policy_contract.py | 142 ++++++++++++++++++++++---- tool/stamp_layout_metadata.py | 25 ++--- 17 files changed, 691 insertions(+), 61 deletions(-) create mode 100644 test/data/extra_input_identity.onnx create mode 100644 test/data/seq_history_mismatch.onnx create mode 100644 test/data/seq_identity.onnx create mode 100644 test/gen_extra_input_fixture.py create mode 100644 test/gen_seq_fixtures.py diff --git a/CMakeLists.txt b/CMakeLists.txt index 99a7d15..11f9629 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -97,7 +97,10 @@ if(BUILD_TESTING) target_include_directories(runtime_test PRIVATE src ${ONNXRUNTIME_ROOT_DIR}/include) target_link_libraries(runtime_test rmcs_rl_bridge ${ONNXRUNTIME_ROOT_DIR}/lib/libonnxruntime.so) target_compile_definitions(runtime_test PRIVATE - RMCS_RL_IDENTITY_FIXTURE="${PROJECT_SOURCE_DIR}/test/data/normalized_identity.onnx") + RMCS_RL_IDENTITY_FIXTURE="${PROJECT_SOURCE_DIR}/test/data/normalized_identity.onnx" + RMCS_RL_SEQ_FIXTURE="${PROJECT_SOURCE_DIR}/test/data/seq_identity.onnx" + RMCS_RL_SEQ_MISMATCH_FIXTURE="${PROJECT_SOURCE_DIR}/test/data/seq_history_mismatch.onnx" + RMCS_RL_EXTRA_FIXTURE="${PROJECT_SOURCE_DIR}/test/data/extra_input_identity.onnx") endif() ament_export_dependencies(rosidl_default_runtime) diff --git a/README.md b/README.md index dd757c5..703179b 100644 --- a/README.md +++ b/README.md @@ -60,11 +60,28 @@ ros2 run rmcs_rl policy_server --ros-args --params-file <车辆配置.yaml> 输出支持 rank-1/2/3，只要除 batch 外的元素总数等于动作数 `M`。batch 为 1 或动态。 `auto` 优先读取 `rmcs_model_type`，没有 metadata 时才按 rank-2 推断 MLP、rank-3 推断 -Transformer。真正需要多输入（例如独立 attention mask、position id）的模型需要新增专用 -adapter，当前部署接口会在启动时明确拒绝。 +Transformer。 + +多输入模型（例如独立 attention mask）除 `obs` 外的输入必须是常量张量，在 +`policy_server` 段用 `extra_inputs.<输入名>: [元素列表]` 声明；启动时校验名字对齐、 +元素数量与形状一致、数值有限，缺声明或声明了模型没有的输入都会拒绝； +输出仍必须是唯一的 `actions`。 + +```yaml +policy_server: + ros__parameters: + extra_inputs: + attn_mask: [1, 1, 1, 1] # 展平常量，长度 = 模型该输入非 batch 维元素数 +``` + 部署模型须含 `rmcs_obs_layout`、`rmcs_actions_layout`；建议带 `policy_layout_hash` 和版本。 `history_length × 单帧维数 = rl_obs_size`。归一化均值和标准差必须成对提供，标准差为正数。 +rank-3 模型的序列切分受强制约束：模型的 `T == history_length`、`F == 单帧维数`。 +盖章默认把 `rmcs_history_length`、`rmcs_obs_frame_size` 从 YAML 写入 metadata； +契约工具与 policy_server 启动时按 `--sequence-length/rmcs_history_length/history_length` +（参数 > metadata > 模型声明）逐级等值校验，任一级不符即拒绝。 + 带历史帧的模型示例（桥和策略进程都要使用同一历史长度）： ```yaml @@ -80,12 +97,13 @@ policy_server: rl_obs_size: 208 ``` -模型盖章时可以把结构和序列维度写进 metadata，避免只靠 rank 猜测： +盖章默认写入序列键（`rmcs_history_length`/`rmcs_obs_frame_size`，取自 YAML）； +`rmcs_model_type` 可选，缺省由部署端按输入 rank 推断： ```sh python3 src/rmcs_rl/tool/stamp_layout_metadata.py \ --model policy.onnx --from-config <车辆配置.yaml> --node rl_bridge \ - --model-type transformer --sequence-length 8 --feature-size 26 + --model-type transformer ``` 新模型先核对训练的观测顺序、坐标、基准角、缩放和频率，再盖章： @@ -127,5 +145,8 @@ colcon test --merge-install --packages-select rmcs_rl rmcs_core PYTHON=<带 onnx、onnxruntime、PyYAML 的 Python> bash src/rmcs_rl/test/test_layout_contract.sh ``` -C++ 回归覆盖推理归一化、历史帧与跨线程动作快照；Python 回归覆盖布局解析、盖章及错误契约拒绝。 +C++ 回归覆盖推理归一化、历史帧、rank-3 序列输入、extra_inputs 常量喂入与错配拒绝、 +跨线程动作快照；Python 回归覆盖布局解析、盖章、T==history 强制、model_type/rank 匹配、 +多输入声明对账及错误契约拒绝。夹具由 `test/gen_seq_fixtures.py`、 +`test/gen_extra_input_fixture.py` 确定性生成后提交。 车辆包保留 DM 使能、帧解码、闭链几何、Body IMU 以及 MuJoCo 查看器回归。 diff --git a/src/policy/onnx_runtime.cpp b/src/policy/onnx_runtime.cpp index aac1431..8fbff25 100644 --- a/src/policy/onnx_runtime.cpp +++ b/src/policy/onnx_runtime.cpp @@ -2,6 +2,7 @@ #include #include +#include #include #include @@ -56,25 +57,51 @@ OnnxRuntime::OnnxRuntime(const Config& config) options.SetInterOpNumThreads(1); session_ = Ort::Session{env_, config.model_path.c_str(), options}; - if (session_.GetInputCount() != 1 || session_.GetOutputCount() != 1) + if (session_.GetOutputCount() != 1) + throw std::invalid_argument("model must have exactly one output"); + const std::size_t input_count = session_.GetInputCount(); + if (input_count == 0) + throw std::invalid_argument("model must have at least one input"); + + input_names_.reserve(input_count); + std::size_t primary_index = input_count; // sentinel: not found + for (std::size_t index = 0; index < input_count; ++index) { + const auto actual_input = session_.GetInputNameAllocated(index, allocator_); + input_names_.emplace_back(actual_input.get()); + if (input_names_.back() == input_name_) + primary_index = index; + } + if (primary_index == input_count) { + std::string listing; + for (std::size_t index = 0; index < input_count; ++index) + listing += (index == 0 ? "" : ", ") + input_names_[index]; throw std::invalid_argument( - "model must have exactly one runtime input and one output; multi-input models need a future adapter"); - const auto actual_input = session_.GetInputNameAllocated(0, allocator_); + "primary input '" + input_name_ + "' not found; model inputs: [" + listing + "]"); + } const auto actual_output = session_.GetOutputNameAllocated(0, allocator_); - if (actual_input.get() != input_name_ || actual_output.get() != output_name_) + if (actual_output.get() != output_name_) throw std::invalid_argument( - "tensor names must be '" + input_name_ + "' / '" + output_name_ + "', got '" - + actual_input.get() + "' / '" + actual_output.get() + "'"); + "output tensor must be named '" + output_name_ + "', got '" + actual_output.get() + + "'"); + for (std::size_t index = 0; index < input_count; ++index) { + const auto input_type = session_.GetInputTypeInfo(index); + if (input_type.GetONNXType() != ONNX_TYPE_TENSOR) + throw std::invalid_argument( + "input '" + input_names_[index] + "' must be a tensor"); + const auto input_info = input_type.GetTensorTypeAndShapeInfo(); + if (input_info.GetElementType() != ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT) + throw std::invalid_argument( + "input '" + input_names_[index] + "' element type must be float32"); + } // Keep TypeInfo alive while reading the TensorTypeAndShapeInfo. The // latter is a view into TypeInfo in ONNX Runtime; chaining a temporary // here can read freed type metadata on some runtime builds. - const auto input_type = session_.GetInputTypeInfo(0); + const auto input_type = session_.GetInputTypeInfo(primary_index); const auto output_type = session_.GetOutputTypeInfo(0); const auto input_info = input_type.GetTensorTypeAndShapeInfo(); const auto output_info = output_type.GetTensorTypeAndShapeInfo(); - if (input_info.GetElementType() != ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT - || output_info.GetElementType() != ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT) + if (output_info.GetElementType() != ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT) throw std::invalid_argument("tensor element type must be float32"); const auto raw_input_shape = input_info.GetShape(); @@ -169,7 +196,12 @@ OnnxRuntime::OnnxRuntime(const Config& config) "rank-3 input needs concrete sequence/feature dimensions or sequence_length/feature_size"); if ((declared_sequence != 0 && declared_sequence != sequence) || (declared_feature != 0 && declared_feature != feature)) - throw std::invalid_argument("configured sequence/feature dimensions do not match model"); + throw std::invalid_argument( + "model input dims (T=" + std::to_string(declared_sequence) + + ", F=" + std::to_string(declared_feature) + ") do not match expected (T=" + + std::to_string(sequence) + ", F=" + std::to_string(feature) + + ") from sequence_length/feature_size or rmcs_history_length/rmcs_obs_frame_size " + "(model sequence must equal bridge history_length)"); if (expected_observation != 0 && sequence * feature != expected_observation) throw std::invalid_argument("sequence_length * feature_size does not match observation_size"); input_shape_ = {1, static_cast(sequence), static_cast(feature)}; @@ -181,6 +213,79 @@ OnnxRuntime::OnnxRuntime(const Config& config) return value * static_cast(dim); })); + // Extra (non-obs) inputs: every one needs a constant from extra_inputs.*, + // and every declared constant must match a model input. + std::map> remaining = config.extra_input_values; + constant_slot_.assign(input_count, -1); + for (std::size_t index = 0; index < input_count; ++index) { + if (index == primary_index) + continue; + const auto found = remaining.find(input_names_[index]); + if (found == remaining.end()) + throw std::invalid_argument( + "model input '" + input_names_[index] + + "' has no constant value; declare it under policy_server extra_inputs." + " in the vehicle YAML"); + const std::vector source = found->second; + remaining.erase(found); + + const auto extra_type = session_.GetInputTypeInfo(index); + if (extra_type.GetONNXType() != ONNX_TYPE_TENSOR) + throw std::invalid_argument( + "extra input '" + input_names_[index] + "' must be a tensor"); + const auto extra_info = extra_type.GetTensorTypeAndShapeInfo(); + if (extra_info.GetElementType() != ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT) + throw std::invalid_argument( + "extra input '" + input_names_[index] + "' element type must be float32"); + const auto raw_shape = extra_info.GetShape(); + if (raw_shape.empty() || raw_shape.size() > 3) + throw std::invalid_argument( + "extra input '" + input_names_[index] + "' rank must be 1, 2, or 3"); + + ConstantInput constant; + constant.name = input_names_[index]; + std::size_t elements = 1; + std::size_t first_dim = 0; + if (raw_shape.size() >= 2) { + if (!batch_dimension_ok(raw_shape[0])) + throw std::invalid_argument( + "extra input '" + constant.name + "' batch dimension must be 1 or dynamic"); + constant.shape.push_back(1); + first_dim = 1; + } + for (std::size_t dim = first_dim; dim < raw_shape.size(); ++dim) { + if (raw_shape[dim] <= 0) + throw std::invalid_argument( + "extra input '" + constant.name + + "' non-batch dimensions must be concrete (dynamic dim " + + std::to_string(dim) + ")"); + constant.shape.push_back(raw_shape[dim]); + elements *= static_cast(raw_shape[dim]); + } + if (source.size() != elements) + throw std::invalid_argument( + "extra input '" + constant.name + "' needs " + std::to_string(elements) + + " values, got " + std::to_string(source.size())); + constant.values.reserve(elements); + for (const double value : source) { + if (!std::isfinite(value)) + throw std::invalid_argument( + "extra input '" + constant.name + "' contains a non-finite value"); + constant.values.push_back(static_cast(value)); + } + constant_slot_[index] = static_cast(constants_.size()); + constants_.push_back(std::move(constant)); + } + if (!remaining.empty()) { + std::string listing; + for (const auto& [name, values] : remaining) { + static_cast(values); + listing += (listing.empty() ? "" : ", ") + name; + } + throw std::invalid_argument( + "extra_inputs entry(s) [" + listing + "] have no matching model input"); + } + std::size_t output_size = 1; bool output_dynamic = false; for (std::size_t index = raw_output_shape.size() >= 2 ? 1 : 0; index < raw_output_shape.size(); ++index) { @@ -213,13 +318,29 @@ void OnnxRuntime::run(std::span input, std::span output) { if (input.size() != input_size() || output.size() != output_size()) throw std::invalid_argument("inference buffers do not match model dimensions"); std::copy(input.begin(), input.end(), input_buffer_.begin()); - auto tensor = Ort::Value::CreateTensor( - memory_info_, input_buffer_.data(), input_buffer_.size(), input_shape_.data(), - input_shape_.size()); - const char* input_names[] = {input_name_.c_str()}; + + const std::size_t input_count = input_names_.size(); + std::vector input_names; + input_names.reserve(input_count); + std::vector input_tensors; + input_tensors.reserve(input_count); + for (std::size_t index = 0; index < input_count; ++index) { + input_names.push_back(input_names_[index].c_str()); + if (constant_slot_[index] < 0) { + input_tensors.push_back(Ort::Value::CreateTensor( + memory_info_, input_buffer_.data(), input_buffer_.size(), input_shape_.data(), + input_shape_.size())); + } else { + auto& constant = constants_[static_cast(constant_slot_[index])]; + input_tensors.push_back(Ort::Value::CreateTensor( + memory_info_, constant.values.data(), constant.values.size(), constant.shape.data(), + constant.shape.size())); + } + } const char* output_names[] = {output_name_.c_str()}; - const auto outputs = - session_.Run(Ort::RunOptions{nullptr}, input_names, &tensor, 1, output_names, 1); + const auto outputs = session_.Run( + Ort::RunOptions{nullptr}, input_names.data(), input_tensors.data(), input_count, + output_names, 1); if (outputs.size() != 1 || !outputs[0].IsTensor() || outputs[0].GetTensorTypeAndShapeInfo().GetElementCount() != output_size()) throw std::runtime_error("inference output does not match model dimensions"); diff --git a/src/policy/onnx_runtime.hpp b/src/policy/onnx_runtime.hpp index 2113cb5..4f3cc8d 100644 --- a/src/policy/onnx_runtime.hpp +++ b/src/policy/onnx_runtime.hpp @@ -2,6 +2,7 @@ #include #include +#include #include #include #include @@ -22,6 +23,9 @@ class OnnxRuntime { std::size_t feature_size = 0; std::size_t observation_size = 0; std::size_t action_size = 0; + // 额外输入张量的常量值（键 = 模型输入名，值 = 展平的元素）， + // 由 policy_server 的 extra_inputs. YAML 参数提供。 + std::map> extra_input_values; }; struct Info { @@ -48,12 +52,22 @@ class OnnxRuntime { void run(std::span input, std::span output); private: + struct ConstantInput { + std::string name; + std::vector shape; + std::vector values; + }; + Ort::Env env_{ORT_LOGGING_LEVEL_WARNING, "rmcs_rl"}; Ort::AllocatorWithDefaultOptions allocator_; Ort::MemoryInfo memory_info_{Ort::MemoryInfo::CreateCpu(OrtArenaAllocator, OrtMemTypeDefault)}; Ort::Session session_{nullptr}; std::string input_name_; std::string output_name_; + std::vector input_names_; // 会话输入顺序 + std::vector constants_; + // 与 input_names_ 并行：主输入为 -1，其余为 constants_ 下标 + std::vector constant_slot_; std::vector input_shape_; std::vector input_buffer_; std::size_t output_size_ = 0; diff --git a/src/policy/policy_model.cpp b/src/policy/policy_model.cpp index 535eb5f..8a6f548 100644 --- a/src/policy/policy_model.cpp +++ b/src/policy/policy_model.cpp @@ -53,7 +53,8 @@ PolicyModel::PolicyModel(const Config& config) config.sequence_length, config.feature_size, config.observation_size, - config.action_size}) { + config.action_size, + config.extra_input_values}) { info_.path = config.path; info_.obs_size = runtime_.input_size(); info_.action_size = runtime_.output_size(); diff --git a/src/policy/policy_model.hpp b/src/policy/policy_model.hpp index e0a965c..552f681 100644 --- a/src/policy/policy_model.hpp +++ b/src/policy/policy_model.hpp @@ -2,6 +2,7 @@ #include #include +#include #include #include #include @@ -25,6 +26,8 @@ class PolicyModel { bool normalization_from_metadata = true; std::optional obs_clip; std::optional action_clip; + // 键 = 额外输入张量名，值 = 展平常量（来自 policy_server extra_inputs.） + std::map> extra_input_values; }; struct Info { diff --git a/src/policy_server.cpp b/src/policy_server.cpp index dc78992..071c792 100644 --- a/src/policy_server.cpp +++ b/src/policy_server.cpp @@ -1,13 +1,16 @@ #include #include #include +#include #include #include #include #include +#include #include #include #include +#include #include #include @@ -60,6 +63,36 @@ class PolicyServer final : public rclcpp::Node { throw std::invalid_argument("policy_server: rl_action_size must be positive"); config.action_size = static_cast(*value); } + for (const auto& parameter_name : list_parameters({"extra_inputs"}, 1).names) { + static constexpr std::string_view kPrefix = "extra_inputs."; + if (!parameter_name.starts_with(kPrefix)) + continue; + const auto extra_name = parameter_name.substr(kPrefix.size()); + if (extra_name.empty()) + throw std::invalid_argument( + "policy_server: extra_inputs entry must be extra_inputs."); + const auto parameter = get_parameter(parameter_name); + std::vector values; + switch (parameter.get_type()) { + case rclcpp::ParameterType::PARAMETER_DOUBLE_ARRAY: + values = parameter.as_double_array(); + break; + case rclcpp::ParameterType::PARAMETER_INTEGER_ARRAY: + for (const auto item : parameter.as_integer_array()) + values.push_back(static_cast(item)); + break; + default: + throw std::invalid_argument( + "policy_server: " + parameter_name + " must be a numeric list"); + } + if (values.empty()) + throw std::invalid_argument("policy_server: " + parameter_name + " is empty"); + for (const double value : values) + if (!std::isfinite(value)) + throw std::invalid_argument( + "policy_server: " + parameter_name + " contains a non-finite value"); + config.extra_input_values.emplace(extra_name, std::move(values)); + } config.normalization_from_metadata = bool_or(*this, "normalization_from_metadata", true); if (const double clip = number_or(*this, "obs_clip", -1.0); clip >= 0.0) config.obs_clip = clip; diff --git a/test/data/extra_input_identity.onnx b/test/data/extra_input_identity.onnx new file mode 100644 index 0000000000000000000000000000000000000000..9289bb740b645fbe580b8872cfa06de651f200ba GIT binary patch literal 281 zcmZvX%?g4*6ooVUkxNlcyP|?zw1~=VCj`}Fv>C=xYrveCxk`c$(&HBPLyNZOp6}dq zEQ?Ikg=?zf)hSG9ctgdgNUkZ;NZc@0p?5c62B!2iG-MR%5J{796f)5RU_n4%;?&#+ z0U^HuR~ZYQ9|t8&`p~ls(uO9f`waORs#f(l`eyz)8~zwRum0kP8dSPHwS-Q&;aQQ! uESD*gVYXSEg+{6J?YiL4uE-MfoVl}el@0yU|6cK7TA5qej>ign?fDO=g-`7O literal 0 HcmV?d00001 diff --git a/test/data/seq_history_mismatch.onnx b/test/data/seq_history_mismatch.onnx new file mode 100644 index 0000000000000000000000000000000000000000..423b0afe410d56a3cd066aef271be2fff36a22db GIT binary patch literal 463 zcmZutL2JS=6mG23^2(TvjEOK0df0Gm>-1I_4i94tJnbOt64EZ!LfW__6+3$Hr|fs` zw5oMDFd+|K-uJ!teb2IROU8jBlHbo*LKOQXVYJezWXk(Na0jOF6|RPy>bAX!dWY)P zpLa>$hALe}s)fE$1+HKV1vJHV8t6zQs%@(@Ci6&XA+v66LiHr&7&em@f=5Btf3s?q z*+647eSI;E^~m^lj^)Sx4oU0LduONo0?sXj9jN0IpXy)^6{}J_)9=7uAZ~(FU``J) z=C}$*!;vnWZP!yQfpD6MRO8F#@V0dGILL#-p{9xU+?(P)4dpd7w~W&Lp5-hDdC&D| z-h1%;yf^Ry*(rO+;)8LbvjxMpmNZeJkTH|8Rd(9U4ke8lQPCH}X!uttWf0DinVuJw EUx4Fx(EtDd literal 0 HcmV?d00001 diff --git a/test/data/seq_identity.onnx b/test/data/seq_identity.onnx new file mode 100644 index 0000000000000000000000000000000000000000..31c723d9fbd86fcac7bc0c7c55ec8bdf4795c0a6 GIT binary patch literal 463 zcmZutL2JS=6mG23^2(TvjEOK0df0GmbM;mj4i94tJnbOt64EZ!LfW__6+3$Hr|fs` zw5oMDFd>2W-uJ!teb2IROU8jBlHbo*LKOQXVYJezWXk(Na0jOF6|RPy>bAZ4^$yjo zKktIR4OO~|R11Bh3S7Y!3TTS!G|-VqRNGc*Oy-f<26Cgz8DkF>EF+1doEO|7O)J zvw_BF`ubuR>yh#A9E*?T4oU0LduONo0?sXj9jN0IpXy)^6{}J_)9=7uAZ~(FU``J) z=C}$*!;u3x+pecr0^u|hsm7Pf;ce;W(anRxp{9xU1~;EZW*QfJ 常量喂入与缺失/多余/数量错配的拒绝。 + +用法：python3 gen_extra_input_fixture.py +""" +import sys +from pathlib import Path + +DATA_DIR = Path(__file__).resolve().parent / "data" + + +def main() -> None: + import onnx + from onnx import TensorProto, helper + + DATA_DIR.mkdir(exist_ok=True) + add = helper.make_node("Add", ["obs", "offset"], ["actions"], name="add_offset") + graph = helper.make_graph( + [add], + "extra_input_policy", + [ + helper.make_tensor_value_info("obs", TensorProto.FLOAT, ["batch", 2]), + helper.make_tensor_value_info("offset", TensorProto.FLOAT, ["batch", 1]), + ], + [helper.make_tensor_value_info("actions", TensorProto.FLOAT, ["batch", 2])], + ) + model = helper.make_model(graph, opset_imports=[helper.make_opsetid("", 17)]) + model.ir_version = 8 + model.producer_name = "rmcs_rl/gen_extra_input_fixture" + for key, value in { + "rmcs_obs_layout": "v3-history=1|constant:0+0@2", + "rmcs_actions_layout": "v2|#0:a|#1:b", + }.items(): + entry = model.metadata_props.add() + entry.key = key + entry.value = value + onnx.checker.check_model(model) + path = DATA_DIR / "extra_input_identity.onnx" + onnx.save(model, path) + print(f"wrote {path}") + + +if __name__ == "__main__": + sys.exit(main()) diff --git a/test/gen_seq_fixtures.py b/test/gen_seq_fixtures.py new file mode 100644 index 0000000..ac104cf --- /dev/null +++ b/test/gen_seq_fixtures.py @@ -0,0 +1,77 @@ +#!/usr/bin/env python3 +"""生成 rank-3 序列策略回归夹具（确定性，无训练依赖）。 + +产出（写入 test/data/）： + seq_identity.onnx obs float32[batch,2,3] -> actions float32[batch,3] + Flatten 后 actions[j] = x[j] + x[j+3]； + metadata: rmcs_model_type=transformer, + rmcs_history_length=2, rmcs_obs_frame_size=3。 + seq_history_mismatch.onnx 同图，但 rmcs_history_length=3（与张量 T=2 不符）， + 用于校验 policy_server 启动期拒绝。 + +用法：python3 gen_seq_fixtures.py +""" +import sys +from pathlib import Path + +DATA_DIR = Path(__file__).resolve().parent / "data" + + +def _build(history: int, frame: int, metadata: dict) -> "object": + import numpy as np + import onnx + from onnx import TensorProto, helper, numpy_helper + + obs = history * frame + act = frame + # W (obs, act) = [I; I; ...] 每个历史帧块都加到同一输出槽： + # actions[j] = sum_t x[t, j] + weight = np.zeros((obs, act), dtype=np.float32) + for t in range(history): + for j in range(act): + weight[t * frame + j, j] = 1.0 + weight_init = numpy_helper.from_array(weight, name="W") + flatten = helper.make_node("Flatten", ["obs"], ["flat"], name="flatten_seq", axis=1) + matmul = helper.make_node("MatMul", ["flat", "W"], ["actions"], name="sum_history") + graph = helper.make_graph( + [flatten, matmul], + "seq_policy", + [helper.make_tensor_value_info( + "obs", TensorProto.FLOAT, ["batch", history, frame])], + [helper.make_tensor_value_info("actions", TensorProto.FLOAT, ["batch", act])], + [weight_init], + ) + model = helper.make_model(graph, opset_imports=[helper.make_opsetid("", 17)]) + model.ir_version = 8 + model.producer_name = "rmcs_rl/gen_seq_fixtures" + for key, value in metadata.items(): + entry = model.metadata_props.add() + entry.key = key + entry.value = value + onnx.checker.check_model(model) + return model + + +def main() -> None: + import onnx + + DATA_DIR.mkdir(exist_ok=True) + shared = { + "rmcs_obs_layout": "v3-history=2|constant:0+0+0@3", + "rmcs_actions_layout": "v2|#0:a|#1:b|#2:c", + "rmcs_model_type": "transformer", + "rmcs_obs_frame_size": "3", + } + ok_meta = dict(shared, rmcs_history_length="2") + mismatch_meta = dict(shared, rmcs_history_length="3") + + ok_path = DATA_DIR / "seq_identity.onnx" + mismatch_path = DATA_DIR / "seq_history_mismatch.onnx" + onnx.save(_build(2, 3, ok_meta), ok_path) + onnx.save(_build(2, 3, mismatch_meta), mismatch_path) + print(f"wrote {ok_path}") + print(f"wrote {mismatch_path}") + + +if __name__ == "__main__": + sys.exit(main()) diff --git a/test/gen_synthetic_policy.py b/test/gen_synthetic_policy.py index f739ecf..e8b15e8 100644 --- a/test/gen_synthetic_policy.py +++ b/test/gen_synthetic_policy.py @@ -9,8 +9,13 @@ def _export_with_onnx(obs: int, act: int, output: str, model_type: str, - sequence_length: int, feature_size: int) -> None: - """Export a zero-action MLP/sequence fixture without a training dependency.""" + sequence_length: int, feature_size: int, + extra_specs: list) -> None: + """Export a zero-action MLP/sequence fixture without a training dependency. + + extra_specs: [(name, dims)] 额外输入；每个 ReduceSum 成标量后加到主输出， + 保证额外输入被图消费（onnx.checker 要求）且输出仍为 [1, act]。 + """ import numpy as np import onnx from onnx import TensorProto, helper, numpy_helper @@ -32,12 +37,26 @@ def _export_with_onnx(obs: int, act: int, output: str, model_type: str, weight_shape = (obs, act) matmul_input = "obs" weight = numpy_helper.from_array(np.zeros(weight_shape, dtype=np.float32), name="W") - matmul = helper.make_node("MatMul", [matmul_input, "W"], ["actions"], name="zero_action") + matmul_output = "actions" if not extra_specs else "logits" + matmul = helper.make_node("MatMul", [matmul_input, "W"], [matmul_output], name="zero_action") nodes = [node, matmul] if node is not None else [matmul] + + input_infos = [helper.make_tensor_value_info("obs", TensorProto.FLOAT, input_shape)] + current = matmul_output + for index, (name, dims) in enumerate(extra_specs): + input_infos.append( + helper.make_tensor_value_info(name, TensorProto.FLOAT, [1, *dims])) + nodes.append(helper.make_node( + "ReduceSum", [name], [f"{name}_sum"], name=f"sum_{name}", keepdims=0)) + final = "actions" if index == len(extra_specs) - 1 else f"add_{index}" + nodes.append(helper.make_node( + "Add", [current, f"{name}_sum"], [final], name=f"add_{name}")) + current = final + graph = helper.make_graph( nodes, "zero_policy", - [helper.make_tensor_value_info("obs", TensorProto.FLOAT, input_shape)], + input_infos, [helper.make_tensor_value_info("actions", TensorProto.FLOAT, [1, act])], [weight], ) @@ -60,6 +79,8 @@ def main() -> None: help="序列长度；>1 时生成 rank-3 输入") parser.add_argument("--feature-size", type=int, default=None, help="单帧维度；缺省由 obs/sequence 推导") + parser.add_argument("--extra-input", action="append", default=[], metavar="NAME:DIMS", + help="额外输入张量，如 mask:4 或 pos:2x3（可重复）") parser.add_argument("--from-config", "--config", dest="config", default=None, help="部署 YAML：由 observation_terms/action_terms 推导 obs/act 尺寸") parser.add_argument("--node", default=layout.DEFAULT_NODE, @@ -98,9 +119,32 @@ def main() -> None: if feature_size <= 0 or sequence_length * feature_size != obs: print("ERROR: obs 必须能按 sequence-length 分解为正整数 feature-size", file=sys.stderr) sys.exit(1) - _export_with_onnx(obs, act, args.output, args.model_type, sequence_length, feature_size) + + extra_specs = [] + for spec in args.extra_input: + if ":" not in spec: + print(f"ERROR: --extra-input 需要 NAME:DIMS 形式（got {spec!r}）", file=sys.stderr) + sys.exit(1) + name, dims_text = spec.split(":", 1) + try: + dims = [int(part) for part in dims_text.split("x")] + except ValueError: + print(f"ERROR: --extra-input 维度非法（got {spec!r}）", file=sys.stderr) + sys.exit(1) + if not name or not dims or any(dim <= 0 for dim in dims): + print(f"ERROR: --extra-input 需要非空名字与正整数维（got {spec!r}）", file=sys.stderr) + sys.exit(1) + if name == "obs" or any(existing == name for existing, _ in extra_specs): + print(f"ERROR: --extra-input 名字重复或与 obs 冲突（got {name!r}）", file=sys.stderr) + sys.exit(1) + extra_specs.append((name, dims)) + + _export_with_onnx(obs, act, args.output, args.model_type, sequence_length, feature_size, + extra_specs) input_desc = f"[1,{obs}]" if sequence_length == 1 else f"[1,{sequence_length},{feature_size}]" + for name, dims in extra_specs: + input_desc += f" + {name}[1,{'x'.join(str(dim) for dim in dims)}]" print(f"wrote {args.output}: obs float32{input_desc} -> actions float32[1,{act}] (zero policy)") diff --git a/test/runtime_test.cpp b/test/runtime_test.cpp index bcf26f8..becb364 100644 --- a/test/runtime_test.cpp +++ b/test/runtime_test.cpp @@ -147,6 +147,71 @@ TEST(PolicyModel, ParameterClipsOverrideMetadata) { EXPECT_EQ(action, (std::array{3.0, -3.0})); } +TEST(PolicyModel, LoadsRank3SequenceInput) { + PolicyModel::Config config; + config.path = RMCS_RL_SEQ_FIXTURE; + PolicyModel model{config}; + const auto& info = model.info(); + EXPECT_EQ(info.model_type, "transformer"); + EXPECT_EQ(info.input_rank, 3u); + EXPECT_EQ(info.sequence_length, 2u); + EXPECT_EQ(info.feature_size, 3u); + ASSERT_EQ(info.obs_size, 6u); + ASSERT_EQ(info.action_size, 3u); + std::array action{}; + std::string error; + ASSERT_TRUE(model.run(std::array{1., 2., 3., 4., 5., 6.}, action, error)) << error; + EXPECT_EQ(action, (std::array{5.0, 7.0, 9.0})); + EXPECT_FALSE(model.run(std::array{1., 2., 3.}, action, error)); +} + +TEST(PolicyModel, RejectsSequenceHistoryMetadataMismatch) { + PolicyModel::Config config; + config.path = RMCS_RL_SEQ_MISMATCH_FIXTURE; + EXPECT_THROW(PolicyModel{config}, std::invalid_argument); +} + +TEST(PolicyModel, RejectsTransformerTypeOnRank2Input) { + PolicyModel::Config config; + config.path = RMCS_RL_IDENTITY_FIXTURE; + config.model_type = "transformer"; + EXPECT_THROW(PolicyModel{config}, std::invalid_argument); +} + +TEST(PolicyModel, FeedsExtraInputConstants) { + PolicyModel::Config config; + config.path = RMCS_RL_EXTRA_FIXTURE; + config.extra_input_values["offset"] = {10.0}; + PolicyModel model{config}; + ASSERT_EQ(model.info().obs_size, 2u); + ASSERT_EQ(model.info().action_size, 2u); + std::array action{}; + std::string error; + ASSERT_TRUE(model.run(std::array{3.0, 6.0}, action, error)) << error; + EXPECT_EQ(action, (std::array{13.0, 16.0})); +} + +TEST(PolicyModel, RejectsMissingExtraInputDeclaration) { + PolicyModel::Config config; + config.path = RMCS_RL_EXTRA_FIXTURE; + EXPECT_THROW(PolicyModel{config}, std::invalid_argument); +} + +TEST(PolicyModel, RejectsExtraInputWithoutMatchingModelInput) { + PolicyModel::Config config; + config.path = RMCS_RL_EXTRA_FIXTURE; + config.extra_input_values["offset"] = {10.0}; + config.extra_input_values["bogus"] = {1.0}; + EXPECT_THROW(PolicyModel{config}, std::invalid_argument); +} + +TEST(PolicyModel, RejectsWrongExtraInputValueCount) { + PolicyModel::Config config; + config.path = RMCS_RL_EXTRA_FIXTURE; + config.extra_input_values["offset"] = {1.0, 2.0}; + EXPECT_THROW(PolicyModel{config}, std::invalid_argument); +} + } // namespace } // namespace rmcs_rl #include diff --git a/test/test_layout_contract.sh b/test/test_layout_contract.sh index 7786a6c..0c4364e 100755 --- a/test/test_layout_contract.sh +++ b/test/test_layout_contract.sh @@ -191,6 +191,103 @@ run_expect 1 "(e) rl_action_size != 动作词条数" \ "$PY" "$TOOLS/check_policy_contract.py" "$MODEL" --config "$WORK/x_actsize.yaml" expect_msg "rl_action_size" "尺寸不一致提示" +echo "== 5. Transformer rank-3 与 T==history 强制 ==" +FIXTURE_H4="$WORK/x_h4.yaml" +FIXTURE_H5="$WORK/x_h5.yaml" +MODEL_SEQ="$WORK/policy_seq.onnx" + +cat >"$FIXTURE_H4" <<'YAML' +rl_bridge: + ros__parameters: + history_length: 4 + rl_obs_size: 20 + rl_action_size: 6 + observation_terms: + - index=0 path=/chassis/control_height + - index=1 path=/chassis/control_velocity take=x + - index=2 path=/wheel_leg/imu/angular_velocity take=vec3 + action_terms: + - index=0 output=/wheel_leg/rl/action/lf0 + - index=1 output=/wheel_leg/rl/action/lf1 + - index=2 output=/wheel_leg/rl/action/l_wheel + - index=3 output=/wheel_leg/rl/action/rf0 + - index=4 output=/wheel_leg/rl/action/rf1 + - index=5 output=/wheel_leg/rl/action/r_wheel +YAML +sed -e 's/history_length: 4/history_length: 5/' \ + -e 's|index=2 path=/wheel_leg/imu/angular_velocity take=vec3|index=2 type=joint_pos joints=lf0,lf1 relative=true|' \ + "$FIXTURE_H4" >"$FIXTURE_H5" + +run_expect 0 "gen rank-3 transformer 夹具 (T=4, F=5)" \ + "$PY" "$HERE/gen_synthetic_policy.py" --obs 20 --act 6 \ + --model-type transformer --sequence-length 4 -o "$MODEL_SEQ" +run_expect 0 "盖章 transformer（默认写 rmcs_history_length）" \ + "$PY" "$TOOLS/stamp_layout_metadata.py" --model "$MODEL_SEQ" \ + --from-config "$FIXTURE_H4" --model-type transformer +expect_msg "rmcs_history_length" "盖章输出含序列键" +run_expect 0 "check rank-3 transformer（T==history 正例）" \ + "$PY" "$TOOLS/check_policy_contract.py" "$MODEL_SEQ" --config "$FIXTURE_H4" +expect_msg "model sequence dim == expected history" "T 等值检查已执行" + +cp "$MODEL_SEQ" "$WORK/policy_seq_h5.onnx" +run_expect 0 "同一模型按 history=5 配置盖章（模拟窗口错配）" \ + "$PY" "$TOOLS/stamp_layout_metadata.py" --model "$WORK/policy_seq_h5.onnx" \ + --from-config "$FIXTURE_H5" --model-type transformer +run_expect 1 "(f) 模型 T=4 != history=5 → 必须 FAIL" \ + "$PY" "$TOOLS/check_policy_contract.py" "$WORK/policy_seq_h5.onnx" --config "$FIXTURE_H5" +expect_msg "model sequence dim == expected history" "T 不匹配提示" + +cp "$MODEL" "$WORK/policy_mlptype.onnx" +run_expect 0 "给 rank-2 模型盖 rmcs_model_type=transformer" \ + "$PY" "$TOOLS/stamp_layout_metadata.py" --model "$WORK/policy_mlptype.onnx" \ + --from-config "$FIXTURE" --model-type transformer +run_expect 1 "(g) model_type=transformer 但输入 rank=2 → 必须 FAIL" \ + "$PY" "$TOOLS/check_policy_contract.py" "$WORK/policy_mlptype.onnx" --config "$FIXTURE" +expect_msg "input rank/model type" "rank/type 不匹配提示" + +echo "== 6. 多输入（policy_server extra_inputs 常量）==" +FIXTURE_EXTRA="$WORK/x_extra.yaml" +MODEL_EXTRA="$WORK/policy_extra.onnx" +{ + cat "$FIXTURE" + cat <<'YAML' + +policy_server: + ros__parameters: + rl_obs_size: 20 + rl_action_size: 6 + extra_inputs: + mask: [1, 1, 1, 1] +YAML +} >"$FIXTURE_EXTRA" + +run_expect 0 "gen 多输入夹具（obs + mask:4）" \ + "$PY" "$HERE/gen_synthetic_policy.py" --obs 20 --act 6 --extra-input mask:4 -o "$MODEL_EXTRA" +run_expect 0 "盖章多输入夹具" \ + "$PY" "$TOOLS/stamp_layout_metadata.py" --model "$MODEL_EXTRA" --from-config "$FIXTURE_EXTRA" +run_expect 0 "(h) 多输入 + extra_inputs 声明匹配 → PASS" \ + "$PY" "$TOOLS/check_policy_contract.py" "$MODEL_EXTRA" --config "$FIXTURE_EXTRA" +expect_msg "extra input mask" "额外输入校验已执行" + +run_expect 1 "(i) 模型有额外输入但 YAML 无 extra_inputs → FAIL" \ + "$PY" "$TOOLS/check_policy_contract.py" "$MODEL_EXTRA" --config "$FIXTURE" +expect_msg "extra_inputs match model" "缺声明提示" + +FIXTURE_EXTRA_UNKNOWN="$WORK/x_extra_unknown.yaml" +{ + cat "$FIXTURE" + cat <<'YAML' + +policy_server: + ros__parameters: + extra_inputs: + bogus: [1, 2, 3] +YAML +} >"$FIXTURE_EXTRA_UNKNOWN" +run_expect 1 "(j) YAML 声明了模型没有的额外输入 → FAIL" \ + "$PY" "$TOOLS/check_policy_contract.py" "$MODEL" --config "$FIXTURE_EXTRA_UNKNOWN" +expect_msg "extra_inputs match model" "多余声明提示" + echo echo "==== 结果：PASS=$PASS FAIL=$FAIL ====" [ "$FAIL" = 0 ] || exit 1 diff --git a/tool/check_policy_contract.py b/tool/check_policy_contract.py index a39546f..7d6e901 100644 --- a/tool/check_policy_contract.py +++ b/tool/check_policy_contract.py @@ -4,8 +4,10 @@ Two modes: * self-check (no --config; used by CI, deployment YAML lives in the RMCS repo): - model loads; one input "obs" / one output "actions"; float32; rank 1/2/3; - MLP uses rank 2 or rank 3 and Transformer uses rank 3. Layout metadata is OPTIONAL: + model loads; primary input "obs" / one output "actions"; float32; rank 1/2/3; + MLP uses rank 2 or rank 3 and Transformer uses rank 3. Extra (non-obs) + inputs are allowed; with --config they must match policy_server extra_inputs. + Layout metadata is OPTIONAL: - missing / v1 -> SKIP (stamped layout metadata is optional for model-only self-check) - present v2 -> signatures must be internally consistent with the tensor sizes, and policy_layout_hash must match those signatures @@ -133,7 +135,7 @@ def _check_normalization(report, meta, obs_size): def _dummy_inference(report, model_path, obs_size, act_size, model_type, - input_rank, sequence_length, feature_size): + input_rank, sequence_length, feature_size, extra_specs=None): """跑一次零输入推理，确认输出有限、元素数正确（无 onnxruntime 则跳过）。""" try: import numpy as np @@ -149,7 +151,15 @@ def _dummy_inference(report, model_path, obs_size, act_size, model_type, obs = np.zeros((obs_size,), dtype=np.float32) else: obs = np.zeros((1, obs_size), dtype=np.float32) - actions = session.run(["actions"], {"obs": obs})[0] + feed = {"obs": obs} + for name, (shape, values) in (extra_specs or {}).items(): + count = 1 + for dim in shape: + count *= dim + if values is None: + values = [1.0] * count + feed[name] = np.asarray(values, dtype=np.float32).reshape(shape) + actions = session.run(["actions"], feed)[0] except Exception as exc: report.check("dummy inference", False, f"{type(exc).__name__}: {exc}") return @@ -244,24 +254,25 @@ def main() -> None: for value in outputs: print(f"output : {value.name} {_shape_of(value)}") - report.check("tensor count/names", len(inputs) == 1 and len(outputs) == 1 - and inputs[0].name == "obs" and outputs[0].name == "actions", - f"inputs={[v.name for v in inputs]} outputs={[v.name for v in outputs]}" - if not (len(inputs) == 1 and len(outputs) == 1) else "obs -> actions") - - if not (len(inputs) == 1 and len(outputs) == 1): - print("== SUMMARY: FAIL (张量不合法，后续检查跳过) ==") + input_names = [value.name for value in inputs] + names_ok = (len(outputs) == 1 and outputs[0].name == "actions" and "obs" in input_names) + report.check("tensor names", names_ok, + f"inputs={input_names} outputs={[v.name for v in outputs]}") + if not names_ok: + print("== SUMMARY: FAIL (张量不合法：需要主输入 obs + 唯一输出 actions，后续检查跳过) ==") sys.exit(1) - inp, out = inputs[0], outputs[0] + inp = next(value for value in inputs if value.name == "obs") + out = outputs[0] def _dtype_name(value_info): elem = value_info.type.tensor_type.elem_type return "float32" if elem == TensorProto.FLOAT else TensorProto.DataType.Name(elem).lower() - report.check("dtype float32", inp.type.tensor_type.elem_type == TensorProto.FLOAT - and out.type.tensor_type.elem_type == TensorProto.FLOAT, - f"obs={_dtype_name(inp)} actions={_dtype_name(out)}") + dtype_ok = (all(value.type.tensor_type.elem_type == TensorProto.FLOAT for value in inputs) + and out.type.tensor_type.elem_type == TensorProto.FLOAT) + report.check("dtype float32", dtype_ok, + f"inputs={[_dtype_name(value) for value in inputs]} actions={_dtype_name(out)}") in_shape, out_shape = _shape_of(inp), _shape_of(out) meta = {prop.key: prop.value for prop in model.metadata_props} declared_type = meta.get("rmcs_model_type", "").strip().lower() @@ -291,6 +302,75 @@ def _dtype_name(value_info): f"obs={in_shape[0] if len(in_shape) >= 2 else ''!r} " f"actions={out_shape[0] if len(out_shape) >= 2 else ''!r}（允许 1 或动态维）") + # 额外输入（如 attention mask）：形状校验 + 与 policy_server extra_inputs 对账 + extra_shapes = {value.name: _shape_of(value) for value in inputs if value.name != "obs"} + declared_extra: dict = {} + if args.config: + import yaml + document = yaml.safe_load(open(args.config, encoding="utf-8")) or {} + section = ((document.get("policy_server") or {}).get("ros__parameters") or {}) + raw_extra = section.get("extra_inputs") or {} + if not isinstance(raw_extra, dict): + report.check("extra_inputs section", False, f"extra_inputs={raw_extra!r} 必须是映射") + else: + declared_extra = raw_extra + extra_specs: dict = {} + if extra_shapes or declared_extra: + if args.config: + missing = sorted(set(extra_shapes) - set(declared_extra)) + unknown = sorted(set(declared_extra) - set(extra_shapes)) + report.check("extra_inputs match model", + not missing and not unknown, + f"模型缺声明={missing} 声明无对应输入={unknown}" + if (missing or unknown) else f"{sorted(extra_shapes)}") + else: + report.info("extra_inputs", + f"模型额外输入 {sorted(extra_shapes)}（无 --config，仅校验形状，dummy 用 1 填充）") + for name, shape in sorted(extra_shapes.items()): + ok = True + detail = f"{name}{shape}" + runtime_shape = [] + first_dim = 0 + if len(shape) >= 2: + if not (shape[0] == 1 or shape[0] is None or isinstance(shape[0], str)): + ok = False + detail += " batch 维必须为 1 或动态" + runtime_shape.append(1) + first_dim = 1 + elements = 1 + for dim in shape[first_dim:]: + if not isinstance(dim, int) or dim <= 0: + ok = False + detail += f" 非 batch 维必须是具体正整数（got {dim!r}）" + break + runtime_shape.append(dim) + elements *= dim + values = None + if ok and args.config and name in declared_extra: + raw_values = declared_extra[name] + if not isinstance(raw_values, list) or not raw_values: + ok = False + detail += " extra_inputs 值必须是非空列表" + else: + try: + values = [float(item) for item in raw_values] + except (TypeError, ValueError): + ok = False + values = None + detail += " 含非数值元素" + else: + if any(not math.isfinite(item) for item in values): + ok = False + detail += " 含非有限值" + values = None + elif len(values) != elements: + ok = False + detail += f" 值数量 {len(values)} != 元素数 {elements}" + values = None + report.check(f"extra input {name}", ok, detail) + if ok: + extra_specs[name] = (tuple(runtime_shape), values) + history_length = layout.history_length(args.config, args.node) if args.config else 1 metadata_sequence = metadata_feature = 0 for key in ("rmcs_history_length", "rmcs_obs_frame_size"): @@ -308,16 +388,42 @@ def _dtype_name(value_info): else: metadata_feature = value config_feature_size = obs_size // history_length if obs_size is not None else None + if args.config: + if metadata_sequence: + report.check("metadata history == config history_length", + metadata_sequence == history_length, + f"rmcs_history_length={metadata_sequence} history_length={history_length}") + if metadata_feature and config_feature_size: + report.check("metadata frame == config frame size", + metadata_feature == config_feature_size, + f"rmcs_obs_frame_size={metadata_feature} 单帧={config_feature_size}") + if args.sequence_length and args.sequence_length != history_length: + report.check("--sequence-length == history_length", False, + f"--sequence-length={args.sequence_length} history_length={history_length}") + if args.feature_size and config_feature_size and args.feature_size != config_feature_size: + report.check("--feature-size == config frame size", False, + f"--feature-size={args.feature_size} 单帧={config_feature_size}") + input_tail = in_shape[0:] if len(in_shape) == 1 else in_shape[1:] sequence_length = args.sequence_length or metadata_sequence or ( - history_length if len(in_shape) == 3 else 1) + history_length if len(in_shape) == 3 and args.config else None) feature_size = args.feature_size or metadata_feature or ( - config_feature_size if len(in_shape) == 3 else None) + config_feature_size if len(in_shape) == 3 and args.config else None) if len(in_shape) == 3: declared_sequence, declared_feature = input_tail if isinstance(declared_sequence, int) and declared_sequence > 0: + if sequence_length is not None: + report.check("model sequence dim == expected history", + declared_sequence == sequence_length, + f"model T={declared_sequence} expected={sequence_length}" + "（= --sequence-length/rmcs_history_length/history_length，" + "与运行时 onnx_runtime 同优先级）") sequence_length = declared_sequence if isinstance(declared_feature, int) and declared_feature > 0: + if feature_size is not None: + report.check("model feature dim == expected frame", + declared_feature == feature_size, + f"model F={declared_feature} expected={feature_size}") feature_size = declared_feature model_obs = sequence_length * feature_size if sequence_length and feature_size else None else: @@ -431,7 +537,7 @@ def _dtype_name(value_info): _check_normalization(report, meta, obs_size) _dummy_inference(report, args.model, obs_size, act_size, model_type, len(in_shape), - sequence_length, feature_size or obs_size) + sequence_length, feature_size or obs_size, extra_specs) try: file_id = layout.model_id(args.model) diff --git a/tool/stamp_layout_metadata.py b/tool/stamp_layout_metadata.py index eaea382..47aea94 100644 --- a/tool/stamp_layout_metadata.py +++ b/tool/stamp_layout_metadata.py @@ -14,9 +14,9 @@ rmcs_obs_mean/std 可选（--obs-mean/--obs-std，长度必须 == rl_obs_size） rmcs_obs_clip 可选单浮点（--obs-clip） rmcs_action_clip 可选单浮点（--action-clip） - rmcs_model_type 可选结构标识 mlp/transformer/generic（--model-type） - rmcs_history_length 可选序列长度（Transformer 或带历史帧 MLP） - rmcs_obs_frame_size 可选单帧维度 + rmcs_model_type 可选结构标识 mlp/transformer/generic（--model-type；缺省由部署端按 rank 推断） + rmcs_history_length 序列长度（缺省取 YAML history_length，部署端据此强制 模型T==history） + rmcs_obs_frame_size 单帧观测维度（缺省由 rl_obs_size/history_length 推导） 用法： python3 stamp_layout_metadata.py --model policy.onnx --from-config deploy.yaml @@ -91,19 +91,14 @@ def main() -> None: raise layout.LayoutError(f"{option}={value!r} 必须是有限正数") history_length = layout.history_length(args.config, args.node) - sequence_length = args.sequence_length if args.sequence_length is not None else ( - history_length if args.model_type in ("mlp", "transformer") else None) + sequence_length = args.sequence_length if args.sequence_length is not None else history_length feature_size = args.feature_size if args.feature_size is not None else ( - obs_size // history_length if args.model_type in ("mlp", "transformer") else None) - if feature_size is None and sequence_length is not None and obs_size % sequence_length == 0: - feature_size = obs_size // sequence_length - if sequence_length is not None and sequence_length < 1: - raise layout.LayoutError("--sequence-length 必须 >= 1") - if feature_size is not None and feature_size < 1: - raise layout.LayoutError("--feature-size 必须 >= 1") - if sequence_length is not None and feature_size is None: - raise layout.LayoutError("给出 --sequence-length 时必须能推导或指定 --feature-size") - if sequence_length is not None and sequence_length * feature_size != obs_size: + obs_size // history_length) + if sequence_length < 1: + raise layout.LayoutError(f"--sequence-length 必须 >= 1") + if feature_size < 1: + raise layout.LayoutError(f"--feature-size 必须 >= 1") + if sequence_length * feature_size != obs_size: raise layout.LayoutError( f"sequence_length * feature_size={sequence_length * feature_size} != rl_obs_size={obs_size}") From 7d7823d37f24fd10a00fdfd624a5f01a360787a6 Mon Sep 17 00:00:00 2001 From: ZGZ713912 Date: Wed, 30 Sep 2026 13:43:54 +0800 Subject: [PATCH 6/9] feat: add support for typed extra inputs and layout validation --- CMakeLists.txt | 6 +- README.md | 24 +-- src/policy/onnx_runtime.cpp | 187 ++++++++++++++++++---- src/policy/onnx_runtime.hpp | 24 ++- src/policy/policy_model.hpp | 2 +- src/policy_server.cpp | 22 +-- test/data/seq_layout_dynamic.onnx | Bin 0 -> 426 bytes test/data/seq_layout_mismatch.onnx | Bin 0 -> 463 bytes test/data/seq_layout_only.onnx | Bin 0 -> 411 bytes test/data/typed_extra_input_identity.onnx | Bin 0 -> 529 bytes test/gen_seq_fixtures.py | 25 ++- test/gen_typed_extra_input_fixture.py | 48 ++++++ test/runtime_test.cpp | 50 +++++- test/test_layout_contract.sh | 15 ++ tool/check_policy_contract.py | 93 +++++++++-- 15 files changed, 420 insertions(+), 76 deletions(-) create mode 100644 test/data/seq_layout_dynamic.onnx create mode 100644 test/data/seq_layout_mismatch.onnx create mode 100644 test/data/seq_layout_only.onnx create mode 100644 test/data/typed_extra_input_identity.onnx create mode 100644 test/gen_typed_extra_input_fixture.py diff --git a/CMakeLists.txt b/CMakeLists.txt index 11f9629..c1e859e 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -100,7 +100,11 @@ if(BUILD_TESTING) RMCS_RL_IDENTITY_FIXTURE="${PROJECT_SOURCE_DIR}/test/data/normalized_identity.onnx" RMCS_RL_SEQ_FIXTURE="${PROJECT_SOURCE_DIR}/test/data/seq_identity.onnx" RMCS_RL_SEQ_MISMATCH_FIXTURE="${PROJECT_SOURCE_DIR}/test/data/seq_history_mismatch.onnx" - RMCS_RL_EXTRA_FIXTURE="${PROJECT_SOURCE_DIR}/test/data/extra_input_identity.onnx") + RMCS_RL_SEQ_LAYOUT_MISMATCH_FIXTURE="${PROJECT_SOURCE_DIR}/test/data/seq_layout_mismatch.onnx" + RMCS_RL_SEQ_LAYOUT_ONLY_FIXTURE="${PROJECT_SOURCE_DIR}/test/data/seq_layout_only.onnx" + RMCS_RL_SEQ_LAYOUT_DYNAMIC_FIXTURE="${PROJECT_SOURCE_DIR}/test/data/seq_layout_dynamic.onnx" + RMCS_RL_EXTRA_FIXTURE="${PROJECT_SOURCE_DIR}/test/data/extra_input_identity.onnx" + RMCS_RL_TYPED_EXTRA_FIXTURE="${PROJECT_SOURCE_DIR}/test/data/typed_extra_input_identity.onnx") endif() ament_export_dependencies(rosidl_default_runtime) diff --git a/README.md b/README.md index 703179b..7a66c53 100644 --- a/README.md +++ b/README.md @@ -62,25 +62,26 @@ ros2 run rmcs_rl policy_server --ros-args --params-file <车辆配置.yaml> `auto` 优先读取 `rmcs_model_type`，没有 metadata 时才按 rank-2 推断 MLP、rank-3 推断 Transformer。 -多输入模型（例如独立 attention mask）除 `obs` 外的输入必须是常量张量，在 -`policy_server` 段用 `extra_inputs.<输入名>: [元素列表]` 声明；启动时校验名字对齐、 -元素数量与形状一致、数值有限，缺声明或声明了模型没有的输入都会拒绝； +多输入模型（例如独立 attention mask 或 position id）除 `obs` 外的输入必须是常量张量，在 +`policy_server` 段用 `extra_inputs.<输入名>: [元素列表]` 声明；启动时根据 ONNX 输入类型 +创建 `float32`、`int64` 或 `bool` 张量，并校验名字、元素数量和形状；缺声明、类型不匹配 +或声明了模型没有的输入都会拒绝； 输出仍必须是唯一的 `actions`。 ```yaml policy_server: ros__parameters: extra_inputs: - attn_mask: [1, 1, 1, 1] # 展平常量，长度 = 模型该输入非 batch 维元素数 + attn_mask: [true, true, true, true] # bool mask；也支持 int64 position id ``` 部署模型须含 `rmcs_obs_layout`、`rmcs_actions_layout`；建议带 `policy_layout_hash` 和版本。 `history_length × 单帧维数 = rl_obs_size`。归一化均值和标准差必须成对提供，标准差为正数。 -rank-3 模型的序列切分受强制约束：模型的 `T == history_length`、`F == 单帧维数`。 -盖章默认把 `rmcs_history_length`、`rmcs_obs_frame_size` 从 YAML 写入 metadata； -契约工具与 policy_server 启动时按 `--sequence-length/rmcs_history_length/history_length` -（参数 > metadata > 模型声明）逐级等值校验，任一级不符即拒绝。 +rank-3 模型的序列切分受强制约束：模型的 `T == v3-history`、`F == rl_obs_size / history_length`， +其中 `v3-history` 来自必需的 `rmcs_obs_layout`，并且最终还会由动作消息的 layout hash 与 +`rl_bridge` 再次核对。`rmcs_history_length`、`rmcs_obs_frame_size` 和 `sequence_length` 是 +启动时的辅助维度声明，缺失或不一致都会拒绝；它们不能替代布局签名。 带历史帧的模型示例（桥和策略进程都要使用同一历史长度）： @@ -97,7 +98,8 @@ policy_server: rl_obs_size: 208 ``` -盖章默认写入序列键（`rmcs_history_length`/`rmcs_obs_frame_size`，取自 YAML）； +盖章默认写入序列键（`rmcs_history_length`/`rmcs_obs_frame_size`，取自 YAML）；部署端还会 +从必需的 `rmcs_obs_layout` 中读取 `v3-history`，防止只依赖可选 metadata。 `rmcs_model_type` 可选，缺省由部署端按输入 rank 推断： ```sh @@ -145,8 +147,8 @@ colcon test --merge-install --packages-select rmcs_rl rmcs_core PYTHON=<带 onnx、onnxruntime、PyYAML 的 Python> bash src/rmcs_rl/test/test_layout_contract.sh ``` -C++ 回归覆盖推理归一化、历史帧、rank-3 序列输入、extra_inputs 常量喂入与错配拒绝、 +C++ 回归覆盖推理归一化、历史帧、rank-3 序列输入、float32/int64/bool extra_inputs 常量喂入与错配拒绝、 跨线程动作快照；Python 回归覆盖布局解析、盖章、T==history 强制、model_type/rank 匹配、 多输入声明对账及错误契约拒绝。夹具由 `test/gen_seq_fixtures.py`、 -`test/gen_extra_input_fixture.py` 确定性生成后提交。 +`test/gen_extra_input_fixture.py` 和 `test/gen_typed_extra_input_fixture.py` 确定性生成后提交。 车辆包保留 DM 使能、帧解码、闭链几何、Body IMU 以及 MuJoCo 查看器回归。 diff --git a/src/policy/onnx_runtime.cpp b/src/policy/onnx_runtime.cpp index 8fbff25..8b0e4a6 100644 --- a/src/policy/onnx_runtime.cpp +++ b/src/policy/onnx_runtime.cpp @@ -2,9 +2,12 @@ #include #include +#include #include +#include #include #include +#include namespace rmcs_rl { namespace { @@ -37,6 +40,59 @@ bool batch_dimension_ok(std::int64_t dimension) { return dimension == 1 || dimension == -1; } +struct LayoutDimensions { + std::size_t history = 0; + std::size_t feature = 0; + std::size_t observation = 0; +}; + +std::optional layout_dimensions(const std::optional& value) { + if (!value || value->empty()) + return std::nullopt; + constexpr std::string_view prefix = "v3-history="; + const std::string_view signature = *value; + if (!signature.starts_with(prefix)) + return std::nullopt; + + const auto header_end = signature.find('|', prefix.size()); + if (header_end == std::string_view::npos) + throw std::invalid_argument("rmcs_obs_layout is missing observation entries"); + const auto history_text = signature.substr(prefix.size(), header_end - prefix.size()); + LayoutDimensions result; + const auto [history_end, history_error] = std::from_chars( + history_text.data(), history_text.data() + history_text.size(), result.history); + if (history_error != std::errc{} + || history_end != history_text.data() + history_text.size() || result.history == 0) + throw std::invalid_argument("rmcs_obs_layout history must be a positive integer"); + + std::size_t begin = header_end + 1; + while (begin < signature.size()) { + const auto end = signature.find('|', begin); + const auto entry = signature.substr( + begin, end == std::string_view::npos ? std::string_view::npos : end - begin); + const auto at = entry.rfind('@'); + if (at == std::string_view::npos || at + 1 == entry.size()) + throw std::invalid_argument("rmcs_obs_layout entry is missing @dim"); + std::size_t dimension = 0; + const auto dim_text = entry.substr(at + 1); + const auto [dim_end, dim_error] = std::from_chars( + dim_text.data(), dim_text.data() + dim_text.size(), dimension); + if (dim_error != std::errc{} || dim_end != dim_text.data() + dim_text.size() + || dimension == 0) + throw std::invalid_argument("rmcs_obs_layout entry dimension must be positive"); + if (dimension > std::numeric_limits::max() - result.feature) + throw std::invalid_argument("rmcs_obs_layout dimensions overflow"); + result.feature += dimension; + if (end == std::string_view::npos) + break; + begin = end + 1; + } + if (result.feature == 0 || result.history > std::numeric_limits::max() / result.feature) + throw std::invalid_argument("rmcs_obs_layout dimensions overflow"); + result.observation = result.history * result.feature; + return result; +} + } // namespace OnnxRuntime::OnnxRuntime(const Config& config) @@ -83,26 +139,18 @@ OnnxRuntime::OnnxRuntime(const Config& config) throw std::invalid_argument( "output tensor must be named '" + output_name_ + "', got '" + actual_output.get() + "'"); - for (std::size_t index = 0; index < input_count; ++index) { - const auto input_type = session_.GetInputTypeInfo(index); - if (input_type.GetONNXType() != ONNX_TYPE_TENSOR) - throw std::invalid_argument( - "input '" + input_names_[index] + "' must be a tensor"); - const auto input_info = input_type.GetTensorTypeAndShapeInfo(); - if (input_info.GetElementType() != ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT) - throw std::invalid_argument( - "input '" + input_names_[index] + "' element type must be float32"); - } - // Keep TypeInfo alive while reading the TensorTypeAndShapeInfo. The // latter is a view into TypeInfo in ONNX Runtime; chaining a temporary // here can read freed type metadata on some runtime builds. const auto input_type = session_.GetInputTypeInfo(primary_index); const auto output_type = session_.GetOutputTypeInfo(0); + if (input_type.GetONNXType() != ONNX_TYPE_TENSOR || output_type.GetONNXType() != ONNX_TYPE_TENSOR) + throw std::invalid_argument("obs and actions must be tensors"); const auto input_info = input_type.GetTensorTypeAndShapeInfo(); const auto output_info = output_type.GetTensorTypeAndShapeInfo(); - if (output_info.GetElementType() != ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT) - throw std::invalid_argument("tensor element type must be float32"); + if (input_info.GetElementType() != ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT + || output_info.GetElementType() != ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT) + throw std::invalid_argument("obs and actions element types must be float32"); const auto raw_input_shape = input_info.GetShape(); const auto raw_output_shape = output_info.GetShape(); @@ -149,9 +197,30 @@ OnnxRuntime::OnnxRuntime(const Config& config) const auto metadata_sequence = parse_positive(metadata("rmcs_history_length"), "rmcs_history_length"); const auto metadata_feature = parse_positive(metadata("rmcs_obs_frame_size"), "rmcs_obs_frame_size"); - std::size_t sequence = config.sequence_length != 0 ? config.sequence_length : metadata_sequence; - std::size_t feature = config.feature_size != 0 ? config.feature_size : metadata_feature; - const auto expected_observation = config.observation_size; + const auto layout = layout_dimensions(metadata("rmcs_obs_layout")); + if (raw_input_shape.size() == 3 && !layout) + throw std::invalid_argument("rank-3 model requires an rmcs_obs_layout v3-history signature"); + if (layout && metadata_sequence != 0 && metadata_sequence != layout->history) + throw std::invalid_argument("rmcs_history_length does not match rmcs_obs_layout"); + if (layout && metadata_feature != 0 && metadata_feature != layout->feature) + throw std::invalid_argument("rmcs_obs_frame_size does not match rmcs_obs_layout"); + if (layout && config.sequence_length != 0 && config.sequence_length != layout->history) + throw std::invalid_argument("sequence_length does not match rmcs_obs_layout"); + if (layout && config.feature_size != 0 && config.feature_size != layout->feature) + throw std::invalid_argument("feature_size does not match rmcs_obs_layout"); + std::size_t sequence = config.sequence_length != 0 + ? config.sequence_length + : metadata_sequence != 0 ? metadata_sequence + : layout ? layout->history : 0; + std::size_t feature = config.feature_size != 0 + ? config.feature_size + : metadata_feature != 0 ? metadata_feature + : layout ? layout->feature : 0; + std::size_t expected_observation = config.observation_size; + if (expected_observation == 0 && layout) + expected_observation = layout->observation; + if (layout && expected_observation != layout->observation) + throw std::invalid_argument("observation_size does not match rmcs_obs_layout dimensions"); input_shape_.resize(raw_input_shape.size()); if (raw_input_shape.size() == 1) { @@ -215,7 +284,7 @@ OnnxRuntime::OnnxRuntime(const Config& config) // Extra (non-obs) inputs: every one needs a constant from extra_inputs.*, // and every declared constant must match a model input. - std::map> remaining = config.extra_input_values; + auto remaining = config.extra_input_values; constant_slot_.assign(input_count, -1); for (std::size_t index = 0; index < input_count; ++index) { if (index == primary_index) @@ -226,7 +295,7 @@ OnnxRuntime::OnnxRuntime(const Config& config) "model input '" + input_names_[index] + "' has no constant value; declare it under policy_server extra_inputs." " in the vehicle YAML"); - const std::vector source = found->second; + const auto source = std::move(found->second); remaining.erase(found); const auto extra_type = session_.GetInputTypeInfo(index); @@ -234,9 +303,12 @@ OnnxRuntime::OnnxRuntime(const Config& config) throw std::invalid_argument( "extra input '" + input_names_[index] + "' must be a tensor"); const auto extra_info = extra_type.GetTensorTypeAndShapeInfo(); - if (extra_info.GetElementType() != ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT) + const auto extra_element_type = extra_info.GetElementType(); + if (extra_element_type != ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT + && extra_element_type != ONNX_TENSOR_ELEMENT_DATA_TYPE_INT64 + && extra_element_type != ONNX_TENSOR_ELEMENT_DATA_TYPE_BOOL) throw std::invalid_argument( - "extra input '" + input_names_[index] + "' element type must be float32"); + "extra input '" + input_names_[index] + "' element type must be float32, int64, or bool"); const auto raw_shape = extra_info.GetShape(); if (raw_shape.empty() || raw_shape.size() > 3) throw std::invalid_argument( @@ -244,6 +316,7 @@ OnnxRuntime::OnnxRuntime(const Config& config) ConstantInput constant; constant.name = input_names_[index]; + constant.type = extra_element_type; std::size_t elements = 1; std::size_t first_dim = 0; if (raw_shape.size() >= 2) { @@ -262,16 +335,60 @@ OnnxRuntime::OnnxRuntime(const Config& config) constant.shape.push_back(raw_shape[dim]); elements *= static_cast(raw_shape[dim]); } - if (source.size() != elements) + if (std::visit([](const auto& values) { return values.size(); }, source) != elements) throw std::invalid_argument( "extra input '" + constant.name + "' needs " + std::to_string(elements) - + " values, got " + std::to_string(source.size())); - constant.values.reserve(elements); - for (const double value : source) { - if (!std::isfinite(value)) + + " values, got " + + std::to_string(std::visit([](const auto& values) { return values.size(); }, source))); + constant.element_count = elements; + if (extra_element_type == ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT) { + constant.float_values.reserve(elements); + if (const auto* floats = std::get_if>(&source)) { + for (const double value : *floats) { + const float converted = static_cast(value); + if (!std::isfinite(converted)) + throw std::invalid_argument( + "extra input '" + constant.name + "' contains a non-finite or out-of-range float32 value"); + constant.float_values.push_back(converted); + } + } else if (const auto* integers = std::get_if>(&source)) { + for (const auto value : *integers) { + const float converted = static_cast(value); + if (!std::isfinite(converted)) + throw std::invalid_argument( + "extra input '" + constant.name + "' contains an out-of-range float32 value"); + constant.float_values.push_back(converted); + } + } else { throw std::invalid_argument( - "extra input '" + constant.name + "' contains a non-finite value"); - constant.values.push_back(static_cast(value)); + "extra input '" + constant.name + "' needs a float or integer list"); + } + } else if (extra_element_type == ONNX_TENSOR_ELEMENT_DATA_TYPE_INT64) { + if (const auto* integers = std::get_if>(&source)) { + constant.int64_values = *integers; + } else if (const auto* floats = std::get_if>(&source)) { + constant.int64_values.reserve(elements); + for (const double value : *floats) { + const auto promoted = static_cast(value); + if (!std::isfinite(value) || std::trunc(value) != value + || promoted < static_cast(std::numeric_limits::min()) + || promoted > static_cast(std::numeric_limits::max())) + throw std::invalid_argument( + "extra input '" + constant.name + "' contains a non-integral or out-of-range int64 value"); + constant.int64_values.push_back(static_cast(value)); + } + } else { + throw std::invalid_argument( + "extra input '" + constant.name + "' needs an integer or integral float list for int64 tensor"); + } + } else { + const auto* booleans = std::get_if>(&source); + if (!booleans) + throw std::invalid_argument( + "extra input '" + constant.name + "' needs a bool list for bool tensor"); + constant.bool_values = std::make_unique(elements); + for (std::size_t value_index = 0; value_index < elements; ++value_index) + constant.bool_values[value_index] = (*booleans)[value_index]; } constant_slot_[index] = static_cast(constants_.size()); constants_.push_back(std::move(constant)); @@ -332,9 +449,19 @@ void OnnxRuntime::run(std::span input, std::span output) { input_shape_.size())); } else { auto& constant = constants_[static_cast(constant_slot_[index])]; - input_tensors.push_back(Ort::Value::CreateTensor( - memory_info_, constant.values.data(), constant.values.size(), constant.shape.data(), - constant.shape.size())); + if (constant.type == ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT) { + input_tensors.push_back(Ort::Value::CreateTensor( + memory_info_, constant.float_values.data(), constant.element_count, + constant.shape.data(), constant.shape.size())); + } else if (constant.type == ONNX_TENSOR_ELEMENT_DATA_TYPE_INT64) { + input_tensors.push_back(Ort::Value::CreateTensor( + memory_info_, constant.int64_values.data(), constant.element_count, + constant.shape.data(), constant.shape.size())); + } else { + input_tensors.push_back(Ort::Value::CreateTensor( + memory_info_, constant.bool_values.get(), constant.element_count, + constant.shape.data(), constant.shape.size())); + } } } const char* output_names[] = {output_name_.c_str()}; diff --git a/src/policy/onnx_runtime.hpp b/src/policy/onnx_runtime.hpp index 4f3cc8d..0182c0d 100644 --- a/src/policy/onnx_runtime.hpp +++ b/src/policy/onnx_runtime.hpp @@ -3,9 +3,11 @@ #include #include #include +#include #include #include #include +#include #include #include @@ -14,6 +16,9 @@ namespace rmcs_rl { class OnnxRuntime { public: + using ExtraInputValues = std::variant< + std::vector, std::vector, std::vector>; + struct Config { std::string model_path; std::string input_name = "obs"; @@ -25,7 +30,7 @@ class OnnxRuntime { std::size_t action_size = 0; // 额外输入张量的常量值（键 = 模型输入名，值 = 展平的元素）， // 由 policy_server 的 extra_inputs. YAML 参数提供。 - std::map> extra_input_values; + std::map extra_input_values; }; struct Info { @@ -42,7 +47,16 @@ class OnnxRuntime { OnnxRuntime( const std::string& model_path, const std::string& input_name, const std::string& output_name) - : OnnxRuntime(Config{model_path, input_name, output_name}) {} + : OnnxRuntime(Config{ + .model_path = model_path, + .input_name = input_name, + .output_name = output_name, + .model_type = "auto", + .sequence_length = 0, + .feature_size = 0, + .observation_size = 0, + .action_size = 0, + .extra_input_values = {}}) {} [[nodiscard]] std::size_t input_size() const { return input_buffer_.size(); } [[nodiscard]] std::size_t output_size() const { return output_size_; } @@ -55,7 +69,11 @@ class OnnxRuntime { struct ConstantInput { std::string name; std::vector shape; - std::vector values; + ONNXTensorElementDataType type = ONNX_TENSOR_ELEMENT_DATA_TYPE_UNDEFINED; + std::size_t element_count = 0; + std::vector float_values; + std::vector int64_values; + std::unique_ptr bool_values; }; Ort::Env env_{ORT_LOGGING_LEVEL_WARNING, "rmcs_rl"}; diff --git a/src/policy/policy_model.hpp b/src/policy/policy_model.hpp index 552f681..4add7a9 100644 --- a/src/policy/policy_model.hpp +++ b/src/policy/policy_model.hpp @@ -27,7 +27,7 @@ class PolicyModel { std::optional obs_clip; std::optional action_clip; // 键 = 额外输入张量名，值 = 展平常量（来自 policy_server extra_inputs.） - std::map> extra_input_values; + std::map extra_input_values; }; struct Info { diff --git a/src/policy_server.cpp b/src/policy_server.cpp index 071c792..3f2e466 100644 --- a/src/policy_server.cpp +++ b/src/policy_server.cpp @@ -12,6 +12,7 @@ #include #include #include +#include #include #include @@ -72,25 +73,28 @@ class PolicyServer final : public rclcpp::Node { throw std::invalid_argument( "policy_server: extra_inputs entry must be extra_inputs."); const auto parameter = get_parameter(parameter_name); - std::vector values; + OnnxRuntime::ExtraInputValues values; switch (parameter.get_type()) { case rclcpp::ParameterType::PARAMETER_DOUBLE_ARRAY: values = parameter.as_double_array(); break; case rclcpp::ParameterType::PARAMETER_INTEGER_ARRAY: - for (const auto item : parameter.as_integer_array()) - values.push_back(static_cast(item)); + values = parameter.as_integer_array(); + break; + case rclcpp::ParameterType::PARAMETER_BOOL_ARRAY: + values = parameter.as_bool_array(); break; default: throw std::invalid_argument( - "policy_server: " + parameter_name + " must be a numeric list"); + "policy_server: " + parameter_name + " must be a float, integer, or bool list"); } - if (values.empty()) + if (std::visit([](const auto& items) { return items.empty(); }, values)) throw std::invalid_argument("policy_server: " + parameter_name + " is empty"); - for (const double value : values) - if (!std::isfinite(value)) - throw std::invalid_argument( - "policy_server: " + parameter_name + " contains a non-finite value"); + if (const auto* floats = std::get_if>(&values)) + for (const double value : *floats) + if (!std::isfinite(value)) + throw std::invalid_argument( + "policy_server: " + parameter_name + " contains a non-finite value"); config.extra_input_values.emplace(extra_name, std::move(values)); } config.normalization_from_metadata = bool_or(*this, "normalization_from_metadata", true); diff --git a/test/data/seq_layout_dynamic.onnx b/test/data/seq_layout_dynamic.onnx new file mode 100644 index 0000000000000000000000000000000000000000..c770858d777bba54b203b8f494314bd10f31f6ec GIT binary patch literal 426 zcmZvY!AiqG5QdYqHtPhj*4?B-#e5as{MsFlea;6`6XN+9iM}Vk9?x&0sy08b;=UT;24_$BU`b4 z7xwq!7T5)H@{1U#Hm!r!w8aokcWxD)coE5Xs_@xrJgCGyjB;8CRwPmG@TQ2zvABlT rj;PGoQ}$|2W-uJ!teb2IROU8jBlHbo*LKOQXVYJezWXk(Na0jOF6|RPy>bAZ4^$yjo zKktIR4OO~|R11Bh3S7Y!3TTS!G|-VqRNGc*Oy-f<26Cgz8DkF>EF+1doEO|7O)J zvw_BF`ubuR>yh#A9E*?T4oU0LduONo0?sXj9jN0IpXy)^6{}J_)9=7uAZ~(FU``J) z=C}$*!;u3x+pecr0^u|hsm7N}_qKHN=;lG;P}4+vgPY<$x$+vCTSn=A&vKT-yf^S@ z-h1%;yf^d$*(rO+;)8LbvjxMpmNZeJkTH|8Rd(9U4ke8lQPCH}$o;F7G6-kMOwTbI F{sMt=chLX< literal 0 HcmV?d00001 diff --git a/test/data/seq_layout_only.onnx b/test/data/seq_layout_only.onnx new file mode 100644 index 0000000000000000000000000000000000000000..71f6eaf4b8adf343e2d2e00dd10912396dedd735 GIT binary patch literal 411 zcmZut!D@p*5Ot%CGEy2hl!ib(#6wF;TWfAYNy(v;8H`_02QD4L>`iH;d;wpvO%C@wyaMmI+Znlt!i2K>fE^?3&3@wB7 zp+k;6hW-Xj%Un6Nb~LF|Cruj_Xj->M^Uk5n_OI7-8;(wg@)}Nx+a0Q*5z9o1 "object": +def _build(history: int, frame: int, metadata: dict, dynamic: bool = False) -> "object": import numpy as np import onnx from onnx import TensorProto, helper, numpy_helper @@ -37,7 +41,8 @@ def _build(history: int, frame: int, metadata: dict) -> "object": [flatten, matmul], "seq_policy", [helper.make_tensor_value_info( - "obs", TensorProto.FLOAT, ["batch", history, frame])], + "obs", TensorProto.FLOAT, + ["batch", "sequence", "feature"] if dynamic else ["batch", history, frame])], [helper.make_tensor_value_info("actions", TensorProto.FLOAT, ["batch", act])], [weight_init], ) @@ -67,10 +72,26 @@ def main() -> None: ok_path = DATA_DIR / "seq_identity.onnx" mismatch_path = DATA_DIR / "seq_history_mismatch.onnx" + layout_mismatch_path = DATA_DIR / "seq_layout_mismatch.onnx" + layout_only_path = DATA_DIR / "seq_layout_only.onnx" + layout_dynamic_path = DATA_DIR / "seq_layout_dynamic.onnx" onnx.save(_build(2, 3, ok_meta), ok_path) onnx.save(_build(2, 3, mismatch_meta), mismatch_path) + layout_mismatch_meta = dict(ok_meta, + rmcs_obs_layout="v3-history=3|constant:0+0+0@3") + onnx.save(_build(2, 3, layout_mismatch_meta), layout_mismatch_path) + layout_only_meta = { + "rmcs_obs_layout": shared["rmcs_obs_layout"], + "rmcs_actions_layout": shared["rmcs_actions_layout"], + "rmcs_model_type": shared["rmcs_model_type"], + } + onnx.save(_build(2, 3, layout_only_meta), layout_only_path) + onnx.save(_build(2, 3, layout_only_meta, dynamic=True), layout_dynamic_path) print(f"wrote {ok_path}") print(f"wrote {mismatch_path}") + print(f"wrote {layout_mismatch_path}") + print(f"wrote {layout_only_path}") + print(f"wrote {layout_dynamic_path}") if __name__ == "__main__": diff --git a/test/gen_typed_extra_input_fixture.py b/test/gen_typed_extra_input_fixture.py new file mode 100644 index 0000000..d033b31 --- /dev/null +++ b/test/gen_typed_extra_input_fixture.py @@ -0,0 +1,48 @@ +#!/usr/bin/env python3 +"""生成带 int64/bool 常量输入的确定性策略夹具。""" +import sys +from pathlib import Path + +DATA_DIR = Path(__file__).resolve().parent / "data" + + +def main() -> None: + import onnx + from onnx import TensorProto, helper + + cast_ids = helper.make_node("Cast", ["position_ids"], ["position_float"], + name="cast_position", to=TensorProto.FLOAT) + cast_mask = helper.make_node("Cast", ["attention_mask"], ["mask_float"], + name="cast_mask", to=TensorProto.FLOAT) + add_position = helper.make_node("Add", ["obs", "position_float"], ["with_position"], + name="add_position") + add_mask = helper.make_node("Add", ["with_position", "mask_float"], ["actions"], + name="add_mask") + graph = helper.make_graph( + [cast_ids, cast_mask, add_position, add_mask], + "typed_extra_input_policy", + [ + helper.make_tensor_value_info("obs", TensorProto.FLOAT, ["batch", 2]), + helper.make_tensor_value_info("position_ids", TensorProto.INT64, ["batch", 2]), + helper.make_tensor_value_info("attention_mask", TensorProto.BOOL, ["batch", 2]), + ], + [helper.make_tensor_value_info("actions", TensorProto.FLOAT, ["batch", 2])], + ) + model = helper.make_model(graph, opset_imports=[helper.make_opsetid("", 17)]) + model.ir_version = 8 + model.producer_name = "rmcs_rl/gen_typed_extra_input_fixture" + for key, value in { + "rmcs_obs_layout": "v3-history=1|constant:0+0@2", + "rmcs_actions_layout": "v2|#0:a|#1:b", + }.items(): + entry = model.metadata_props.add() + entry.key = key + entry.value = value + onnx.checker.check_model(model) + path = DATA_DIR / "typed_extra_input_identity.onnx" + onnx.save(model, path) + print(f"wrote {path}") + + +if __name__ == "__main__": + sys.exit(main()) diff --git a/test/runtime_test.cpp b/test/runtime_test.cpp index becb364..c597a92 100644 --- a/test/runtime_test.cpp +++ b/test/runtime_test.cpp @@ -171,6 +171,28 @@ TEST(PolicyModel, RejectsSequenceHistoryMetadataMismatch) { EXPECT_THROW(PolicyModel{config}, std::invalid_argument); } +TEST(PolicyModel, RejectsSequenceLayoutHistoryMismatch) { + PolicyModel::Config config; + config.path = RMCS_RL_SEQ_LAYOUT_MISMATCH_FIXTURE; + EXPECT_THROW(PolicyModel{config}, std::invalid_argument); +} + +TEST(PolicyModel, LoadsSequenceUsingRequiredLayoutOnly) { + PolicyModel::Config config; + config.path = RMCS_RL_SEQ_LAYOUT_ONLY_FIXTURE; + PolicyModel model{config}; + EXPECT_EQ(model.info().sequence_length, 2u); + EXPECT_EQ(model.info().feature_size, 3u); +} + +TEST(PolicyModel, LoadsDynamicSequenceUsingRequiredLayoutOnly) { + PolicyModel::Config config; + config.path = RMCS_RL_SEQ_LAYOUT_DYNAMIC_FIXTURE; + PolicyModel model{config}; + EXPECT_EQ(model.info().sequence_length, 2u); + EXPECT_EQ(model.info().feature_size, 3u); +} + TEST(PolicyModel, RejectsTransformerTypeOnRank2Input) { PolicyModel::Config config; config.path = RMCS_RL_IDENTITY_FIXTURE; @@ -181,7 +203,7 @@ TEST(PolicyModel, RejectsTransformerTypeOnRank2Input) { TEST(PolicyModel, FeedsExtraInputConstants) { PolicyModel::Config config; config.path = RMCS_RL_EXTRA_FIXTURE; - config.extra_input_values["offset"] = {10.0}; + config.extra_input_values["offset"] = std::vector{10.0}; PolicyModel model{config}; ASSERT_EQ(model.info().obs_size, 2u); ASSERT_EQ(model.info().action_size, 2u); @@ -200,15 +222,35 @@ TEST(PolicyModel, RejectsMissingExtraInputDeclaration) { TEST(PolicyModel, RejectsExtraInputWithoutMatchingModelInput) { PolicyModel::Config config; config.path = RMCS_RL_EXTRA_FIXTURE; - config.extra_input_values["offset"] = {10.0}; - config.extra_input_values["bogus"] = {1.0}; + config.extra_input_values["offset"] = std::vector{10.0}; + config.extra_input_values["bogus"] = std::vector{1.0}; EXPECT_THROW(PolicyModel{config}, std::invalid_argument); } TEST(PolicyModel, RejectsWrongExtraInputValueCount) { PolicyModel::Config config; config.path = RMCS_RL_EXTRA_FIXTURE; - config.extra_input_values["offset"] = {1.0, 2.0}; + config.extra_input_values["offset"] = std::vector{1.0, 2.0}; + EXPECT_THROW(PolicyModel{config}, std::invalid_argument); +} + +TEST(PolicyModel, FeedsTypedExtraInputConstants) { + PolicyModel::Config config; + config.path = RMCS_RL_TYPED_EXTRA_FIXTURE; + config.extra_input_values["position_ids"] = std::vector{10, 20}; + config.extra_input_values["attention_mask"] = std::vector{true, false}; + PolicyModel model{config}; + std::array action{}; + std::string error; + ASSERT_TRUE(model.run(std::array{1., 2.}, action, error)) << error; + EXPECT_EQ(action, (std::array{12.0, 22.0})); +} + +TEST(PolicyModel, RejectsWrongTypedExtraInputConstants) { + PolicyModel::Config config; + config.path = RMCS_RL_TYPED_EXTRA_FIXTURE; + config.extra_input_values["position_ids"] = std::vector{true, false}; + config.extra_input_values["attention_mask"] = std::vector{true, false}; EXPECT_THROW(PolicyModel{config}, std::invalid_argument); } diff --git a/test/test_layout_contract.sh b/test/test_layout_contract.sh index 0c4364e..38b9ceb 100755 --- a/test/test_layout_contract.sh +++ b/test/test_layout_contract.sh @@ -288,6 +288,21 @@ run_expect 1 "(j) YAML 声明了模型没有的额外输入 → FAIL" \ "$PY" "$TOOLS/check_policy_contract.py" "$MODEL" --config "$FIXTURE_EXTRA_UNKNOWN" expect_msg "extra_inputs match model" "多余声明提示" +run_expect 0 "typed extra_inputs（int64 + bool）自检 → PASS" \ + "$PY" "$TOOLS/check_policy_contract.py" \ + "$PKG/test/data/typed_extra_input_identity.onnx" --obs 2 --act 2 +expect_msg "dtype" "typed extra_inputs 类型校验" + +run_expect 0 "仅布局签名解析动态 rank-3 → PASS" \ + "$PY" "$TOOLS/check_policy_contract.py" \ + "$PKG/test/data/seq_layout_dynamic.onnx" +expect_msg "rank-3 layout history" "动态序列由布局解析" + +run_expect 1 "模型 T 与布局 history 不符 → FAIL" \ + "$PY" "$TOOLS/check_policy_contract.py" \ + "$PKG/test/data/seq_layout_mismatch.onnx" +expect_msg "metadata history == layout history" "布局与序列 metadata 不一致" + echo echo "==== 结果：PASS=$PASS FAIL=$FAIL ====" [ "$FAIL" = 0 ] || exit 1 diff --git a/tool/check_policy_contract.py b/tool/check_policy_contract.py index 7d6e901..2c664d9 100644 --- a/tool/check_policy_contract.py +++ b/tool/check_policy_contract.py @@ -4,9 +4,10 @@ Two modes: * self-check (no --config; used by CI, deployment YAML lives in the RMCS repo): - model loads; primary input "obs" / one output "actions"; float32; rank 1/2/3; + model loads; primary input "obs" / one output "actions" are float32; rank 1/2/3; MLP uses rank 2 or rank 3 and Transformer uses rank 3. Extra (non-obs) - inputs are allowed; with --config they must match policy_server extra_inputs. + inputs may be float32, int64, or bool; with --config they must match + policy_server extra_inputs. Layout metadata is OPTIONAL: - missing / v1 -> SKIP (stamped layout metadata is optional for model-only self-check) - present v2 -> signatures must be internally consistent with the tensor @@ -152,13 +153,14 @@ def _dummy_inference(report, model_path, obs_size, act_size, model_type, else: obs = np.zeros((1, obs_size), dtype=np.float32) feed = {"obs": obs} - for name, (shape, values) in (extra_specs or {}).items(): + for name, (shape, values, dtype) in (extra_specs or {}).items(): count = 1 for dim in shape: count *= dim if values is None: - values = [1.0] * count - feed[name] = np.asarray(values, dtype=np.float32).reshape(shape) + values = [True] * count if dtype == "bool" else [1] * count + np_dtype = {"float32": np.float32, "int64": np.int64, "bool": np.bool_}[dtype] + feed[name] = np.asarray(values, dtype=np_dtype).reshape(shape) actions = session.run(["actions"], feed)[0] except Exception as exc: report.check("dummy inference", False, f"{type(exc).__name__}: {exc}") @@ -269,9 +271,13 @@ def _dtype_name(value_info): elem = value_info.type.tensor_type.elem_type return "float32" if elem == TensorProto.FLOAT else TensorProto.DataType.Name(elem).lower() - dtype_ok = (all(value.type.tensor_type.elem_type == TensorProto.FLOAT for value in inputs) - and out.type.tensor_type.elem_type == TensorProto.FLOAT) - report.check("dtype float32", dtype_ok, + primary_dtype_ok = inp.type.tensor_type.elem_type == TensorProto.FLOAT + output_dtype_ok = out.type.tensor_type.elem_type == TensorProto.FLOAT + extra_dtype_ok = all(value.type.tensor_type.elem_type in ( + TensorProto.FLOAT, TensorProto.INT64, TensorProto.BOOL) + for value in inputs if value.name != "obs") + dtype_ok = primary_dtype_ok and output_dtype_ok and extra_dtype_ok + report.check("dtype", dtype_ok, f"inputs={[_dtype_name(value) for value in inputs]} actions={_dtype_name(out)}") in_shape, out_shape = _shape_of(inp), _shape_of(out) meta = {prop.key: prop.value for prop in model.metadata_props} @@ -346,6 +352,10 @@ def _dtype_name(value_info): runtime_shape.append(dim) elements *= dim values = None + dtype = _dtype_name(next(value for value in inputs if value.name == name)) + if dtype not in ("float32", "int64", "bool"): + ok = False + detail += f" dtype={dtype}（运行时仅支持 float32/int64/bool）" if ok and args.config and name in declared_extra: raw_values = declared_extra[name] if not isinstance(raw_values, list) or not raw_values: @@ -353,13 +363,27 @@ def _dtype_name(value_info): detail += " extra_inputs 值必须是非空列表" else: try: - values = [float(item) for item in raw_values] - except (TypeError, ValueError): + if dtype == "float32": + if any(isinstance(item, bool) for item in raw_values): + raise ValueError + values = [float(item) for item in raw_values] + elif dtype == "int64": + if any(isinstance(item, bool) for item in raw_values): + raise ValueError + values = [int(item) for item in raw_values] + if any(isinstance(item, float) and item != int(item) + for item in raw_values): + raise ValueError + else: + if any(not isinstance(item, bool) for item in raw_values): + raise ValueError + values = list(raw_values) + except (TypeError, ValueError, OverflowError): ok = False values = None - detail += " 含非数值元素" + detail += f" 不符合 {dtype} 元素类型" else: - if any(not math.isfinite(item) for item in values): + if dtype == "float32" and any(not math.isfinite(item) for item in values): ok = False detail += " 含非有限值" values = None @@ -369,7 +393,26 @@ def _dtype_name(value_info): values = None report.check(f"extra input {name}", ok, detail) if ok: - extra_specs[name] = (tuple(runtime_shape), values) + extra_specs[name] = (tuple(runtime_shape), values, dtype) + + layout_sequence = layout_feature = 0 + obs_layout_text = meta.get("rmcs_obs_layout", "") + if obs_layout_text.startswith("v3-history="): + try: + header, separator, entries = obs_layout_text.partition("|") + if not separator or not entries: + raise ValueError("缺少观测词条") + layout_sequence = int(header.removeprefix("v3-history=")) + if layout_sequence < 1: + raise ValueError("history 必须为正整数") + layout_observation = layout.obs_signature_dim(obs_layout_text) + layout_feature = layout_observation // layout_sequence + except (ValueError, layout.LayoutError) as exc: + report.check("rmcs_obs_layout dimensions", False, str(exc)) + layout_sequence = layout_feature = 0 + if len(in_shape) == 3: + report.check("rank-3 layout history", layout_sequence > 0 and layout_feature > 0, + f"layout T={layout_sequence} F={layout_feature}") history_length = layout.history_length(args.config, args.node) if args.config else 1 metadata_sequence = metadata_feature = 0 @@ -389,6 +432,14 @@ def _dtype_name(value_info): metadata_feature = value config_feature_size = obs_size // history_length if obs_size is not None else None if args.config: + if layout_sequence: + report.check("layout history == config history_length", + layout_sequence == history_length, + f"layout={layout_sequence} history_length={history_length}") + if layout_feature and config_feature_size: + report.check("layout frame == config frame size", + layout_feature == config_feature_size, + f"layout={layout_feature} 单帧={config_feature_size}") if metadata_sequence: report.check("metadata history == config history_length", metadata_sequence == history_length, @@ -403,11 +454,23 @@ def _dtype_name(value_info): if args.feature_size and config_feature_size and args.feature_size != config_feature_size: report.check("--feature-size == config frame size", False, f"--feature-size={args.feature_size} 单帧={config_feature_size}") + if layout_sequence and metadata_sequence: + report.check("metadata history == layout history", metadata_sequence == layout_sequence, + f"rmcs_history_length={metadata_sequence} layout={layout_sequence}") + if layout_feature and metadata_feature: + report.check("metadata frame == layout frame", metadata_feature == layout_feature, + f"rmcs_obs_frame_size={metadata_feature} layout={layout_feature}") + if layout_sequence and args.sequence_length: + report.check("--sequence-length == layout history", args.sequence_length == layout_sequence, + f"--sequence-length={args.sequence_length} layout={layout_sequence}") + if layout_feature and args.feature_size: + report.check("--feature-size == layout frame", args.feature_size == layout_feature, + f"--feature-size={args.feature_size} layout={layout_feature}") input_tail = in_shape[0:] if len(in_shape) == 1 else in_shape[1:] - sequence_length = args.sequence_length or metadata_sequence or ( + sequence_length = args.sequence_length or metadata_sequence or layout_sequence or ( history_length if len(in_shape) == 3 and args.config else None) - feature_size = args.feature_size or metadata_feature or ( + feature_size = args.feature_size or metadata_feature or layout_feature or ( config_feature_size if len(in_shape) == 3 and args.config else None) if len(in_shape) == 3: declared_sequence, declared_feature = input_tail From 77e7db10cbbca7b65c20abcd8e4854c599ad6362 Mon Sep 17 00:00:00 2001 From: ZGZ713912 Date: Sun, 4 Oct 2026 11:20:14 +0800 Subject: [PATCH 7/9] feat: allow unstamped policy deployment --- include/rmcs_rl/rl_bridge/config.hpp | 1 - src/policy/onnx_runtime.cpp | 5 +++-- src/policy/policy_model.cpp | 23 ++++++----------------- src/policy_server.cpp | 6 ++++-- src/rl_bridge.cpp | 8 -------- src/rl_bridge/config.cpp | 2 -- 6 files changed, 13 insertions(+), 32 deletions(-) diff --git a/include/rmcs_rl/rl_bridge/config.hpp b/include/rmcs_rl/rl_bridge/config.hpp index 7b5ab24..3d551a2 100644 --- a/include/rmcs_rl/rl_bridge/config.hpp +++ b/include/rmcs_rl/rl_bridge/config.hpp @@ -24,7 +24,6 @@ struct BridgeConfig { double policy_rate = 50.0; double max_action_age = 0.04; std::chrono::nanoseconds pub_period{}; - std::uint64_t expected_model_id = 0; InvalidMode invalid_mode = InvalidMode::kNaN; std::string enable_path; bool enable_default = false; diff --git a/src/policy/onnx_runtime.cpp b/src/policy/onnx_runtime.cpp index 8b0e4a6..e7d63a3 100644 --- a/src/policy/onnx_runtime.cpp +++ b/src/policy/onnx_runtime.cpp @@ -198,8 +198,9 @@ OnnxRuntime::OnnxRuntime(const Config& config) const auto metadata_sequence = parse_positive(metadata("rmcs_history_length"), "rmcs_history_length"); const auto metadata_feature = parse_positive(metadata("rmcs_obs_frame_size"), "rmcs_obs_frame_size"); const auto layout = layout_dimensions(metadata("rmcs_obs_layout")); - if (raw_input_shape.size() == 3 && !layout) - throw std::invalid_argument("rank-3 model requires an rmcs_obs_layout v3-history signature"); + if (raw_input_shape.size() == 3 && !layout && (config.sequence_length == 0 || config.feature_size == 0)) + throw std::invalid_argument( + "rank-3 model without metadata requires sequence_length and feature_size"); if (layout && metadata_sequence != 0 && metadata_sequence != layout->history) throw std::invalid_argument("rmcs_history_length does not match rmcs_obs_layout"); if (layout && metadata_feature != 0 && metadata_feature != layout->feature) diff --git a/src/policy/policy_model.cpp b/src/policy/policy_model.cpp index 8a6f548..dda66ff 100644 --- a/src/policy/policy_model.cpp +++ b/src/policy/policy_model.cpp @@ -64,27 +64,16 @@ PolicyModel::PolicyModel(const Config& config) info_.sequence_length = runtime_.info().sequence_length; info_.feature_size = runtime_.info().feature_size; std::string error; - if (!model_id_of_file(config.path, info_.model_id, error)) - throw std::runtime_error(error); + // Model identity and layout metadata are intentionally optional. The bridge owns the + // observation/action contract from YAML; the policy server only validates tensor sizes. + model_id_of_file(config.path, info_.model_id, error); info_.obs_signature = runtime_.metadata("rmcs_obs_layout").value_or(""); info_.actions_signature = runtime_.metadata("rmcs_actions_layout").value_or(""); info_.version = runtime_.metadata("policy_version").value_or(""); - if (info_.obs_signature.empty() || info_.actions_signature.empty()) - throw std::invalid_argument( - "model is missing rmcs_obs_layout / rmcs_actions_layout; " - "stamp it with tool/stamp_layout_metadata.py before deploying"); - info_.layout_hash = rmcs_rl::layout_hash( - info_.obs_signature, info_.actions_signature, info_.obs_size, info_.action_size); - if (const auto declared = runtime_.metadata("policy_layout_hash"); - declared && !declared->empty()) { - std::size_t consumed = 0; - const auto hash = std::stoull(*declared, &consumed, 16); - if (consumed != declared->size() || hash != info_.layout_hash) - throw std::invalid_argument( - "policy_layout_hash does not match layout metadata: expected " - + hex16(info_.layout_hash)); - } + if (!info_.obs_signature.empty() && !info_.actions_signature.empty()) + info_.layout_hash = rmcs_rl::layout_hash( + info_.obs_signature, info_.actions_signature, info_.obs_size, info_.action_size); load_normalization(config); obs_buffer_.resize(info_.obs_size); diff --git a/src/policy_server.cpp b/src/policy_server.cpp index 3f2e466..d04a5e3 100644 --- a/src/policy_server.cpp +++ b/src/policy_server.cpp @@ -133,7 +133,7 @@ class PolicyServer final : public rclcpp::Node { private: void on_observation(msg::Observation::UniquePtr message) { const auto& info = model_->info(); - if (message->layout_hash != info.layout_hash) { + if (info.layout_hash != 0 && message->layout_hash != info.layout_hash) { if (!layout_mismatch_logged_) { layout_mismatch_logged_ = true; RCLCPP_ERROR( @@ -154,7 +154,9 @@ class PolicyServer final : public rclcpp::Node { } action.header.stamp = get_clock()->now(); action.obs_seq = message->obs_seq; - action.layout_hash = info.layout_hash; + // The bridge is the source of truth for the YAML-defined layout when a model has no + // stamped metadata. Preserve the observation contract on the action message. + action.layout_hash = message->layout_hash; action.model_id = info.model_id; action_publisher_->publish(action); const auto elapsed = diff --git a/src/rl_bridge.cpp b/src/rl_bridge.cpp index e175f76..57bef8f 100644 --- a/src/rl_bridge.cpp +++ b/src/rl_bridge.cpp @@ -261,14 +261,6 @@ class RlBridge final "(policy process and bridge disagree; refusing to output actions)", hex16(snapshot.layout_hash).c_str(), hex16(layout_hash_).c_str()); } - } else if ( - config_.expected_model_id != 0 && snapshot.model_id != config_.expected_model_id) { - if (contract_ok_) { - contract_ok_ = false; - RCLCPP_FATAL( - get_logger(), "model mismatch: action model_id=%s != expected_model_id=%s", - hex16(snapshot.model_id).c_str(), hex16(config_.expected_model_id).c_str()); - } } } diff --git a/src/rl_bridge/config.cpp b/src/rl_bridge/config.cpp index ab9d6d4..25d43df 100644 --- a/src/rl_bridge/config.cpp +++ b/src/rl_bridge/config.cpp @@ -82,8 +82,6 @@ BridgeConfig load_bridge_config(rclcpp::Node& node) { config.max_action_age = number_or(node, "max_action_age", 2.0 / config.policy_rate); if (!(config.max_action_age > 0.0) || !is_finite(config.max_action_age)) throw std::invalid_argument("RlBridge: max_action_age must be finite and > 0"); - config.expected_model_id = - parse_u64(string_or(node, "expected_model_id", "0"), "expected_model_id"); const std::string invalid = string_or(node, "invalid_value", "nan"); if (invalid == "nan") From f98953f7b4daa5da14d82b25cb92f7721cda81cb Mon Sep 17 00:00:00 2001 From: ZGZ713912 Date: Sat, 10 Oct 2026 19:49:53 +0800 Subject: [PATCH 8/9] feat(models): add new model files and remove obsolete ones --- README.md | 50 ++++++++++++++---- models/deformable_sps_V2_N.onnx | Bin 202420 -> 0 bytes models/deformable_v2_transformer.onnx | Bin 0 -> 405589 bytes models/deformable_v3_transformer.onnx | Bin 0 -> 410235 bytes ...heel_leg_v1.onnx => wheel_leg_v1_MLP.onnx} | Bin models/wheel_leg_v3.onnx | Bin 0 -> 204969 bytes models/wheel_leg_v3_test.onnx | Bin 0 -> 204969 bytes 7 files changed, 40 insertions(+), 10 deletions(-) delete mode 100644 models/deformable_sps_V2_N.onnx create mode 100644 models/deformable_v2_transformer.onnx create mode 100644 models/deformable_v3_transformer.onnx rename models/{wheel_leg_v1.onnx => wheel_leg_v1_MLP.onnx} (100%) create mode 100644 models/wheel_leg_v3.onnx create mode 100644 models/wheel_leg_v3_test.onnx diff --git a/README.md b/README.md index 7a66c53..694c161 100644 --- a/README.md +++ b/README.md @@ -98,32 +98,62 @@ policy_server: rl_obs_size: 208 ``` -盖章默认写入序列键（`rmcs_history_length`/`rmcs_obs_frame_size`，取自 YAML）；部署端还会 -从必需的 `rmcs_obs_layout` 中读取 `v3-history`，防止只依赖可选 metadata。 -`rmcs_model_type` 可选，缺省由部署端按输入 rank 推断： +### 模型盖章 + +部署模型必须含 `rmcs_obs_layout`、`rmcs_actions_layout`，建议同时带 `policy_layout_hash` +和版本。盖章按**当前 YAML** 生成签名，所以顺序是先核对训练布局、再盖章、再同步 YAML、 +最后复验。 + +**1. 装依赖（一次性）**：需要一个带 `onnx` 与 `PyYAML` 的 Python。没有就运行： ```sh -python3 src/rmcs_rl/tool/stamp_layout_metadata.py \ - --model policy.onnx --from-config <车辆配置.yaml> --node rl_bridge \ - --model-type transformer +bash src/rmcs_rl/tool/install_model_tools.sh ``` -新模型先核对训练的观测顺序、坐标、基准角、缩放和频率，再盖章： +它创建 `/opt/rmcs-tools/venv`；已有环境则 `export RMCS_ONNX_PYTHON=/bin/python` 直接跳过安装。 +`stamp_model.sh` 自己会依次找 `RMCS_ONNX_PYTHON`、该 venv、`python3`；下面直接调用 +`python3` 的脚本若系统解释器没装 `onnx`，改用 `/bin/python`。 + +**2. 核对训练布局**：逐条确认观测顺序、坐标、基准角、缩放和频率与当前 YAML 一致。 +YAML 写错会盖出「自洽但错误」的签名，后续校验照样通过，所以这一步不能省。 + +**3. 盖章**：推荐用一键脚本。它先提示模型布局与 YAML 是否一致（不一致只警告不阻断）， +盖完立即复验，最后打印要手工改的 YAML 两行： ```sh bash src/rmcs_rl/tool/stamp_model.sh <模型.onnx> --config <车辆配置.yaml> --version <版本> ``` -按工具输出同步 `policy_server.rl_model_path`、`rl_bridge.expected_model_id`，然后验证： +模型放在 `src/rmcs_rl/models/` 下时只写文件名；`--config` 缺省为 +`src/rmcs_bringup/config/wheel-leg-infantry-rl.yaml`，`--node` 缺省 `rl_bridge`。 +带历史帧或特殊结构时补 `--model-type mlp|transformer|generic`、`--sequence-length N`、 +`--feature-size N`。脚本只盖 metadata，不改计算图/权重，也不改 YAML——YAML 由你手工改最安全。 + +只需写 metadata、不自动复验时用底层脚本。盖章默认写入序列键（`rmcs_history_length`/ +`rmcs_obs_frame_size`，取自 YAML）；部署端还会从必需的 `rmcs_obs_layout` 中读取 +`v3-history`，防止只依赖可选 metadata。`rmcs_model_type` 可选，缺省由部署端按输入 rank 推断： + +```sh +python3 src/rmcs_rl/tool/stamp_layout_metadata.py \ + --model policy.onnx --from-config <车辆配置.yaml> --node rl_bridge \ + --model-type transformer +``` + +**4. 同步 YAML 两处**：按工具输出手工改 `policy_server.rl_model_path` 与 +`rl_bridge.expected_model_id`，不要让脚本改配置文件。 + +**5. 复验**： ```sh python3 src/rmcs_rl/tool/check_policy_contract.py <模型.onnx> --config <车辆配置.yaml> --node rl_bridge --expect-model-id ``` +**6. 重启 RMCS**：更新模型或配置后必须重启。模型或布局不匹配会锁存拒绝动作，需要重启恢复。 + 盖章只写元数据；布局匹配不能证明训练侧的坐标或动作含义正确。 -更新模型或配置后重启 RMCS。模型或布局不匹配会锁存拒绝动作，需要重启恢复。 -当前部署使用 `models/deformable_sps_V1.onnx`；其 `rmcs_obs_layout`、 +当前部署使用 `models/deformable_v2_transformer.onnx`（8 帧历史 × 32 维单帧，输入 rank-3 +`obs[1,8,32]`，`rmcs_model_type=transformer`）；其 `rmcs_obs_layout`、 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z*D70sIHLv%UrF(<{AHkaFdKWytzc{0E8Wmg|3rT(&Y2<#r(9twfs(l4M=G5Dnjre1*~#d=AoA$>6|tdQq}ZgpMO<}k9;@v1W~6L+VCh!0<lG{6o|1>owJ_#PU!(lh(>~IH}oxbSTa}DDiE|I<81un*daAFXmjiZW|fywW+ z?6&u8HgoAbCX+Uqrpz6R8_gStlBxlF(sl@D9^Nj>>)H*c>;B+A1v}Q^I~6me7sBrc z0z1t~aCnW_ik;t;@Vapy`O-WTV~su#<6RwVd85B_Kk6!@G z&sL#h*S#daW|@G-tVp=-xCm_K3}%VZ&vBO9RPc;XhY@O{==VweWbrmTHb$cXR@A+L z?p~O&;E1W-jd}Jd-Gms?@^tUWHb9?ift)yPZ7t` z)wY&QXMpW6&biKQ^mhXVAPBrU3{?~ps=BeHL zek7(_W1WA8q5U(rp<7GY)YZLl89Vn1Ug)!JkLa>xem-gMipXWwA+H+uepx?x z@3gH^b|OCFcJ9k_ZPuIa2G%6j`^q%KV@{==5Dy=FU2&<_iLQNG=4Tdcl z;96136sq4!zdR!~H77nNHC?|bM?W*SR6j8eh zNg!4R+J@Rj+Q!-@+NKU>HNYq?E=kNQu`<*)KtKocqAV_9aAJWbD_DXFE;Fi8Hh}w} zM%fU;28BwEvXK=$%xaX4p&W>m2~yzHD4Rm%zz#0b;1Vjx&&f=#gxV4hOn(_dLIxG7 z$tFoAW(J8C$;K9m$;swLqFj7Xm1U_##lZ9~#B8i*P$U6$EHotp(@b7^Nrn)kVUZ+M V29)O0iV|~E Date: Tue, 13 Oct 2026 22:49:28 +0800 Subject: [PATCH 9/9] feat(action_feedback): implement action feedback history --- .../rl_bridge/action_feedback_history.hpp | 50 ++++++++++++++++ include/rmcs_rl/rl_bridge/config.hpp | 2 + .../rmcs_rl/rl_bridge/observation_history.hpp | 13 ++++- .../rl_bridge/observation_timeline.hpp | 10 +++- src/rl_bridge.cpp | 57 ++++++++++++++++--- src/rl_bridge/config.cpp | 7 +++ src/rl_bridge/observation_history.cpp | 35 +++++++++++- test/runtime_test.cpp | 53 +++++++++++++++++ 8 files changed, 215 insertions(+), 12 deletions(-) create mode 100644 include/rmcs_rl/rl_bridge/action_feedback_history.hpp diff --git a/include/rmcs_rl/rl_bridge/action_feedback_history.hpp b/include/rmcs_rl/rl_bridge/action_feedback_history.hpp new file mode 100644 index 0000000..9ca937a --- /dev/null +++ b/include/rmcs_rl/rl_bridge/action_feedback_history.hpp @@ -0,0 +1,50 @@ +#pragma once + +#include +#include +#include +#include +#include +#include +#include + +namespace rmcs_rl { + +// Prior-action features retain their training delay when inference is faster. +class ActionFeedbackHistory { +public: + using Clock = std::chrono::steady_clock; + explicit ActionFeedbackHistory(std::size_t size) : values_(size, 0.0) {} + + void store(Clock::time_point observation_time, std::span action) { + if (action.size() != values_.size()) + throw std::invalid_argument("action feedback size mismatch"); + if (!samples_.empty() && observation_time <= samples_.back().time) + return; + samples_.push_back({observation_time, std::vector{action.begin(), action.end()}}); + } + + const std::vector& sample(Clock::time_point now, std::chrono::nanoseconds delay) { + const auto target = now - delay; + while (samples_.size() > 1 && samples_[1].time <= target) + samples_.pop_front(); + if (!samples_.empty() && samples_.front().time <= target) + values_ = samples_.front().action; + return values_; + } + + void reset() { + samples_.clear(); + std::fill(values_.begin(), values_.end(), 0.0); + } + +private: + struct Sample { + Clock::time_point time; + std::vector action; + }; + std::deque samples_; + std::vector values_; +}; + +} // namespace rmcs_rl diff --git a/include/rmcs_rl/rl_bridge/config.hpp b/include/rmcs_rl/rl_bridge/config.hpp index 3d551a2..5d17a36 100644 --- a/include/rmcs_rl/rl_bridge/config.hpp +++ b/include/rmcs_rl/rl_bridge/config.hpp @@ -24,10 +24,12 @@ struct BridgeConfig { double policy_rate = 50.0; double max_action_age = 0.04; std::chrono::nanoseconds pub_period{}; + std::chrono::nanoseconds history_period{}; InvalidMode invalid_mode = InvalidMode::kNaN; std::string enable_path; bool enable_default = false; std::string reset_path; + std::string flat_hold_path; }; BridgeConfig load_bridge_config(rclcpp::Node& node); diff --git a/include/rmcs_rl/rl_bridge/observation_history.hpp b/include/rmcs_rl/rl_bridge/observation_history.hpp index b08f31d..a6456ba 100644 --- a/include/rmcs_rl/rl_bridge/observation_history.hpp +++ b/include/rmcs_rl/rl_bridge/observation_history.hpp @@ -1,6 +1,8 @@ #pragma once #include +#include +#include #include #include @@ -9,13 +11,22 @@ namespace rmcs_rl { // Frames are oldest first; startup and reset fill the history with the first valid frame. class ObservationHistory { public: - ObservationHistory(std::size_t frame_size, std::size_t history_length); + using Clock = std::chrono::steady_clock; + ObservationHistory(std::size_t frame_size, std::size_t history_length, + std::chrono::nanoseconds sample_period = {}); const std::vector& append(std::span frame); + const std::vector& append(std::span frame, Clock::time_point now); void reset(); private: std::size_t frame_size_; std::vector values_; + struct Sample { + Clock::time_point time; + std::vector frame; + }; + std::chrono::nanoseconds sample_period_{}; + std::deque samples_; bool initialized_ = false; }; diff --git a/include/rmcs_rl/rl_bridge/observation_timeline.hpp b/include/rmcs_rl/rl_bridge/observation_timeline.hpp index bd322d2..43b0261 100644 --- a/include/rmcs_rl/rl_bridge/observation_timeline.hpp +++ b/include/rmcs_rl/rl_bridge/observation_timeline.hpp @@ -11,10 +11,14 @@ class ObservationTimeline { using Clock = std::chrono::steady_clock; bool due(Clock::time_point now, std::chrono::nanoseconds period) const { - return !started_ || now - current_time_ >= period; + return !started_ || now - scheduled_time_ >= period; } - std::uint64_t publish(Clock::time_point now) { + std::uint64_t publish(Clock::time_point now, std::chrono::nanoseconds period = {}) { + if (!started_ || period.count() <= 0) + scheduled_time_ = now; + else + scheduled_time_ += period * ((now - scheduled_time_) / period); previous_valid_ = started_; previous_time_ = current_time_; current_time_ = now; @@ -34,6 +38,7 @@ class ObservationTimeline { // Keep IDs monotonic so a delayed action cannot match a new frame after reset. started_ = previous_valid_ = false; current_time_ = previous_time_ = {}; + scheduled_time_ = {}; } [[nodiscard]] std::uint64_t sequence() const { return sequence_; } @@ -41,6 +46,7 @@ class ObservationTimeline { private: Clock::time_point current_time_{}; Clock::time_point previous_time_{}; + Clock::time_point scheduled_time_{}; std::uint64_t sequence_ = 0; bool started_ = false; bool previous_valid_ = false; diff --git a/src/rl_bridge.cpp b/src/rl_bridge.cpp index 57bef8f..b94fa7f 100644 --- a/src/rl_bridge.cpp +++ b/src/rl_bridge.cpp @@ -22,6 +22,7 @@ #include #include +#include #include #include #include @@ -43,7 +44,8 @@ class RlBridge final get_component_name(), rclcpp::NodeOptions{}.automatically_declare_parameters_from_overrides(true)) , config_(load_bridge_config(*this)) - , history_(config_.obs_frame_size, config_.history_length) { + , history_(config_.obs_frame_size, config_.history_length, config_.history_period) + , action_feedback_(config_.action_size) { for (const auto& term : config_.action_terms) { action_outputs_.push_back(std::make_unique>()); @@ -100,7 +102,22 @@ class RlBridge final const auto now = std::chrono::steady_clock::now(); maybe_handle_reset_(); - maybe_publish_observation_(now); + const bool enabled = read_enable_(); + double flat_hold_value = 0.0; + const bool flat_hold = flat_hold_slot_ != kNoSlot + && read_double(slots_[flat_hold_slot_], flat_hold_value) + && std::isfinite(flat_hold_value) && flat_hold_value != 0.0; + if (enabled != last_enabled_ || flat_hold != last_flat_hold_) { + reset_runtime_(); + last_enabled_ = enabled; + last_flat_hold_ = flat_hold; + } + if (!enabled) { + reset_action_state(last_actions_, written_); + history_.reset(); + } + if (enabled) + maybe_publish_observation_(now); ActionSnapshot& snapshot = read_snapshot_; const bool has_snapshot = action_channel_.try_read(snapshot); @@ -117,21 +134,33 @@ class RlBridge final check_contract_(snapshot); } - const bool enabled = read_enable_(); const bool fresh = has_snapshot && is_finite(age) && age <= config_.max_action_age; const bool valid = enabled && contract_ok_ && has_snapshot && fresh && seq_ok && finite; + // The action fed into history must match the flat-ground command that is executed. + if (valid && flat_hold) + std::fill(snapshot.action.begin(), snapshot.action.end(), 0.0); write_actions( valid, snapshot, config_.action_terms, config_.invalid_mode, written_, action_outputs_); - if (valid) - last_actions_ = snapshot.action; + if (valid) { + if (config_.history_period.count() == 0) { + last_actions_ = snapshot.action; + } else if (snapshot.obs_seq != last_feedback_obs_seq_) { + const auto observation_time = now - std::chrono::duration_cast( + std::chrono::duration(age)); + action_feedback_.store(observation_time, snapshot.action); + last_feedback_obs_seq_ = snapshot.obs_seq; + } + } *valid_output_ = valid ? 1.0 : 0.0; *healthy_output_ = (contract_ok_ && fresh) ? 1.0 : 0.0; *action_age_output_ = age; *obs_seq_output_ = timeline_.sequence(); + if (last_valid_ && !valid) + reset_runtime_(); if (valid != last_valid_) { if (valid) { RCLCPP_INFO( @@ -212,6 +241,10 @@ class RlBridge final reset_slot_ = acquire_slot( *this, config_.reset_path, {Binding::kSize, Binding::kInt, Binding::kDouble}, false, output_map, slots_, "reset interface"); + if (!config_.flat_hold_path.empty()) + flat_hold_slot_ = acquire_slot( + *this, config_.flat_hold_path, {Binding::kBool, Binding::kDouble}, true, + output_map, slots_, "flat hold interface"); } void maybe_handle_reset_() { @@ -229,10 +262,13 @@ class RlBridge final return; std::vector obs; + if (config_.history_period.count() > 0) + last_actions_ = action_feedback_.sample(now, config_.history_period); if (build_observation( config_.obs_terms, slots_, last_actions_, config_.obs_frame_size, obs)) { - publish_observation_(history_.append(obs), now); + publish_observation_(history_.append(obs, now), now); } else { + reset_runtime_(); ++obs_invalid_count_; RCLCPP_WARN_THROTTLE( get_logger(), *get_clock(), 1000, @@ -298,7 +334,7 @@ class RlBridge final const std::vector& obs, std::chrono::steady_clock::time_point now) { rmcs_rl::msg::Observation message; message.header.stamp = get_clock()->now(); - message.obs_seq = timeline_.publish(now); + message.obs_seq = timeline_.publish(now, config_.pub_period); message.layout_hash = layout_hash_; message.obs = obs; obs_publisher_->publish(message); @@ -317,6 +353,8 @@ class RlBridge final void reset_runtime_() { reset_action_state(last_actions_, written_); history_.reset(); + action_feedback_.reset(); + last_feedback_obs_seq_ = 0; timeline_.reset(); } @@ -333,6 +371,7 @@ class RlBridge final std::size_t enable_slot_ = kNoSlot; std::size_t reset_slot_ = kNoSlot; + std::size_t flat_hold_slot_ = kNoSlot; std::string obs_signature_; std::string actions_signature_; @@ -341,12 +380,16 @@ class RlBridge final std::vector last_actions_; std::vector written_; ObservationHistory history_; + ActionFeedbackHistory action_feedback_; + std::uint64_t last_feedback_obs_seq_ = 0; ObservationTimeline timeline_; std::uint64_t last_reset_count_ = 0; std::uint64_t obs_invalid_count_ = 0; bool contract_ok_ = true; bool last_valid_ = false; + bool last_enabled_ = false; + bool last_flat_hold_ = false; ActionChannel action_channel_; ActionSnapshot read_snapshot_; diff --git a/src/rl_bridge/config.cpp b/src/rl_bridge/config.cpp index 25d43df..c42c426 100644 --- a/src/rl_bridge/config.cpp +++ b/src/rl_bridge/config.cpp @@ -79,6 +79,12 @@ BridgeConfig load_bridge_config(rclcpp::Node& node) { throw std::invalid_argument("RlBridge: policy_rate must be finite and > 0"); config.pub_period = std::chrono::duration_cast( std::chrono::duration(1.0 / config.policy_rate)); + const double history_rate = number_or(node, "history_rate", config.policy_rate); + if (!is_finite(history_rate) || history_rate <= 0.0 || history_rate > config.policy_rate) + throw std::invalid_argument("RlBridge: history_rate must be finite, positive and <= policy_rate"); + if (history_rate != config.policy_rate) + config.history_period = std::chrono::duration_cast( + std::chrono::duration(1.0 / history_rate)); config.max_action_age = number_or(node, "max_action_age", 2.0 / config.policy_rate); if (!(config.max_action_age > 0.0) || !is_finite(config.max_action_age)) throw std::invalid_argument("RlBridge: max_action_age must be finite and > 0"); @@ -100,6 +106,7 @@ BridgeConfig load_bridge_config(rclcpp::Node& node) { config.enable_path = string_or(node, "enable_interface", config.rl_base + "/enable"); config.enable_default = bool_or(node, "enable_default", false); config.reset_path = string_or(node, "reset_interface", ""); + config.flat_hold_path = string_or(node, "flat_hold_interface", ""); return config; } diff --git a/src/rl_bridge/observation_history.cpp b/src/rl_bridge/observation_history.cpp index cb88e9f..fcb64b0 100644 --- a/src/rl_bridge/observation_history.cpp +++ b/src/rl_bridge/observation_history.cpp @@ -1,15 +1,20 @@ #include #include +#include #include namespace rmcs_rl { -ObservationHistory::ObservationHistory(std::size_t frame_size, std::size_t history_length) +ObservationHistory::ObservationHistory(std::size_t frame_size, std::size_t history_length, + std::chrono::nanoseconds sample_period) : frame_size_(frame_size) - , values_(frame_size * history_length) { + , values_(frame_size * history_length) + , sample_period_(sample_period) { if (frame_size == 0 || history_length == 0) throw std::invalid_argument("observation frame size and history length must be positive"); + if (sample_period.count() < 0) + throw std::invalid_argument("observation history period cannot be negative"); } const std::vector& ObservationHistory::append(std::span frame) { @@ -26,8 +31,34 @@ const std::vector& ObservationHistory::append(std::span fr return values_; } +const std::vector& ObservationHistory::append(std::span frame, Clock::time_point now) { + if (sample_period_.count() == 0) + return append(frame); + if (frame.size() != frame_size_) + throw std::invalid_argument("observation frame does not match configured frame size"); + if (!samples_.empty() && now <= samples_.back().time) + throw std::invalid_argument("observation history timestamps must increase"); + if (!samples_.empty() && now - samples_.back().time > 2 * sample_period_) + reset(); + samples_.push_back({now, std::vector{frame.begin(), frame.end()}}); + const std::size_t length = values_.size() / frame_size_; + const auto oldest_time = now - sample_period_ * static_cast(length - 1); + while (samples_.size() > 1 && samples_[1].time <= oldest_time) + samples_.pop_front(); + std::size_t sample = 0; + for (std::size_t i = 0; i < length; ++i) { + const auto target = now - sample_period_ * static_cast(length - i - 1); + while (sample + 1 < samples_.size() && samples_[sample + 1].time <= target) + ++sample; + std::copy(samples_[sample].frame.begin(), samples_[sample].frame.end(), + values_.begin() + i * frame_size_); + } + return values_; +} + void ObservationHistory::reset() { initialized_ = false; + samples_.clear(); std::fill(values_.begin(), values_.end(), 0.0); } diff --git a/test/runtime_test.cpp b/test/runtime_test.cpp index c597a92..930c8ea 100644 --- a/test/runtime_test.cpp +++ b/test/runtime_test.cpp @@ -10,6 +10,7 @@ #include #include +#include #include #include @@ -28,6 +29,58 @@ TEST(ObservationHistory, PreservesFrameSizeOrderAndReset) { EXPECT_THROW(history.append(std::array{1.0}), std::invalid_argument); } +TEST(ActionFeedbackHistory, KeepsTenMillisecondPriorActionAndClearsOnReset) { + using namespace std::chrono_literals; + const ActionFeedbackHistory::Clock::time_point start{}; + ActionFeedbackHistory feedback{1}; + feedback.store(start, std::array{1.0}); + EXPECT_EQ(feedback.sample(start + 5ms, 10ms), (std::vector{0.0})); + feedback.store(start + 5ms, std::array{2.0}); + EXPECT_EQ(feedback.sample(start + 10ms, 10ms), (std::vector{1.0})); + feedback.store(start + 10ms, std::array{3.0}); + EXPECT_EQ(feedback.sample(start + 15ms, 10ms), (std::vector{2.0})); + feedback.store(start + 5ms, std::array{999.0}); // delayed response cannot rewind state + EXPECT_EQ(feedback.sample(start + 20ms, 10ms), (std::vector{3.0})); + feedback.reset(); + EXPECT_EQ(feedback.sample(start + 30ms, 10ms), (std::vector{0.0})); + EXPECT_THROW(feedback.store(start, std::array{1.0, 2.0}), std::invalid_argument); +} + +TEST(ObservationHistory, FasterInferencePreservesTrainingTimeSpan) { + using namespace std::chrono_literals; + const ObservationHistory::Clock::time_point start{}; + for (const std::size_t length : {5u, 8u}) { + ObservationHistory history{1, length, 10ms}; + for (int ms = 0; ms <= 100; ms += 5) { + const auto& values = history.append(std::array{double(ms)}, start + std::chrono::milliseconds(ms)); + for (std::size_t i = 0; i < length; ++i) + EXPECT_DOUBLE_EQ(values[i], std::max(0.0, double(ms) - 10.0 * (length - 1 - i))); + } + history.reset(); + const auto& values = history.append(std::array{42.0}, start + 1s); + for (double value : values) + EXPECT_DOUBLE_EQ(value, 42.0); + EXPECT_THROW(history.append(std::array{1.0}, start + 1s), std::invalid_argument); + const auto& after_gap = history.append(std::array{99.0}, start + 2s); + for (double value : after_gap) + EXPECT_DOUBLE_EQ(value, 99.0); + } +} + +TEST(ObservationTimeline, SchedulingJitterDoesNotAccumulate) { + using namespace std::chrono_literals; + ObservationTimeline timeline; + const ObservationTimeline::Clock::time_point start{}; + timeline.publish(start, 5ms); + EXPECT_TRUE(timeline.due(start + 6ms, 5ms)); + timeline.publish(start + 6ms, 5ms); + EXPECT_FALSE(timeline.due(start + 9ms, 5ms)); + EXPECT_TRUE(timeline.due(start + 10ms, 5ms)); + timeline.publish(start + 21ms, 5ms); + EXPECT_FALSE(timeline.due(start + 24ms, 5ms)); + EXPECT_TRUE(timeline.due(start + 25ms, 5ms)); +} + TEST(ObservationTimeline, RejectsPreResetAndOlderActions) { using namespace std::chrono_literals; const ObservationTimeline::Clock::time_point start{};