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{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "## Example usage of Tempestpy" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "vscode": { "languageId": "plaintext" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "pygame 2.6.1 (SDL 2.28.4, Python 3.10.12)\n", "Hello from the pygame community. https://www.pygame.org/contribute.html\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2024-11-29 12:24:16.266841: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", "2024-11-29 12:24:16.283112: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", "2024-11-29 12:24:16.287862: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n", "2024-11-29 12:24:16.298829: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n", "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n", "2024-11-29 12:24:18.626838: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n", "error: XDG_RUNTIME_DIR not set in the environment.\n" ] } ], "source": [ "from sb3_contrib import MaskablePPO\n", "from sb3_contrib.common.wrappers import ActionMasker\n", "from stable_baselines3.common.logger import Logger, CSVOutputFormat, TensorBoardOutputFormat, HumanOutputFormat\n", "\n", "import gymnasium as gym\n", "\n", "from minigrid.core.actions import Actions\n", "from minigrid.core.constants import TILE_PIXELS\n", "from minigrid.wrappers import RGBImgObsWrapper, ImgObsWrapper\n", "\n", "import tempfile, datetime, shutil\n", "\n", "import time\n", "import os\n", "\n", "from utils import MiniGridShieldHandler, create_log_dir, ShieldingConfig, MiniWrapper, expname, shield_needed, shielded_evaluation, create_shield_overlay_image\n", "from sb3utils import MiniGridSbShieldingWrapper, parse_sb3_arguments, ImageRecorderCallback, InfoCallback\n", "\n", "import os, sys\n", "from copy import deepcopy\n", "\n", "from PIL import Image" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "vscode": { "languageId": "plaintext" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Starting the training\n" ] }, { "data": { "image/jpeg": 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"text/plain": [ "<PIL.Image.Image image mode=RGB size=864x704>" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\n", "Computing new shield\n", "LOG: Starting with explicit model creation...\n", "Elapsed time is 1.5311391353607178 seconds.\n", "LOG: Starting with model checking...\n", "Elapsed time is 0.0014214515686035156 seconds.\n", "Write to file shielding_files_20241129T122454_58hszne6/shield.\n", "LOG: Starting to translate shield...\n", "Elapsed time is 0.056265830993652344 seconds.\n", "\n", "\n", "Computing new shield\n", "LOG: Starting with explicit model creation...\n", "Elapsed time is 1.3646655082702637 seconds.\n", "LOG: Starting with model checking...\n", "Elapsed time is 0.0015163421630859375 seconds.\n", "LOG: Starting to translate shield...\n", "Write to file shielding_files_20241129T122456_wtrsvp2x/shield.\n", "Elapsed time is 0.05994606018066406 seconds.\n", "\n", "\n", "Computing new shield\n", "LOG: Starting with explicit model creation...\n", "Elapsed time is 1.5757696628570557 seconds.\n", "LOG: Starting with model checking...\n", "Elapsed time is 0.0013585090637207031 seconds.\n", " WARN (PreShield.cpp:50): No shielding action possible with absolute comparison for state with index 683\n", " WARN (PreShield.cpp:50): No shielding action possible with absolute comparison for state with index 1139\n", "Write to file shielding_files_20241129T122458_wavsk47p/shield.\n", " WARN (PreShield.cpp:50): No shielding action possible with absolute comparison for state with index 683\n", " WARN (PreShield.cpp:50): No shielding action possible with absolute comparison for state with index 1139\n", "LOG: Starting to translate shield...\n", "Elapsed time is 0.05765676498413086 seconds.\n", "\n", "\n", "Computing new shield\n", "LOG: Starting with explicit model creation...\n", "Elapsed time is 1.7896459102630615 seconds.\n", "LOG: Starting with model checking...\n", "Elapsed time is 0.0013873577117919922 seconds.\n", " WARN (PreShield.cpp:50): No shielding action possible with absolute comparison for state with index 610\n", " WARN (PreShield.cpp:50): No shielding action possible with absolute comparison for state with index 611\n", " WARN (PreShield.cpp:50): No shielding action possible with absolute comparison for state with index 635\n", "LOG: Starting to translate shield...\n", " WARN (PreShield.cpp:50): No shielding action possible with absolute comparison for state with index 659\n", " WARN (PreShield.cpp:50): No shielding action possible with absolute comparison for state with index 683\n", " WARN (PreShield.cpp:50): No shielding action possible with absolute comparison for state with index 1139\n", "Write to file shielding_files_20241129T122500_n10bceo8/shield.\n", " WARN (PreShield.cpp:50): No shielding action possible with absolute comparison for state with index 610\n", " WARN (PreShield.cpp:50): No shielding action possible with absolute comparison for state with index 611\n", " WARN (PreShield.cpp:50): No shielding action possible with absolute comparison for state with index 635\n", " WARN (PreShield.cpp:50): No shielding action possible with absolute comparison for state with index 659\n", " WARN (PreShield.cpp:50): No shielding action possible with absolute comparison for state with index 683\n", " WARN (PreShield.cpp:50): No shielding action possible with absolute comparison for state with index 1139\n", "Elapsed time is 0.057317256927490234 seconds.\n" ] }, { "data": { "image/png": "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 "text/plain": [ "<PIL.Image.Image image mode=RGBA size=864x704>" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "The shield for shield_value = 0.9\n" ] }, { "data": { "image/png": "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 "text/plain": [ "<PIL.Image.Image image mode=RGBA size=864x704>" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "The shield for shield_value = 0.95\n" ] }, { "data": { "image/png": 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"text/plain": [ "<PIL.Image.Image image mode=RGBA size=864x704>" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "The shield for shield_value = 0.99\n" ] }, { "data": { "image/png": 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"text/plain": [ "<PIL.Image.Image image mode=RGBA size=864x704>" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "The shield for shield_value = 1.0\n", "Training with shield:\n" ] }, { "data": { "image/png": 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"text/plain": [ "<PIL.Image.Image image mode=RGBA size=864x704>" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Using cpu device\n", "Wrapping the env with a `Monitor` wrapper\n", "Wrapping the env in a DummyVecEnv.\n", "Wrapping the env in a VecTransposeImage.\n", "truncated: {'reached_goal': False, 'ran_into_lava': False, 'opened_door': False, 'picked_up': False}\n", "truncated: {'reached_goal': False, 'ran_into_lava': False, 'opened_door': False, 'picked_up': False}\n", "truncated: {'reached_goal': False, 'ran_into_lava': False, 'opened_door': False, 'picked_up': False}\n", "truncated: {'reached_goal': False, 'ran_into_lava': False, 'opened_door': False, 'picked_up': False}\n", "truncated: {'reached_goal': False, 'ran_into_lava': False, 'opened_door': False, 'picked_up': False}\n", "truncated: {'reached_goal': False, 'ran_into_lava': False, 'opened_door': False, 'picked_up': False}\n", "truncated: {'reached_goal': False, 'ran_into_lava': False, 'opened_door': False, 'picked_up': False}\n", "truncated: {'reached_goal': False, 'ran_into_lava': False, 'opened_door': False, 'picked_up': False}\n", "truncated: {'reached_goal': False, 'ran_into_lava': False, 'opened_door': False, 'picked_up': False}\n", "truncated: {'reached_goal': False, 'ran_into_lava': False, 'opened_door': False, 'picked_up': False}\n", "-----------------------------------\n", "| info/ | |\n", "| no_shield_action | 0 |\n", "| sum_opened_door | 0 |\n", "| sum_picked_up | 0 |\n", "| sum_ran_into_lava | 0 |\n", "| sum_reached_goal | 0 |\n", "| rollout/ | |\n", "| ep_len_mean | 200 |\n", "| ep_rew_mean | -2 |\n", "| time/ | |\n", "| fps | 63 |\n", "| iterations | 1 |\n", "| time_elapsed | 32 |\n", "| total_timesteps | 2048 |\n", "-----------------------------------\n" ] } ], "source": [ "GRID_TO_PRISM_BINARY=os.getenv(\"M2P_BINARY\")\n", "\n", "def mask_fn(env: gym.Env):\n", " return env.create_action_mask()\n", "\n", "def nomask_fn(env: gym.Env):\n", " return [1.0] * 7\n", "\n", "def main():\n", " #env = \"MiniGrid-LavaSlipperyCliff-16x13-Slip10-Time-v0\"\n", " env = \"MiniGrid-WindyCity2-v0\"\n", "\n", " formula = \"Pmax=? [G ! AgentIsOnLava]\"\n", " value_for_training = 0.99\n", " shield_comparison = \"absolute\"\n", " shielding = ShieldingConfig.Training\n", " \n", " logger = Logger(\"/tmp\", output_formats=[HumanOutputFormat(sys.stdout)])\n", " \n", " env = gym.make(env, render_mode=\"rgb_array\")\n", " image_env = RGBImgObsWrapper(env, TILE_PIXELS)\n", " env = RGBImgObsWrapper(env, 8)\n", " env = ImgObsWrapper(env)\n", " env = MiniWrapper(env)\n", "\n", " \n", " env.reset()\n", " Image.fromarray(env.render()).show()\n", " \n", " shield_handlers = dict()\n", " if shield_needed(shielding):\n", " for value in [0.9, 0.95, 0.99, 1.0]:\n", " shield_handler = MiniGridShieldHandler(GRID_TO_PRISM_BINARY, \"grid.txt\", \"grid.prism\", formula, shield_value=value, shield_comparison=shield_comparison, nocleanup=True, prism_file=None)\n", " env = MiniGridSbShieldingWrapper(env, shield_handler=shield_handler, create_shield_at_reset=False)\n", "\n", "\n", " shield_handlers[value] = shield_handler\n", " if shield_needed(shielding):\n", " for value in [0.9, 0.95, 0.99, 1.0]: \n", " create_shield_overlay_image(image_env, shield_handlers[value].create_shield())\n", " print(f\"The shield for shield_value = {value}\")\n", "\n", " if shielding == ShieldingConfig.Training:\n", " env = MiniGridSbShieldingWrapper(env, shield_handler=shield_handlers[value_for_training], create_shield_at_reset=False)\n", " env = ActionMasker(env, mask_fn)\n", " print(\"Training with shield:\")\n", " create_shield_overlay_image(image_env, shield_handlers[value_for_training].create_shield())\n", " elif shielding == ShieldingConfig.Disabled:\n", " env = ActionMasker(env, nomask_fn)\n", " else:\n", " assert(False) \n", " model = MaskablePPO(\"CnnPolicy\", env, verbose=1, device=\"auto\")\n", " model.set_logger(logger)\n", " steps = 200\n", "\n", " model.learn(steps,callback=[InfoCallback()])\n", "\n", "\n", "\n", "if __name__ == '__main__':\n", " print(\"Starting the training\")\n", " main()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.12" } }, "nbformat": 4, "nbformat_minor": 4}
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