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{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "## Example usage of Tempestpy" ] }, { "cell_type": "code", "execution_count": 2, "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 10:15:58.098867: 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 10:15:58.215498: 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 10:15:58.247100: 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 10:15:58.481063: 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 10:16:01.296290: 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": 3, "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 1.4756522178649902 seconds.\n", "LOG: Starting with model checking...\n", "Elapsed time is 0.007963895797729492 seconds.\n", "Write to file shielding_files_20241129T101609_2ylwmp9k/shield.\n", "LOG: Starting to translate shield...\n", "Elapsed time is 0.05611824989318848 seconds.\n", "\n", "\n", "Computing new shield\n", "LOG: Starting with explicit model creation...\n", "Elapsed time is 1.2929818630218506 seconds.\n", "LOG: Starting with model checking...\n", "Elapsed time is 0.0013511180877685547 seconds.\n", "Write to file shielding_files_20241129T101611_o5a_j5lh/shield.\n", "LOG: Starting to translate shield...\n", "Elapsed time is 0.05822467803955078 seconds.\n", "\n", "\n", "Computing new shield\n", "LOG: Starting with explicit model creation...\n", "Elapsed time is 1.192638874053955 seconds.\n", "LOG: Starting with model checking...\n", "Elapsed time is 0.0012052059173583984 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_20241129T101613_79jou6ds/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 0.051551103591918945 seconds.\n", "\n", "\n", "Computing new shield\n", "LOG: Starting with explicit model creation...\n", "Elapsed time is 1.1984505653381348 seconds.\n", "LOG: Starting with model checking...\n", "Elapsed time is 0.0012307167053222656 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", " 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", "LOG: Starting to translate shield...\n", " WARN (PreShield.cpp:50): No shielding action possible with absolute comparison for state with index 1139\n", "Write to file shielding_files_20241129T101615_2o4596m3/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 0.05582904815673828 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" ] }, { "ename": "AssertionError", "evalue": "", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mAssertionError\u001b[0m Traceback (most recent call last)", "Cell \u001b[0;32mIn[3], line 63\u001b[0m\n\u001b[1;32m 61\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;18m__name__\u001b[39m \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m__main__\u001b[39m\u001b[38;5;124m'\u001b[39m:\n\u001b[1;32m 62\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mStarting the training\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m---> 63\u001b[0m \u001b[43mmain\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n", "Cell \u001b[0;32mIn[3], line 56\u001b[0m, in \u001b[0;36mmain\u001b[0;34m()\u001b[0m\n\u001b[1;32m 53\u001b[0m model\u001b[38;5;241m.\u001b[39mset_logger(logger)\n\u001b[1;32m 54\u001b[0m steps \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m20_000\u001b[39m\n\u001b[0;32m---> 56\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m(\u001b[38;5;28;01mFalse\u001b[39;00m)\n\u001b[1;32m 57\u001b[0m model\u001b[38;5;241m.\u001b[39mlearn(steps,callback\u001b[38;5;241m=\u001b[39m[InfoCallback()])\n", "\u001b[0;31mAssertionError\u001b[0m: " ] } ], "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-WindyCity-Adv-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 = 20_000\n", "\n", " assert(False)\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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