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"state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } } } } }, "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": { "id": "xV2FWNs65cY6" }, "outputs": [], "source": [ "%%capture\n", "# Clone the repository (can take 3min)\n", "!git clone --depth 1 https://github.com/Unity-Technologies/ml-agents" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "id": "d8wmVcMk7xKo" }, "outputs": [], "source": [ "%%capture\n", "# Go inside the repository and install the package (can take 3min)\n", "%cd ml-agents\n", "!pip3 install -e ./ml-agents-envs\n", "!pip3 install -e ./ml-agents" ] }, { "cell_type": "code", "source": [ "!mkdir ./trained-envs-executables\n", "!mkdir ./trained-envs-executables/linux" ], "metadata": { "id": "dCUeGzyz6NPv" }, "execution_count": 3, "outputs": [] }, { "cell_type": "code", "source": [ "!wget \"https://github.com/huggingface/Huggy/raw/main/Huggy.zip\" -O ./trained-envs-executables/linux/Huggy.zip" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "uhmoYkoB6JiX", "outputId": "dfe663d7-868d-4ec7-ba97-c7935cc5a513" }, "execution_count": 4, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "--2024-02-23 17:05:33-- https://github.com/huggingface/Huggy/raw/main/Huggy.zip\n", "Resolving github.com (github.com)... 192.30.255.113\n", "Connecting to github.com (github.com)|192.30.255.113|:443... connected.\n", "HTTP request sent, awaiting response... 302 Found\n", "Location: https://media.githubusercontent.com/media/huggingface/Huggy/main/Huggy.zip [following]\n", "--2024-02-23 17:05:33-- https://media.githubusercontent.com/media/huggingface/Huggy/main/Huggy.zip\n", "Resolving media.githubusercontent.com (media.githubusercontent.com)... 185.199.108.133, 185.199.109.133, 185.199.110.133, ...\n", "Connecting to media.githubusercontent.com (media.githubusercontent.com)|185.199.108.133|:443... connected.\n", "HTTP request sent, awaiting response... 200 OK\n", "Length: 39214997 (37M) [application/zip]\n", "Saving to: ‘./trained-envs-executables/linux/Huggy.zip’\n", "\n", "./trained-envs-exec 100%[===================>] 37.40M 244MB/s in 0.2s \n", "\n", "2024-02-23 17:05:35 (244 MB/s) - ‘./trained-envs-executables/linux/Huggy.zip’ saved [39214997/39214997]\n", "\n" ] } ] }, { "cell_type": "code", "source": [ "%%capture\n", "!unzip -d ./trained-envs-executables/linux/ ./trained-envs-executables/linux/Huggy.zip" ], "metadata": { "id": "PcoTxSTX6NZp" }, "execution_count": 5, "outputs": [] }, { "cell_type": "code", "source": [ "!chmod -R 755 ./trained-envs-executables/linux/Huggy" ], "metadata": { "id": "M0YotyCf6Nb9" }, "execution_count": 6, "outputs": [] }, { "cell_type": "code", "source": [ "!mlagents-learn ./config/ppo/Huggy.yaml --env=./trained-envs-executables/linux/Huggy/Huggy --run-id=\"Huggy2\" --no-graphics" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "wHEDv1396NgJ", "outputId": "91d7c50f-7883-48f5-9471-90d18e6acfe1" }, "execution_count": 7, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "/usr/local/lib/python3.10/dist-packages/torch/__init__.py:696: UserWarning: torch.set_default_tensor_type() is deprecated as of PyTorch 2.1, please use torch.set_default_dtype() and torch.set_default_device() as alternatives. (Triggered internally at ../torch/csrc/tensor/python_tensor.cpp:451.)\n", " _C._set_default_tensor_type(t)\n", "\n", " ┐ ╖\n", " ╓╖╬│╡ ││╬╖╖\n", " ╓╖╬│││││┘ ╬│││││╬╖\n", " ╖╬│││││╬╜ ╙╬│││││╖╖ ╗╗╗\n", " ╬╬╬╬╖││╦╖ ╖╬││╗╣╣╣╬ ╟╣╣╬ ╟╣╣╣ ╜╜╜ ╟╣╣\n", " ╬╬╬╬╬╬╬╬╖│╬╖╖╓╬╪│╓╣╣╣╣╣╣╣╬ ╟╣╣╬ ╟╣╣╣ ╒╣╣╖╗╣╣╣╗ ╣╣╣ ╣╣╣╣╣╣ ╟╣╣╖ ╣╣╣\n", " ╬╬╬╬┐ ╙╬╬╬╬│╓╣╣╣╝╜ ╫╣╣╣╬ ╟╣╣╬ ╟╣╣╣ ╟╣╣╣╙ ╙╣╣╣ ╣╣╣ ╙╟╣╣╜╙ ╫╣╣ ╟╣╣\n", " ╬╬╬╬┐ ╙╬╬╣╣ ╫╣╣╣╬ ╟╣╣╬ ╟╣╣╣ ╟╣╣╬ ╣╣╣ ╣╣╣ ╟╣╣ ╣╣╣┌╣╣╜\n", " ╬╬╬╜ ╬╬╣╣ ╙╝╣╣╬ ╙╣╣╣╗╖╓╗╣╣╣╜ ╟╣╣╬ ╣╣╣ ╣╣╣ ╟╣╣╦╓ ╣╣╣╣╣\n", " ╙ ╓╦╖ ╬╬╣╣ ╓╗╗╖ ╙╝╣╣╣╣╝╜ ╘╝╝╜ ╝╝╝ ╝╝╝ ╙╣╣╣ ╟╣╣╣\n", " ╩╬╬╬╬╬╬╦╦╬╬╣╣╗╣╣╣╣╣╣╣╝ ╫╣╣╣╣\n", " ╙╬╬╬╬╬╬╬╣╣╣╣╣╣╝╜\n", " ╙╬╬╬╣╣╣╜\n", " ╙\n", " \n", " Version information:\n", " ml-agents: 1.1.0.dev0,\n", " ml-agents-envs: 1.1.0.dev0,\n", " Communicator API: 1.5.0,\n", " PyTorch: 2.2.1+cu121\n", "[INFO] Connected to Unity environment with package version 2.2.1-exp.1 and communication version 1.5.0\n", "[INFO] Connected new brain: Huggy?team=0\n", "[INFO] Hyperparameters for behavior name Huggy: \n", "\ttrainer_type:\tppo\n", "\thyperparameters:\t\n", "\t batch_size:\t2048\n", "\t buffer_size:\t20480\n", "\t learning_rate:\t0.0003\n", "\t beta:\t0.005\n", "\t epsilon:\t0.2\n", "\t lambd:\t0.95\n", "\t num_epoch:\t3\n", "\t shared_critic:\tFalse\n", "\t learning_rate_schedule:\tlinear\n", "\t beta_schedule:\tlinear\n", "\t epsilon_schedule:\tlinear\n", "\tcheckpoint_interval:\t200000\n", "\tnetwork_settings:\t\n", "\t normalize:\tTrue\n", "\t hidden_units:\t512\n", "\t num_layers:\t3\n", "\t vis_encode_type:\tsimple\n", "\t memory:\tNone\n", "\t goal_conditioning_type:\thyper\n", "\t deterministic:\tFalse\n", "\treward_signals:\t\n", "\t extrinsic:\t\n", "\t gamma:\t0.995\n", "\t strength:\t1.0\n", "\t network_settings:\t\n", "\t normalize:\tFalse\n", "\t hidden_units:\t128\n", "\t num_layers:\t2\n", "\t vis_encode_type:\tsimple\n", "\t memory:\tNone\n", "\t goal_conditioning_type:\thyper\n", "\t deterministic:\tFalse\n", "\tinit_path:\tNone\n", "\tkeep_checkpoints:\t15\n", "\teven_checkpoints:\tFalse\n", "\tmax_steps:\t2000000\n", "\ttime_horizon:\t1000\n", "\tsummary_freq:\t50000\n", "\tthreaded:\tFalse\n", "\tself_play:\tNone\n", "\tbehavioral_cloning:\tNone\n", "[INFO] Huggy. Step: 50000. Time Elapsed: 93.378 s. Mean Reward: 1.909. Std of Reward: 0.914. Training.\n", "[INFO] Huggy. Step: 100000. Time Elapsed: 175.763 s. Mean Reward: 2.584. Std of Reward: 1.080. Training.\n", "[INFO] Huggy. Step: 150000. Time Elapsed: 266.613 s. Mean Reward: 3.110. Std of Reward: 1.117. Training.\n", "[INFO] Huggy. Step: 200000. Time Elapsed: 348.009 s. Mean Reward: 3.468. Std of Reward: 1.310. Training.\n", "[INFO] Exported results/Huggy2/Huggy/Huggy-199826.onnx\n", "[INFO] Huggy. Step: 250000. Time Elapsed: 442.187 s. Mean Reward: 3.305. Std of Reward: 1.395. Training.\n", "[INFO] Huggy. Step: 300000. Time Elapsed: 529.052 s. Mean Reward: 3.647. Std of Reward: 1.422. Training.\n", "[INFO] Huggy. Step: 350000. Time Elapsed: 614.213 s. Mean Reward: 3.862. Std of Reward: 1.543. Training.\n", "[INFO] Huggy. Step: 400000. Time Elapsed: 710.369 s. Mean Reward: 3.833. Std of Reward: 1.632. Training.\n", "[INFO] Exported results/Huggy2/Huggy/Huggy-399993.onnx\n", "[INFO] Huggy. Step: 450000. Time Elapsed: 796.704 s. Mean Reward: 3.883. Std of Reward: 1.697. Training.\n", "[INFO] Huggy. Step: 500000. Time Elapsed: 891.846 s. Mean Reward: 3.767. Std of Reward: 1.780. Training.\n", "[INFO] Huggy. Step: 550000. Time Elapsed: 976.981 s. Mean Reward: 3.748. Std of Reward: 1.747. Training.\n", "[INFO] Huggy. Step: 600000. Time Elapsed: 1074.936 s. Mean Reward: 3.700. Std of Reward: 1.690. Training.\n", "[INFO] Exported results/Huggy2/Huggy/Huggy-599947.onnx\n", "[INFO] Huggy. Step: 650000. Time Elapsed: 1164.652 s. Mean Reward: 3.830. Std of Reward: 1.696. Training.\n", "[INFO] Huggy. Step: 700000. Time Elapsed: 1250.707 s. Mean Reward: 3.820. Std of Reward: 1.811. Training.\n", "[INFO] Huggy. Step: 750000. Time Elapsed: 1345.573 s. Mean Reward: 3.904. Std of Reward: 1.747. Training.\n", "[INFO] Huggy. Step: 800000. Time Elapsed: 1433.824 s. Mean Reward: 3.841. Std of Reward: 1.647. Training.\n", "[INFO] Exported results/Huggy2/Huggy/Huggy-799965.onnx\n", "[INFO] Huggy. Step: 850000. Time Elapsed: 1528.304 s. Mean Reward: 3.815. Std of Reward: 1.784. Training.\n", "[INFO] Huggy. Step: 900000. Time Elapsed: 1615.571 s. Mean Reward: 3.966. Std of Reward: 1.696. Training.\n", "[INFO] Huggy. Step: 950000. Time Elapsed: 1714.848 s. Mean Reward: 3.818. Std of Reward: 1.711. Training.\n", "[INFO] Huggy. Step: 1000000. Time Elapsed: 1803.308 s. Mean Reward: 3.939. Std of Reward: 1.724. Training.\n", "[INFO] Exported results/Huggy2/Huggy/Huggy-999988.onnx\n", "[INFO] Huggy. Step: 1050000. Time Elapsed: 1891.760 s. Mean Reward: 3.963. Std of Reward: 1.686. Training.\n", "[INFO] Huggy. Step: 1100000. Time Elapsed: 1990.631 s. Mean Reward: 3.863. Std of Reward: 1.779. Training.\n", "[INFO] Huggy. Step: 1150000. Time Elapsed: 2080.953 s. Mean Reward: 3.912. Std of Reward: 1.684. Training.\n", "[INFO] Huggy. Step: 1200000. Time Elapsed: 2179.607 s. Mean Reward: 3.971. Std of Reward: 1.675. Training.\n", "[INFO] Exported results/Huggy2/Huggy/Huggy-1199952.onnx\n", "[INFO] Huggy. Step: 1250000. Time Elapsed: 2267.157 s. Mean Reward: 3.846. Std of Reward: 1.774. Training.\n", "[INFO] Huggy. Step: 1300000. Time Elapsed: 2366.259 s. Mean Reward: 3.790. Std of Reward: 1.684. Training.\n", "[INFO] Huggy. Step: 1350000. Time Elapsed: 2455.261 s. Mean Reward: 3.883. Std of Reward: 1.680. Training.\n", "[INFO] Huggy. Step: 1400000. Time Elapsed: 2551.313 s. Mean Reward: 3.909. Std of Reward: 1.621. Training.\n", "[INFO] Exported results/Huggy2/Huggy/Huggy-1399996.onnx\n", "[INFO] Huggy. Step: 1450000. Time Elapsed: 2638.028 s. Mean Reward: 3.872. Std of Reward: 1.700. Training.\n", "[INFO] Huggy. Step: 1500000. Time Elapsed: 2726.560 s. Mean Reward: 3.849. Std of Reward: 1.699. Training.\n", "[INFO] Huggy. Step: 1550000. Time Elapsed: 2821.528 s. Mean Reward: 3.976. Std of Reward: 1.728. Training.\n", "[INFO] Huggy. Step: 1600000. Time Elapsed: 2908.367 s. Mean Reward: 3.887. Std of Reward: 1.701. Training.\n", "[INFO] Exported results/Huggy2/Huggy/Huggy-1599961.onnx\n", "[INFO] Huggy. Step: 1650000. Time Elapsed: 3005.380 s. Mean Reward: 3.857. Std of Reward: 1.713. Training.\n", "[INFO] Huggy. Step: 1700000. Time Elapsed: 3097.110 s. Mean Reward: 3.943. Std of Reward: 1.666. Training.\n", "[INFO] Huggy. Step: 1750000. Time Elapsed: 3196.133 s. Mean Reward: 4.018. Std of Reward: 1.769. Training.\n", "[INFO] Huggy. Step: 1800000. Time Elapsed: 3288.032 s. Mean Reward: 3.789. Std of Reward: 1.684. Training.\n", "[INFO] Exported results/Huggy2/Huggy/Huggy-1799993.onnx\n", "[INFO] Huggy. Step: 1850000. Time Elapsed: 3378.888 s. Mean Reward: 3.871. Std of Reward: 1.685. Training.\n", "[INFO] Huggy. Step: 1900000. Time Elapsed: 3477.182 s. Mean Reward: 3.893. Std of Reward: 1.726. Training.\n", "[INFO] Huggy. Step: 1950000. Time Elapsed: 3566.042 s. Mean Reward: 3.936. Std of Reward: 1.702. Training.\n", "[INFO] Huggy. Step: 2000000. Time Elapsed: 3661.740 s. Mean Reward: 3.916. Std of Reward: 1.828. Training.\n", "[INFO] Exported results/Huggy2/Huggy/Huggy-1999981.onnx\n", "[INFO] Exported results/Huggy2/Huggy/Huggy-2000065.onnx\n", "[INFO] Copied results/Huggy2/Huggy/Huggy-2000065.onnx to results/Huggy2/Huggy.onnx.\n" ] } ] }, { "cell_type": "code", "source": [ "from huggingface_hub import notebook_login\n", "notebook_login()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 145, "referenced_widgets": [ "ba3ffd7bb01a4cafa2635b5f106bc1cd", "c41a41b0e9f14ed88a0e1bdbe80d754c", "de682414aefb45c7beb124d2ff029844", "380f1c7ab66d44d79fe1241433b3de58", "0da59d818fa44cde9cbc8b803bd30d38", "4dd3d809e24f4c8388e0ca126dc9f1a2", "251fd2fec80a4ec7a59272a41d379d2f", "d59e27cb10f44d16b63f0868a283dfe6", "23853a0320f3423d8f37213a6f1afec0", "f7220d55fa1a4fd2933c148f94ef7092", "6555a2944f1f408db5ab508472eb1710", "262b7fcaa1a545c1948f42283c763506", "4b83ced9a7924ae9ad9209c92e445c55", "2cfff59e91eb45a4a33ae45c886ee188", "236f1354946a471699ed746856f6ebce", "1b463f3730964499b5872d45057ea7f1", "23c6a79f7ab44019b2e331531187edbe", "d435e1a579394af0af9ee4b67566b121", "ca2f9498bd7b440f8d570a39a8cb7c98", "03dd395bb4e743c3b545f5dc7fa62c75", "071b0a7cb7ff4fa9b4a50d2bdbcfc01a", "26cedad581804b40817c4db80b44d56d", "cf76cc497c424249b7e449ea5589e90b", "825548fb63f8444a89940aca63bc7b83", "e56c1224065b4c92b6a8800773224037", "76dc121e5aac492ab209f28385136fc4", "59de9658f0f14163b5115d32a300ce88", "54dd72d47d324b1ea0ddbf44a68fa414", "4ea0ab70227448a98c37cbe56d7af3a5", "feb19fb48daf47be9e1375eaf67ff19d", "44cb4e413f2f414fb6e92557ae355158", "5a7fef3b31cd49e2a43c2b2ad545cce2" ] }, "id": "wALA9m226Nm7", "outputId": "8d07facf-0458-470e-8dd9-fb9c1056db2a" }, "execution_count": 8, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "VBox(children=(HTML(value='
\n", " sys.exit(load_entry_point('mlagents', 'console_scripts', 'mlagents-push-to-hf')())\n", " File \"/content/ml-agents/ml-agents/mlagents/utils/push_to_hf.py\", line 205, in main\n", " package_to_hub(\n", " File \"/content/ml-agents/ml-agents/mlagents/utils/push_to_hf.py\", line 159, in package_to_hub\n", " _generate_config(local_path, configfile_name)\n", " File \"/content/ml-agents/ml-agents/mlagents/utils/push_to_hf.py\", line 29, in _generate_config\n", " with open(os.path.join(local_dir, configfile_name)) as yaml_in:\n", "FileNotFoundError: [Errno 2] No such file or directory: 'results/Huggy/configuration.yaml'\n" ] } ] }, { "cell_type": "code", "source": [], "metadata": { "id": "PeBLrP5GLedL" }, "execution_count": null, "outputs": [] }, { "cell_type": "markdown", "source": [], "metadata": { "id": "aVz3MLHA6LWZ" } } ] }