{ "cells": [ { "cell_type": "markdown", "id": "986bcaab", "metadata": {}, "source": [ "# Running Tune experiments with BOHB\n", "\n", "In this tutorial we introduce BOHB, while running a simple Ray Tune experiment.\n", "Tune’s Search Algorithms integrate with BOHB and, as a result,\n", "allow you to seamlessly scale up a BOHB optimization\n", "process - without sacrificing performance.\n", "\n", "Bayesian Optimization HyperBand (BOHB) combines the benefits of Bayesian optimization\n", "together with Bandit-based methods (e.g. HyperBand). BOHB does not rely on\n", "the gradient of the objective function,\n", "but instead, learns from samples of the search space.\n", "It is suitable for optimizing functions that are non-differentiable,\n", "with many local minima, or even unknown but only testable.\n", "Therefore, this approach belongs to the domain of\n", "\"derivative-free optimization\" and \"black-box optimization\".\n", "\n", "In this example we minimize a simple objective to briefly demonstrate the usage of\n", "BOHB with Ray Tune via `BOHBSearch`. It's useful to keep in mind that despite\n", "the emphasis on machine learning experiments, Ray Tune optimizes any implicit\n", "or explicit objective. Here we assume `ConfigSpace==0.4.18` and `hpbandster==0.7.4`\n", "libraries are installed. To learn more, please refer to the\n", "[BOHB website](https://github.com/automl/HpBandSter)." ] }, { "cell_type": "code", "execution_count": 1, "id": "d12bd979", "metadata": { "tags": [ "remove-cell" ] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Collecting ConfigSpace==0.4.18\n", " Using cached ConfigSpace-0.4.18-cp37-cp37m-macosx_10_15_x86_64.whl\n", "Requirement already satisfied: pyparsing in /Users/kai/.pyenv/versions/3.7.7/lib/python3.7/site-packages (from ConfigSpace==0.4.18) (2.4.7)\n", "Requirement already satisfied: numpy in /Users/kai/.pyenv/versions/3.7.7/lib/python3.7/site-packages (from ConfigSpace==0.4.18) (1.21.6)\n", "Requirement already satisfied: cython in /Users/kai/.pyenv/versions/3.7.7/lib/python3.7/site-packages (from ConfigSpace==0.4.18) (0.29.30)\n", "Installing collected packages: ConfigSpace\n", " Attempting uninstall: ConfigSpace\n", " Found existing installation: ConfigSpace 0.4.21\n", " Uninstalling ConfigSpace-0.4.21:\n", " Successfully uninstalled ConfigSpace-0.4.21\n", "Successfully installed ConfigSpace-0.4.18\n", "\u001b[33mWARNING: There was an error checking the latest version of pip.\u001b[0m\u001b[33m\n", "\u001b[0mRequirement already satisfied: hpbandster==0.7.4 in /Users/kai/.pyenv/versions/3.7.7/lib/python3.7/site-packages (0.7.4)\n", "Requirement already satisfied: netifaces in /Users/kai/.pyenv/versions/3.7.7/lib/python3.7/site-packages (from hpbandster==0.7.4) (0.11.0)\n", "Requirement already satisfied: scipy in /Users/kai/.pyenv/versions/3.7.7/lib/python3.7/site-packages (from hpbandster==0.7.4) (1.4.1)\n", "Requirement already satisfied: Pyro4 in /Users/kai/.pyenv/versions/3.7.7/lib/python3.7/site-packages (from hpbandster==0.7.4) (4.82)\n", "Requirement already satisfied: serpent in /Users/kai/.pyenv/versions/3.7.7/lib/python3.7/site-packages (from hpbandster==0.7.4) (1.40)\n", "Requirement already satisfied: statsmodels in /Users/kai/.pyenv/versions/3.7.7/lib/python3.7/site-packages (from hpbandster==0.7.4) (0.13.2)\n", "Requirement already satisfied: ConfigSpace in /Users/kai/.pyenv/versions/3.7.7/lib/python3.7/site-packages (from hpbandster==0.7.4) (0.4.18)\n", "Requirement already satisfied: numpy in /Users/kai/.pyenv/versions/3.7.7/lib/python3.7/site-packages (from hpbandster==0.7.4) (1.21.6)\n", "Requirement already satisfied: cython in /Users/kai/.pyenv/versions/3.7.7/lib/python3.7/site-packages (from ConfigSpace->hpbandster==0.7.4) (0.29.30)\n", "Requirement already satisfied: pyparsing in /Users/kai/.pyenv/versions/3.7.7/lib/python3.7/site-packages (from ConfigSpace->hpbandster==0.7.4) (2.4.7)\n", "Requirement already satisfied: pandas>=0.25 in /Users/kai/.pyenv/versions/3.7.7/lib/python3.7/site-packages (from statsmodels->hpbandster==0.7.4) (1.3.5)\n", "Requirement already satisfied: packaging>=21.3 in /Users/kai/.pyenv/versions/3.7.7/lib/python3.7/site-packages (from statsmodels->hpbandster==0.7.4) (21.3)\n", "Requirement already satisfied: patsy>=0.5.2 in /Users/kai/.pyenv/versions/3.7.7/lib/python3.7/site-packages (from statsmodels->hpbandster==0.7.4) (0.5.2)\n", "Requirement already satisfied: python-dateutil>=2.7.3 in /Users/kai/.pyenv/versions/3.7.7/lib/python3.7/site-packages (from pandas>=0.25->statsmodels->hpbandster==0.7.4) (2.8.2)\n", "Requirement already satisfied: pytz>=2017.3 in /Users/kai/.pyenv/versions/3.7.7/lib/python3.7/site-packages (from pandas>=0.25->statsmodels->hpbandster==0.7.4) (2022.1)\n", "Requirement already satisfied: six in /Users/kai/.pyenv/versions/3.7.7/lib/python3.7/site-packages (from patsy>=0.5.2->statsmodels->hpbandster==0.7.4) (1.16.0)\n", "\u001b[33mWARNING: There was an error checking the latest version of pip.\u001b[0m\u001b[33m\n", "\u001b[0m" ] } ], "source": [ "# !pip install ray[tune]\n", "!pip install ConfigSpace==0.4.18\n", "!pip install hpbandster==0.7.4" ] }, { "cell_type": "markdown", "id": "96641e94", "metadata": {}, "source": [ "Click below to see all the imports we need for this example.\n", "You can also launch directly into a Binder instance to run this notebook yourself.\n", "Just click on the rocket symbol at the top of the navigation." ] }, { "cell_type": "code", "execution_count": 2, "id": "0e65ccdb", "metadata": { "tags": [ "hide-input" ] }, "outputs": [], "source": [ "import time\n", "\n", "import ray\n", "from ray import air, tune\n", "from ray.air import session\n", "from ray.tune.schedulers.hb_bohb import HyperBandForBOHB\n", "from ray.tune.search.bohb import TuneBOHB\n", "import ConfigSpace as CS" ] }, { "cell_type": "markdown", "id": "edba942a", "metadata": {}, "source": [ "Let's start by defining a simple evaluation function.\n", "We artificially sleep for a bit (`0.1` seconds) to simulate a long-running ML experiment.\n", "This setup assumes that we're running multiple `step`s of an experiment and try to tune\n", "two hyperparameters, namely `width` and `height`, and `activation`." ] }, { "cell_type": "code", "execution_count": 3, "id": "af512205", "metadata": {}, "outputs": [], "source": [ "def evaluate(step, width, height, activation):\n", " time.sleep(0.1)\n", " activation_boost = 10 if activation==\"relu\" else 1\n", " return (0.1 + width * step / 100) ** (-1) + height * 0.1 + activation_boost" ] }, { "cell_type": "markdown", "id": "c073ea21", "metadata": {}, "source": [ "Next, our `objective` function takes a Tune `config`, evaluates the `score` of your\n", "experiment in a training loop, and uses `session.report` to report the `score` back to Tune." ] }, { "cell_type": "code", "execution_count": 4, "id": "8a086e87", "metadata": {}, "outputs": [], "source": [ "def objective(config):\n", " for step in range(config[\"steps\"]):\n", " score = evaluate(step, config[\"width\"], config[\"height\"], config[\"activation\"])\n", " session.report({\"iterations\": step, \"mean_loss\": score})" ] }, { "cell_type": "code", "execution_count": 5, "id": "05d07329", "metadata": { "tags": [ "remove-cell" ] }, "outputs": [ { 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Python version:3.7.7
Ray version: 3.0.0.dev0
Dashboard:http://127.0.0.1:8265
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Current time: 2022-07-22 15:07:54 (running for 00:00:26.41)
Memory usage on this node: 9.9/16.0 GiB
Using HyperBand: num_stopped=9 total_brackets=1\n", "Round #0:\n", " Bracket(Max Size (n)=1, Milestone (r)=64, completed=66.8%): {TERMINATED: 10}
Resources requested: 0/16 CPUs, 0/0 GPUs, 0.0/4.95 GiB heap, 0.0/2.0 GiB objects
Current best trial: a0c11456 with mean_loss=-4.53376204004117 and parameters={'steps': 100, 'width': 3.7250202606878258, 'height': -57.97769618290691, 'activation': 'tanh'}
Result logdir: /Users/kai/ray_results/bohb_exp
Number of trials: 10/10 (10 TERMINATED)
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Trial name status loc activation height width loss iter total time (s) ts iterations neg_mean_loss
objective_9e8d8b06TERMINATED127.0.0.1:45117tanh 37.6516 12.2188 5.28254 16 2.23943 0 15 -5.28254
objective_a052a214TERMINATED127.0.0.1:45150relu -4.1062717.9931 11.1524 4 0.531915 0 3 -11.1524
objective_a06180d6TERMINATED127.0.0.1:45151tanh 89.5711 8.0551212.884 4 0.534212 0 3 -12.884
objective_a077899eTERMINATED127.0.0.1:45152relu 67.3538 13.6388 18.6994 4 0.538702 0 3 -18.6994
objective_a0865c76TERMINATED127.0.0.1:45153relu 25.9876 9.5710315.1819 4 0.559531 0 3 -15.1819
objective_a0a42d1eTERMINATED127.0.0.1:45154relu 80.9133 13.0972 20.1201 4 0.538588 0 3 -20.1201
objective_a0c11456TERMINATED127.0.0.1:45117tanh -57.9777 3.72502-4.53376 100 13.0563 0 99 4.53376
objective_a0dce442TERMINATED127.0.0.1:45200tanh -1.68715 1.87185 3.4575 16 2.27704 0 15 -3.4575
objective_a0f84156TERMINATED127.0.0.1:45157tanh 65.9879 5.4157511.4087 4 0.548028 0 3 -11.4087
objective_a1142416TERMINATED127.0.0.1:45201tanh 5.35569 4.85644 2.74262 16 2.27749 0 15 -2.74262


" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Result for objective_9e8d8b06:\n", " date: 2022-07-22_15-07-31\n", " done: false\n", " experiment_id: c1cb9895c3f04e73b7cce9435cd92c68\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 14.765164520733162\n", " neg_mean_loss: -14.765164520733162\n", " node_ip: 127.0.0.1\n", " pid: 45117\n", " time_since_restore: 0.10084700584411621\n", " time_this_iter_s: 0.10084700584411621\n", " time_total_s: 0.10084700584411621\n", " timestamp: 1658498851\n", " timesteps_since_restore: 0\n", " training_iteration: 1\n", " trial_id: 9e8d8b06\n", " warmup_time: 0.005752086639404297\n", " \n", "Result for objective_a06180d6:\n", " date: 2022-07-22_15-07-31\n", " done: false\n", " experiment_id: c1cb9895c3f04e73b7cce9435cd92c68\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 19.957107852020386\n", " neg_mean_loss: -19.957107852020386\n", " node_ip: 127.0.0.1\n", " pid: 45117\n", " time_since_restore: 0.10333395004272461\n", " time_this_iter_s: 0.10333395004272461\n", " time_total_s: 0.10333395004272461\n", " timestamp: 1658498851\n", " timesteps_since_restore: 0\n", " training_iteration: 1\n", " trial_id: a06180d6\n", " warmup_time: 0.005752086639404297\n", " \n", "Result for objective_a0a42d1e:\n", " date: 2022-07-22_15-07-31\n", " done: false\n", " experiment_id: c1cb9895c3f04e73b7cce9435cd92c68\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 28.091327935768636\n", " neg_mean_loss: -28.091327935768636\n", " node_ip: 127.0.0.1\n", " pid: 45117\n", " time_since_restore: 0.10419368743896484\n", " time_this_iter_s: 0.10419368743896484\n", " time_total_s: 0.10419368743896484\n", " timestamp: 1658498851\n", " timesteps_since_restore: 0\n", " training_iteration: 1\n", " trial_id: a0a42d1e\n", " warmup_time: 0.005752086639404297\n", " \n", "Result for objective_a0c11456:\n", " date: 2022-07-22_15-07-31\n", " done: false\n", " experiment_id: c1cb9895c3f04e73b7cce9435cd92c68\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 5.202230381709309\n", " neg_mean_loss: -5.202230381709309\n", " node_ip: 127.0.0.1\n", " pid: 45117\n", " time_since_restore: 0.10060286521911621\n", " time_this_iter_s: 0.10060286521911621\n", " time_total_s: 0.10060286521911621\n", " timestamp: 1658498851\n", " timesteps_since_restore: 0\n", " training_iteration: 1\n", " trial_id: a0c11456\n", " warmup_time: 0.005752086639404297\n", " \n", "Result for objective_a0dce442:\n", " date: 2022-07-22_15-07-32\n", " done: false\n", " experiment_id: c1cb9895c3f04e73b7cce9435cd92c68\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 10.831285273000042\n", " neg_mean_loss: -10.831285273000042\n", " node_ip: 127.0.0.1\n", " pid: 45117\n", " time_since_restore: 0.10183191299438477\n", " time_this_iter_s: 0.10183191299438477\n", " time_total_s: 0.10183191299438477\n", " timestamp: 1658498852\n", " timesteps_since_restore: 0\n", " training_iteration: 1\n", " trial_id: a0dce442\n", " warmup_time: 0.005752086639404297\n", " \n", "Result for objective_a0f84156:\n", " date: 2022-07-22_15-07-32\n", " done: false\n", " experiment_id: c1cb9895c3f04e73b7cce9435cd92c68\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 17.598785421495204\n", " neg_mean_loss: -17.598785421495204\n", " node_ip: 127.0.0.1\n", " pid: 45117\n", " time_since_restore: 0.10328507423400879\n", " time_this_iter_s: 0.10328507423400879\n", " time_total_s: 0.10328507423400879\n", " timestamp: 1658498852\n", " timesteps_since_restore: 0\n", " training_iteration: 1\n", " trial_id: a0f84156\n", " warmup_time: 0.005752086639404297\n", " \n", "Result for objective_a1142416:\n", " date: 2022-07-22_15-07-32\n", " done: false\n", " experiment_id: c1cb9895c3f04e73b7cce9435cd92c68\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 11.53556906389516\n", " neg_mean_loss: -11.53556906389516\n", " node_ip: 127.0.0.1\n", " pid: 45117\n", " time_since_restore: 0.10475611686706543\n", " time_this_iter_s: 0.10475611686706543\n", " time_total_s: 0.10475611686706543\n", " timestamp: 1658498852\n", " timesteps_since_restore: 0\n", " training_iteration: 1\n", " trial_id: a1142416\n", " warmup_time: 0.005752086639404297\n", " \n", "Result for objective_a052a214:\n", " date: 2022-07-22_15-07-34\n", " done: false\n", " experiment_id: 0fb96edfd1b34561b337e7146a3c64aa\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 19.5893732640325\n", " neg_mean_loss: -19.5893732640325\n", " node_ip: 127.0.0.1\n", " pid: 45126\n", " time_since_restore: 0.10437989234924316\n", " time_this_iter_s: 0.10437989234924316\n", " time_total_s: 0.10437989234924316\n", " timestamp: 1658498854\n", " timesteps_since_restore: 0\n", " training_iteration: 1\n", " trial_id: a052a214\n", " warmup_time: 0.003122091293334961\n", " \n", "Result for objective_a077899e:\n", " date: 2022-07-22_15-07-34\n", " done: false\n", " experiment_id: 008f8a44fb0c4475a3e9dad32f1bd2c9\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 26.735381559909975\n", " neg_mean_loss: -26.735381559909975\n", " node_ip: 127.0.0.1\n", " pid: 45129\n", " time_since_restore: 0.10449695587158203\n", " time_this_iter_s: 0.10449695587158203\n", " time_total_s: 0.10449695587158203\n", " timestamp: 1658498854\n", " timesteps_since_restore: 0\n", " training_iteration: 1\n", " trial_id: a077899e\n", " warmup_time: 0.0031490325927734375\n", " \n", "Result for objective_a0865c76:\n", " date: 2022-07-22_15-07-34\n", " done: false\n", " experiment_id: 06a194a4b7784ca5932a66e44e3cd815\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 22.598763488408313\n", " neg_mean_loss: -22.598763488408313\n", " node_ip: 127.0.0.1\n", " pid: 45132\n", " time_since_restore: 0.10512685775756836\n", " time_this_iter_s: 0.10512685775756836\n", " time_total_s: 0.10512685775756836\n", " timestamp: 1658498854\n", " timesteps_since_restore: 0\n", " training_iteration: 1\n", " trial_id: a0865c76\n", " warmup_time: 0.00397801399230957\n", " \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001b[2m\u001b[36m(objective pid=45117)\u001b[0m 2022-07-22 15:07:34,468\tINFO trainable.py:655 -- Restored on 127.0.0.1 from checkpoint: /Users/kai/ray_results/bohb_exp/objective_9e8d8b06_1_activation=tanh,height=37.6516,steps=100,width=12.2188_2022-07-22_15-07-28/checkpoint_tmpf674c6\n", 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after restoring: {'_iteration': 0, '_timesteps_total': 0, '_time_total': 0.10449695587158203, '_episodes_total': 0}\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Result for objective_a06180d6:\n", " date: 2022-07-22_15-07-38\n", " done: false\n", " episodes_total: 0\n", " experiment_id: c1cb9895c3f04e73b7cce9435cd92c68\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 19.957107852020386\n", " neg_mean_loss: -19.957107852020386\n", " node_ip: 127.0.0.1\n", " pid: 45151\n", " time_since_restore: 0.10456109046936035\n", " time_this_iter_s: 0.10456109046936035\n", " time_total_s: 0.20789504051208496\n", " timestamp: 1658498858\n", " timesteps_since_restore: 0\n", " timesteps_total: 0\n", " training_iteration: 1\n", " trial_id: a06180d6\n", " warmup_time: 0.010712862014770508\n", " \n", "Result for objective_a0c11456:\n", " date: 2022-07-22_15-07-38\n", " done: false\n", " episodes_total: 0\n", " experiment_id: c1cb9895c3f04e73b7cce9435cd92c68\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 5.202230381709309\n", " neg_mean_loss: -5.202230381709309\n", " node_ip: 127.0.0.1\n", " pid: 45155\n", " time_since_restore: 0.10466408729553223\n", " time_this_iter_s: 0.10466408729553223\n", " time_total_s: 0.20526695251464844\n", " timestamp: 1658498858\n", " timesteps_since_restore: 0\n", " timesteps_total: 0\n", " training_iteration: 1\n", " trial_id: a0c11456\n", " warmup_time: 0.007361888885498047\n", " \n", "Result for objective_a0a42d1e:\n", " date: 2022-07-22_15-07-38\n", " done: false\n", " episodes_total: 0\n", " experiment_id: c1cb9895c3f04e73b7cce9435cd92c68\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 28.091327935768636\n", " neg_mean_loss: -28.091327935768636\n", " node_ip: 127.0.0.1\n", " pid: 45154\n", " time_since_restore: 0.10032892227172852\n", " time_this_iter_s: 0.10032892227172852\n", " time_total_s: 0.20452260971069336\n", " timestamp: 1658498858\n", " timesteps_since_restore: 0\n", " timesteps_total: 0\n", " training_iteration: 1\n", " trial_id: a0a42d1e\n", " warmup_time: 0.008682966232299805\n", " \n", "Result for objective_a0dce442:\n", " date: 2022-07-22_15-07-38\n", " done: false\n", " episodes_total: 0\n", " experiment_id: c1cb9895c3f04e73b7cce9435cd92c68\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 10.831285273000042\n", " neg_mean_loss: -10.831285273000042\n", " node_ip: 127.0.0.1\n", " pid: 45156\n", " time_since_restore: 0.10120797157287598\n", " time_this_iter_s: 0.10120797157287598\n", " time_total_s: 0.20303988456726074\n", " timestamp: 1658498858\n", " timesteps_since_restore: 0\n", " timesteps_total: 0\n", " training_iteration: 1\n", " trial_id: a0dce442\n", " warmup_time: 0.0077381134033203125\n", " \n", "Result for objective_a1142416:\n", " date: 2022-07-22_15-07-38\n", " done: false\n", " episodes_total: 0\n", " experiment_id: c1cb9895c3f04e73b7cce9435cd92c68\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 11.53556906389516\n", " neg_mean_loss: -11.53556906389516\n", " node_ip: 127.0.0.1\n", " pid: 45158\n", " time_since_restore: 0.10349392890930176\n", " time_this_iter_s: 0.10349392890930176\n", " time_total_s: 0.2082500457763672\n", " timestamp: 1658498858\n", " timesteps_since_restore: 0\n", " timesteps_total: 0\n", " training_iteration: 1\n", " trial_id: a1142416\n", " warmup_time: 0.007157087326049805\n", " \n", "Result for objective_a0f84156:\n", " date: 2022-07-22_15-07-38\n", " done: false\n", " episodes_total: 0\n", " experiment_id: c1cb9895c3f04e73b7cce9435cd92c68\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 17.598785421495204\n", " neg_mean_loss: -17.598785421495204\n", " node_ip: 127.0.0.1\n", " pid: 45157\n", " time_since_restore: 0.10368680953979492\n", " time_this_iter_s: 0.10368680953979492\n", " time_total_s: 0.2069718837738037\n", " timestamp: 1658498858\n", " timesteps_since_restore: 0\n", " timesteps_total: 0\n", " training_iteration: 1\n", " trial_id: a0f84156\n", " warmup_time: 0.006359100341796875\n", " \n", "Result for objective_a052a214:\n", " date: 2022-07-22_15-07-38\n", " done: false\n", " episodes_total: 0\n", " experiment_id: 0fb96edfd1b34561b337e7146a3c64aa\n", " experiment_tag: 2_activation=relu,height=-4.1063,steps=100,width=17.9931\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 3\n", " iterations_since_restore: 4\n", " mean_loss: 11.152378612292932\n", " neg_mean_loss: -11.152378612292932\n", " node_ip: 127.0.0.1\n", " pid: 45150\n", " time_since_restore: 0.4275352954864502\n", " time_this_iter_s: 0.1124732494354248\n", " time_total_s: 0.5319151878356934\n", " timestamp: 1658498858\n", " timesteps_since_restore: 0\n", " timesteps_total: 0\n", " training_iteration: 4\n", " trial_id: a052a214\n", " warmup_time: 0.010692834854125977\n", " \n", "Result for objective_9e8d8b06:\n", " date: 2022-07-22_15-07-39\n", " done: false\n", " episodes_total: 0\n", " experiment_id: c1cb9895c3f04e73b7cce9435cd92c68\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 14.765164520733162\n", " neg_mean_loss: -14.765164520733162\n", " node_ip: 127.0.0.1\n", " pid: 45117\n", " time_since_restore: 0.10145044326782227\n", " time_this_iter_s: 0.10145044326782227\n", " time_total_s: 0.6308252811431885\n", " timestamp: 1658498859\n", " timesteps_since_restore: 0\n", " timesteps_total: 0\n", " training_iteration: 1\n", " trial_id: 9e8d8b06\n", " warmup_time: 0.005752086639404297\n", " \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001b[2m\u001b[36m(objective pid=45117)\u001b[0m 2022-07-22 15:07:39,222\tINFO trainable.py:655 -- Restored on 127.0.0.1 from 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"name": "stdout", "output_type": "stream", "text": [ "Result for objective_a0c11456:\n", " date: 2022-07-22_15-07-43\n", " done: false\n", " episodes_total: 0\n", " experiment_id: c1cb9895c3f04e73b7cce9435cd92c68\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 11\n", " iterations_since_restore: 12\n", " mean_loss: -2.8360322412948014\n", " neg_mean_loss: 2.8360322412948014\n", " node_ip: 127.0.0.1\n", " pid: 45199\n", " time_since_restore: 1.3028512001037598\n", " time_this_iter_s: 0.10884499549865723\n", " time_total_s: 1.8373572826385498\n", " timestamp: 1658498863\n", " timesteps_since_restore: 0\n", " timesteps_total: 0\n", " training_iteration: 12\n", " trial_id: a0c11456\n", " warmup_time: 0.0074689388275146484\n", " \n", "Result for objective_a0dce442:\n", " date: 2022-07-22_15-07-43\n", " done: false\n", " episodes_total: 0\n", " experiment_id: c1cb9895c3f04e73b7cce9435cd92c68\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 11\n", " iterations_since_restore: 12\n", " mean_loss: 4.100295137851358\n", " neg_mean_loss: -4.100295137851358\n", " node_ip: 127.0.0.1\n", " pid: 45200\n", " time_since_restore: 1.3082969188690186\n", " time_this_iter_s: 0.10707712173461914\n", " time_total_s: 1.8431987762451172\n", " timestamp: 1658498863\n", " timesteps_since_restore: 0\n", " timesteps_total: 0\n", " training_iteration: 12\n", " trial_id: a0dce442\n", " warmup_time: 0.007519960403442383\n", " \n", "Result for objective_a1142416:\n", " date: 2022-07-22_15-07-43\n", " done: false\n", " episodes_total: 0\n", " experiment_id: c1cb9895c3f04e73b7cce9435cd92c68\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 11\n", " iterations_since_restore: 12\n", " mean_loss: 3.112339173810433\n", " neg_mean_loss: -3.112339173810433\n", " node_ip: 127.0.0.1\n", " pid: 45201\n", " time_since_restore: 1.2954580783843994\n", " time_this_iter_s: 0.1081690788269043\n", " time_total_s: 1.8399872779846191\n", " timestamp: 1658498863\n", " timesteps_since_restore: 0\n", " timesteps_total: 0\n", " training_iteration: 12\n", " trial_id: a1142416\n", " warmup_time: 0.006086826324462891\n", " \n", "Result for objective_a1142416:\n", " date: 2022-07-22_15-07-43\n", " done: true\n", " episodes_total: 0\n", " experiment_id: c1cb9895c3f04e73b7cce9435cd92c68\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 15\n", " iterations_since_restore: 16\n", " mean_loss: 2.7426202715773025\n", " neg_mean_loss: -2.7426202715773025\n", " node_ip: 127.0.0.1\n", " pid: 45201\n", " time_since_restore: 1.7329609394073486\n", " time_this_iter_s: 0.1072549819946289\n", " time_total_s: 2.2774901390075684\n", " timestamp: 1658498863\n", " timesteps_since_restore: 0\n", " timesteps_total: 0\n", " training_iteration: 16\n", " trial_id: a1142416\n", " warmup_time: 0.006086826324462891\n", " \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001b[2m\u001b[36m(objective pid=45117)\u001b[0m 2022-07-22 15:07:43,765\tINFO trainable.py:655 -- Restored on 127.0.0.1 from checkpoint: /Users/kai/ray_results/bohb_exp/objective_a0c11456_7_activation=tanh,height=-57.9777,steps=100,width=3.7250_2022-07-22_15-07-31/checkpoint_tmp3f09eb\n", "\u001b[2m\u001b[36m(objective pid=45117)\u001b[0m 2022-07-22 15:07:43,765\tINFO trainable.py:663 -- Current state after restoring: {'_iteration': 0, '_timesteps_total': 0, '_time_total': 2.273958206176758, '_episodes_total': 0}\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Result for objective_a0c11456:\n", " date: 2022-07-22_15-07-48\n", " done: false\n", " episodes_total: 0\n", " experiment_id: c1cb9895c3f04e73b7cce9435cd92c68\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 40\n", " iterations_since_restore: 41\n", " mean_loss: -4.168842006342518\n", " neg_mean_loss: 4.168842006342518\n", " node_ip: 127.0.0.1\n", " pid: 45117\n", " time_since_restore: 4.4259912967681885\n", " time_this_iter_s: 0.10874629020690918\n", " time_total_s: 6.699949502944946\n", " timestamp: 1658498868\n", " timesteps_since_restore: 0\n", " timesteps_total: 0\n", " training_iteration: 41\n", " trial_id: a0c11456\n", " warmup_time: 0.005752086639404297\n", " \n", "Result for objective_a0c11456:\n", " date: 2022-07-22_15-07-53\n", " done: false\n", " episodes_total: 0\n", " experiment_id: c1cb9895c3f04e73b7cce9435cd92c68\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 87\n", " iterations_since_restore: 88\n", " mean_loss: -4.498437215767879\n", " neg_mean_loss: 4.498437215767879\n", " node_ip: 127.0.0.1\n", " pid: 45117\n", " time_since_restore: 9.488422155380249\n", " time_this_iter_s: 0.10667800903320312\n", " time_total_s: 11.762380361557007\n", " timestamp: 1658498873\n", " timesteps_since_restore: 0\n", " timesteps_total: 0\n", " training_iteration: 88\n", " trial_id: a0c11456\n", " warmup_time: 0.005752086639404297\n", " \n", "Result for objective_a0c11456:\n", " date: 2022-07-22_15-07-54\n", " done: true\n", " episodes_total: 0\n", " experiment_id: c1cb9895c3f04e73b7cce9435cd92c68\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 99\n", " iterations_since_restore: 100\n", " mean_loss: -4.53376204004117\n", " neg_mean_loss: 4.53376204004117\n", " node_ip: 127.0.0.1\n", " pid: 45117\n", " time_since_restore: 10.782363176345825\n", " time_this_iter_s: 0.1065070629119873\n", " time_total_s: 13.056321382522583\n", " timestamp: 1658498874\n", " timesteps_since_restore: 0\n", " timesteps_total: 0\n", " training_iteration: 100\n", " trial_id: a0c11456\n", " warmup_time: 0.005752086639404297\n", " \n" ] } ], "source": [ "tuner = tune.Tuner(\n", " objective,\n", " tune_config=tune.TuneConfig(\n", " metric=\"mean_loss\",\n", " mode=\"min\",\n", " search_alg=algo,\n", " scheduler=scheduler,\n", " num_samples=num_samples,\n", " ),\n", " run_config=air.RunConfig(\n", " name=\"bohb_exp\",\n", " stop={\"training_iteration\": 100},\n", " ),\n", " param_space=search_space,\n", ")\n", "results = tuner.fit()" ] }, { "cell_type": "markdown", "id": "3e89853c", "metadata": {}, "source": [ "Here are the hyperparameters found to minimize the mean loss of the defined objective." ] }, { "cell_type": "code", "execution_count": 11, "id": "4be691d5", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Best hyperparameters found were: {'steps': 100, 'width': 3.7250202606878258, 'height': -57.97769618290691, 'activation': 'tanh'}\n" ] } ], "source": [ "print(\"Best hyperparameters found were: \", results.get_best_result().config)" ] }, { "cell_type": "markdown", "id": "800a19d9", "metadata": {}, "source": [ "## Optional: Passing the search space via the TuneBOHB algorithm\n", "\n", "We can define the hyperparameter search space using `ConfigSpace`,\n", "which is the format accepted by BOHB." ] }, { "cell_type": "code", "execution_count": 12, "id": "b96cb496", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/Users/kai/.pyenv/versions/3.7.7/lib/python3.7/site-packages/ipykernel_launcher.py:3: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warning, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.\n", "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n", " This is separate from the ipykernel package so we can avoid doing imports until\n", "/Users/kai/.pyenv/versions/3.7.7/lib/python3.7/site-packages/ipykernel_launcher.py:6: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warning, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.\n", "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n", " \n", "/Users/kai/.pyenv/versions/3.7.7/lib/python3.7/site-packages/ipykernel_launcher.py:9: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warning, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.\n", "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n", " if __name__ == \"__main__\":\n", "/Users/kai/.pyenv/versions/3.7.7/lib/python3.7/site-packages/ipykernel_launcher.py:13: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warning, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.\n", "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n", " del sys.path[0]\n" ] }, { "data": { "text/plain": [ "activation, Type: Categorical, Choices: {relu, tanh}, Default: relu" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "config_space = CS.ConfigurationSpace()\n", "config_space.add_hyperparameter(\n", " CS.Constant(\"steps\", 100)\n", ")\n", "config_space.add_hyperparameter(\n", " CS.UniformFloatHyperparameter(\"width\", lower=0, upper=20)\n", ")\n", "config_space.add_hyperparameter(\n", " CS.UniformFloatHyperparameter(\"height\", lower=-100, upper=100)\n", ")\n", "config_space.add_hyperparameter(\n", " CS.CategoricalHyperparameter(\n", " \"activation\", choices=[\"relu\", \"tanh\"]\n", " )\n", ")" ] }, { "cell_type": "code", "execution_count": 13, "id": "9cb77270", "metadata": {}, "outputs": [], "source": [ "# As we are passing config space directly to the searcher,\n", "# we need to define metric and mode in it as well, in addition\n", "# to Tuner()\n", "algo = TuneBOHB(\n", " space=config_space,\n", " metric=\"mean_loss\",\n", " mode=\"max\",\n", ")\n", "algo = tune.search.ConcurrencyLimiter(algo, max_concurrent=4)\n", "scheduler = HyperBandForBOHB(\n", " time_attr=\"training_iteration\",\n", " max_t=100,\n", " reduction_factor=4,\n", " stop_last_trials=False,\n", ")" ] }, { "cell_type": "code", "execution_count": 17, "id": "8305c975", "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "text/html": [ "== Status ==
Current time: 2022-07-22 15:11:40 (running for 00:00:29.52)
Memory usage on this node: 10.3/16.0 GiB
Using HyperBand: num_stopped=9 total_brackets=1\n", "Round #0:\n", " Bracket(Max Size (n)=1, Milestone (r)=64, completed=66.8%): {TERMINATED: 10}
Resources requested: 0/16 CPUs, 0/0 GPUs, 0.0/4.95 GiB heap, 0.0/2.0 GiB objects
Current best trial: 25b64488 with mean_loss=-3.74634537130406 and parameters={'activation': 'tanh', 'height': -48.451797714080236, 'steps': 100, 'width': 10.119125894538891}
Result logdir: /Users/kai/ray_results/bohb_exp_2
Number of trials: 10/10 (10 TERMINATED)
\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
Trial name status loc activation height steps width loss iter total time (s) ts iterations neg_mean_loss
objective_2397442cTERMINATED127.0.0.1:45401tanh 32.8422 10012.1847 4.80297 16 2.25951 0 15 -4.80297
objective_25b4a998TERMINATED127.0.0.1:45401relu 20.2852 100 2.08202 18.1839 4 0.535426 0 3 -18.1839
objective_25b64488TERMINATED127.0.0.1:45453tanh -48.4518 10010.1191 -3.74635 100 11.5319 0 99 3.74635
objective_25b7dfe6TERMINATED127.0.0.1:45403relu -18.8439 10019.1277 9.59966 4 0.581903 0 3 -9.59966
objective_25cfab4eTERMINATED127.0.0.1:45404relu 17.2057 100 0.31708320.8519 4 0.59468 0 3 -20.8519
objective_278eba4cTERMINATED127.0.0.1:45454relu -27.0179 10013.577 7.76626 16 2.31198 0 15 -7.76626
objective_279d01a6TERMINATED127.0.0.1:45407relu 59.1103 100 2.4466 21.6781 4 0.575556 0 3 -21.6781
objective_27aa31e6TERMINATED127.0.0.1:45409relu 50.058 10017.3776 16.6153 4 0.537561 0 3 -16.6153
objective_27b7e2beTERMINATED127.0.0.1:45455relu -51.2093 100 8.94948 5.57235 16 2.64238 0 15 -5.57235
objective_27c59a80TERMINATED127.0.0.1:45446relu 29.165 100 4.26995 17.3006 4 0.539177 0 3 -17.3006


" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Result for objective_2397442c:\n", " date: 2022-07-22_15-11-15\n", " done: false\n", " experiment_id: 1a4ebf62df50443492dc6df792fcb67a\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 14.284216630043918\n", " neg_mean_loss: -14.284216630043918\n", " node_ip: 127.0.0.1\n", " pid: 45353\n", " time_since_restore: 0.10108494758605957\n", " time_this_iter_s: 0.10108494758605957\n", " time_total_s: 0.10108494758605957\n", " timestamp: 1658499075\n", " timesteps_since_restore: 0\n", " training_iteration: 1\n", " trial_id: 2397442c\n", " warmup_time: 0.002635955810546875\n", " \n", "Result for objective_25b7dfe6:\n", " date: 2022-07-22_15-11-17\n", " done: false\n", " experiment_id: 0fd6607aa9674cb5a05b6ce63e474fd3\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 18.115606120430186\n", " neg_mean_loss: -18.115606120430186\n", " node_ip: 127.0.0.1\n", " pid: 45371\n", " time_since_restore: 0.10365676879882812\n", " time_this_iter_s: 0.10365676879882812\n", " time_total_s: 0.10365676879882812\n", " timestamp: 1658499077\n", " timesteps_since_restore: 0\n", " training_iteration: 1\n", " trial_id: 25b7dfe6\n", " warmup_time: 0.005063056945800781\n", " \n", "Result for objective_25b4a998:\n", " date: 2022-07-22_15-11-17\n", " done: false\n", " experiment_id: 20a5d76dc18749e4b1c9f15c5d8b43cf\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 22.028519616352035\n", " neg_mean_loss: -22.028519616352035\n", " node_ip: 127.0.0.1\n", " pid: 45369\n", " time_since_restore: 0.10431909561157227\n", " time_this_iter_s: 0.10431909561157227\n", " time_total_s: 0.10431909561157227\n", " timestamp: 1658499077\n", " timesteps_since_restore: 0\n", " training_iteration: 1\n", " trial_id: 25b4a998\n", " warmup_time: 0.004379987716674805\n", " \n", "Result for objective_25b64488:\n", " date: 2022-07-22_15-11-17\n", " done: false\n", " experiment_id: 75e7c1ad20a2495cac29630df6c3c782\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 6.154820228591976\n", " neg_mean_loss: -6.154820228591976\n", " node_ip: 127.0.0.1\n", " pid: 45370\n", " time_since_restore: 0.10407018661499023\n", " time_this_iter_s: 0.10407018661499023\n", " time_total_s: 0.10407018661499023\n", " timestamp: 1658499077\n", " timesteps_since_restore: 0\n", " training_iteration: 1\n", " trial_id: 25b64488\n", " warmup_time: 0.003113985061645508\n", " \n", "Result for objective_25cfab4e:\n", " date: 2022-07-22_15-11-18\n", " done: false\n", " experiment_id: fdc43ca37ed44cde857ca150a8f1e84f\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 21.72056884033249\n", " neg_mean_loss: -21.72056884033249\n", " node_ip: 127.0.0.1\n", " pid: 45378\n", " time_since_restore: 0.10431408882141113\n", " time_this_iter_s: 0.10431408882141113\n", " time_total_s: 0.10431408882141113\n", " timestamp: 1658499078\n", " timesteps_since_restore: 0\n", " training_iteration: 1\n", " trial_id: 25cfab4e\n", " warmup_time: 0.0029649734497070312\n", " \n", "Result for objective_279d01a6:\n", " date: 2022-07-22_15-11-18\n", " done: false\n", " experiment_id: 20a5d76dc18749e4b1c9f15c5d8b43cf\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 25.911032294938884\n", " neg_mean_loss: -25.911032294938884\n", " node_ip: 127.0.0.1\n", " pid: 45369\n", " time_since_restore: 0.10361599922180176\n", " time_this_iter_s: 0.10361599922180176\n", " time_total_s: 0.10361599922180176\n", " timestamp: 1658499078\n", " timesteps_since_restore: 0\n", " training_iteration: 1\n", " trial_id: 279d01a6\n", " warmup_time: 0.004379987716674805\n", " \n", "Result for objective_27aa31e6:\n", " date: 2022-07-22_15-11-18\n", " done: false\n", " experiment_id: 75e7c1ad20a2495cac29630df6c3c782\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 25.005798678308594\n", " neg_mean_loss: -25.005798678308594\n", " node_ip: 127.0.0.1\n", " pid: 45370\n", " time_since_restore: 0.10430693626403809\n", " time_this_iter_s: 0.10430693626403809\n", " time_total_s: 0.10430693626403809\n", " timestamp: 1658499078\n", " timesteps_since_restore: 0\n", " training_iteration: 1\n", " trial_id: 27aa31e6\n", " warmup_time: 0.003113985061645508\n", " \n", "Result for objective_27b7e2be:\n", " date: 2022-07-22_15-11-18\n", " done: false\n", " experiment_id: fdc43ca37ed44cde857ca150a8f1e84f\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 14.879072389639937\n", " neg_mean_loss: -14.879072389639937\n", " node_ip: 127.0.0.1\n", " pid: 45378\n", " time_since_restore: 0.10371994972229004\n", " time_this_iter_s: 0.10371994972229004\n", " time_total_s: 0.10371994972229004\n", " timestamp: 1658499078\n", " timesteps_since_restore: 0\n", " training_iteration: 1\n", " trial_id: 27b7e2be\n", " warmup_time: 0.0029649734497070312\n", " \n", "Result for objective_27c59a80:\n", " date: 2022-07-22_15-11-18\n", " done: false\n", " experiment_id: 20a5d76dc18749e4b1c9f15c5d8b43cf\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 22.916501000037474\n", " neg_mean_loss: -22.916501000037474\n", " node_ip: 127.0.0.1\n", " pid: 45369\n", " time_since_restore: 0.10353732109069824\n", " time_this_iter_s: 0.10353732109069824\n", " time_total_s: 0.10353732109069824\n", " timestamp: 1658499078\n", " timesteps_since_restore: 0\n", " training_iteration: 1\n", " trial_id: 27c59a80\n", " warmup_time: 0.004379987716674805\n", " \n", "Result for objective_278eba4c:\n", " date: 2022-07-22_15-11-20\n", " done: false\n", " experiment_id: 90186993d7ff42698c4615640d47d896\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 17.29821256734647\n", " neg_mean_loss: -17.29821256734647\n", " node_ip: 127.0.0.1\n", " pid: 45393\n", " time_since_restore: 0.10304784774780273\n", " time_this_iter_s: 0.10304784774780273\n", " time_total_s: 0.10304784774780273\n", " timestamp: 1658499080\n", " timesteps_since_restore: 0\n", " training_iteration: 1\n", " trial_id: 278eba4c\n", " warmup_time: 0.0027189254760742188\n", " \n", "Result for objective_2397442c:\n", " date: 2022-07-22_15-11-20\n", " done: false\n", " episodes_total: 0\n", " experiment_id: 1a4ebf62df50443492dc6df792fcb67a\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 14.284216630043918\n", " neg_mean_loss: -14.284216630043918\n", " node_ip: 127.0.0.1\n", " pid: 45370\n", " time_since_restore: 0.10411787033081055\n", " time_this_iter_s: 0.10411787033081055\n", " time_total_s: 0.20520281791687012\n", " timestamp: 1658499080\n", " timesteps_since_restore: 0\n", " timesteps_total: 0\n", " training_iteration: 1\n", " trial_id: 2397442c\n", " warmup_time: 0.003113985061645508\n", " \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001b[2m\u001b[36m(objective pid=45370)\u001b[0m 2022-07-22 15:11:20,826\tINFO trainable.py:655 -- Restored on 127.0.0.1 from checkpoint: /Users/kai/ray_results/bohb_exp_2/objective_2397442c_1_activation=tanh,height=32.8422,steps=100,width=12.1847_2022-07-22_15-11-11/checkpoint_tmpf4b290\n", "\u001b[2m\u001b[36m(objective pid=45370)\u001b[0m 2022-07-22 15:11:20,826\tINFO trainable.py:663 -- Current state after restoring: {'_iteration': 0, '_timesteps_total': 0, '_time_total': 0.10108494758605957, '_episodes_total': 0}\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Result for objective_25b4a998:\n", " date: 2022-07-22_15-11-24\n", " done: false\n", " episodes_total: 0\n", " experiment_id: 20a5d76dc18749e4b1c9f15c5d8b43cf\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 22.028519616352035\n", " neg_mean_loss: -22.028519616352035\n", " node_ip: 127.0.0.1\n", " pid: 45401\n", " time_since_restore: 0.10445284843444824\n", " time_this_iter_s: 0.10445284843444824\n", " time_total_s: 0.2087719440460205\n", " timestamp: 1658499084\n", " timesteps_since_restore: 0\n", " timesteps_total: 0\n", " training_iteration: 1\n", " trial_id: 25b4a998\n", " warmup_time: 0.010488033294677734\n", " \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001b[2m\u001b[36m(objective pid=45405)\u001b[0m 2022-07-22 15:11:23,963\tINFO trainable.py:655 -- Restored on 127.0.0.1 from checkpoint: 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trainable.py:655 -- Restored on 127.0.0.1 from checkpoint: /Users/kai/ray_results/bohb_exp_2/objective_25b64488_3_activation=tanh,height=-48.4518,steps=100,width=10.1191_2022-07-22_15-11-14/checkpoint_tmp5ce175\n", "\u001b[2m\u001b[36m(objective pid=45402)\u001b[0m 2022-07-22 15:11:23,966\tINFO trainable.py:663 -- Current state after restoring: {'_iteration': 0, '_timesteps_total': 0, '_time_total': 0.10407018661499023, '_episodes_total': 0}\n", "\u001b[2m\u001b[36m(objective pid=45407)\u001b[0m 2022-07-22 15:11:23,966\tINFO trainable.py:655 -- Restored on 127.0.0.1 from checkpoint: /Users/kai/ray_results/bohb_exp_2/objective_279d01a6_7_activation=relu,height=59.1103,steps=100,width=2.4466_2022-07-22_15-11-18/checkpoint_tmp942eac\n", "\u001b[2m\u001b[36m(objective pid=45407)\u001b[0m 2022-07-22 15:11:23,966\tINFO trainable.py:663 -- Current state after restoring: {'_iteration': 0, '_timesteps_total': 0, '_time_total': 0.10361599922180176, '_episodes_total': 0}\n", "\u001b[2m\u001b[36m(objective pid=45404)\u001b[0m 2022-07-22 15:11:23,960\tINFO trainable.py:655 -- Restored on 127.0.0.1 from checkpoint: /Users/kai/ray_results/bohb_exp_2/objective_25cfab4e_5_activation=relu,height=17.2057,steps=100,width=0.3171_2022-07-22_15-11-15/checkpoint_tmpc8ceee\n", "\u001b[2m\u001b[36m(objective pid=45404)\u001b[0m 2022-07-22 15:11:23,960\tINFO trainable.py:663 -- Current state after restoring: {'_iteration': 0, '_timesteps_total': 0, '_time_total': 0.10431408882141113, '_episodes_total': 0}\n", "\u001b[2m\u001b[36m(objective pid=45403)\u001b[0m 2022-07-22 15:11:23,966\tINFO trainable.py:655 -- Restored on 127.0.0.1 from checkpoint: /Users/kai/ray_results/bohb_exp_2/objective_25b7dfe6_4_activation=relu,height=-18.8439,steps=100,width=19.1277_2022-07-22_15-11-14/checkpoint_tmp24108b\n", "\u001b[2m\u001b[36m(objective pid=45403)\u001b[0m 2022-07-22 15:11:23,966\tINFO trainable.py:663 -- Current state after restoring: {'_iteration': 0, '_timesteps_total': 0, '_time_total': 0.10365676879882812, '_episodes_total': 0}\n", "\u001b[2m\u001b[36m(objective pid=45409)\u001b[0m 2022-07-22 15:11:23,997\tINFO trainable.py:655 -- Restored on 127.0.0.1 from checkpoint: /Users/kai/ray_results/bohb_exp_2/objective_27aa31e6_8_activation=relu,height=50.0580,steps=100,width=17.3776_2022-07-22_15-11-18/checkpoint_tmp4218e5\n", "\u001b[2m\u001b[36m(objective pid=45409)\u001b[0m 2022-07-22 15:11:23,997\tINFO trainable.py:663 -- Current state after restoring: {'_iteration': 0, '_timesteps_total': 0, '_time_total': 0.10430693626403809, '_episodes_total': 0}\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Result for objective_27aa31e6:\n", " date: 2022-07-22_15-11-24\n", " done: false\n", " episodes_total: 0\n", " experiment_id: 75e7c1ad20a2495cac29630df6c3c782\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 25.005798678308594\n", " neg_mean_loss: -25.005798678308594\n", " node_ip: 127.0.0.1\n", " pid: 45409\n", " time_since_restore: 0.10203695297241211\n", " time_this_iter_s: 0.10203695297241211\n", " time_total_s: 0.2063438892364502\n", " timestamp: 1658499084\n", " timesteps_since_restore: 0\n", " timesteps_total: 0\n", " training_iteration: 1\n", " trial_id: 27aa31e6\n", " warmup_time: 0.0062160491943359375\n", " \n", "Result for objective_279d01a6:\n", " date: 2022-07-22_15-11-24\n", " done: false\n", " episodes_total: 0\n", " experiment_id: 20a5d76dc18749e4b1c9f15c5d8b43cf\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 25.911032294938884\n", " neg_mean_loss: -25.911032294938884\n", " node_ip: 127.0.0.1\n", " pid: 45407\n", " time_since_restore: 0.10443115234375\n", " time_this_iter_s: 0.10443115234375\n", " time_total_s: 0.20804715156555176\n", " timestamp: 1658499084\n", " timesteps_since_restore: 0\n", " timesteps_total: 0\n", " training_iteration: 1\n", " trial_id: 279d01a6\n", " warmup_time: 0.010073184967041016\n", " \n", "Result for objective_25b7dfe6:\n", " date: 2022-07-22_15-11-24\n", " done: false\n", " episodes_total: 0\n", " experiment_id: 0fd6607aa9674cb5a05b6ce63e474fd3\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 18.115606120430186\n", " neg_mean_loss: -18.115606120430186\n", " node_ip: 127.0.0.1\n", " pid: 45403\n", " time_since_restore: 0.1044917106628418\n", " time_this_iter_s: 0.1044917106628418\n", " time_total_s: 0.20814847946166992\n", " timestamp: 1658499084\n", " timesteps_since_restore: 0\n", " timesteps_total: 0\n", " training_iteration: 1\n", " trial_id: 25b7dfe6\n", " warmup_time: 0.011971235275268555\n", " \n", "Result for objective_25cfab4e:\n", " date: 2022-07-22_15-11-24\n", " done: false\n", " episodes_total: 0\n", " experiment_id: fdc43ca37ed44cde857ca150a8f1e84f\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 21.72056884033249\n", " neg_mean_loss: -21.72056884033249\n", " node_ip: 127.0.0.1\n", " pid: 45404\n", " time_since_restore: 0.10379600524902344\n", " time_this_iter_s: 0.10379600524902344\n", " time_total_s: 0.20811009407043457\n", " timestamp: 1658499084\n", " timesteps_since_restore: 0\n", " timesteps_total: 0\n", " training_iteration: 1\n", " trial_id: 25cfab4e\n", " warmup_time: 0.009023904800415039\n", " \n", "Result for objective_25b64488:\n", " date: 2022-07-22_15-11-24\n", " done: false\n", " episodes_total: 0\n", " experiment_id: 75e7c1ad20a2495cac29630df6c3c782\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 6.154820228591976\n", " neg_mean_loss: -6.154820228591976\n", " node_ip: 127.0.0.1\n", " pid: 45402\n", " time_since_restore: 0.10440897941589355\n", " time_this_iter_s: 0.10440897941589355\n", " time_total_s: 0.2084791660308838\n", " timestamp: 1658499084\n", " timesteps_since_restore: 0\n", " timesteps_total: 0\n", " training_iteration: 1\n", " trial_id: 25b64488\n", " warmup_time: 0.011686325073242188\n", " \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001b[2m\u001b[36m(objective pid=45424)\u001b[0m 2022-07-22 15:11:24,383\tINFO trainable.py:655 -- Restored on 127.0.0.1 from checkpoint: /Users/kai/ray_results/bohb_exp_2/objective_27b7e2be_9_activation=relu,height=-51.2093,steps=100,width=8.9495_2022-07-22_15-11-18/checkpoint_tmp996dec\n", "\u001b[2m\u001b[36m(objective pid=45424)\u001b[0m 2022-07-22 15:11:24,384\tINFO trainable.py:663 -- Current state after restoring: {'_iteration': 0, '_timesteps_total': 0, '_time_total': 0.10371994972229004, '_episodes_total': 0}\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Result for objective_27b7e2be:\n", " date: 2022-07-22_15-11-24\n", " done: false\n", " episodes_total: 0\n", " experiment_id: fdc43ca37ed44cde857ca150a8f1e84f\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 14.879072389639937\n", " neg_mean_loss: -14.879072389639937\n", " node_ip: 127.0.0.1\n", " pid: 45424\n", " time_since_restore: 0.1031639575958252\n", " time_this_iter_s: 0.1031639575958252\n", " time_total_s: 0.20688390731811523\n", " timestamp: 1658499084\n", " timesteps_since_restore: 0\n", " timesteps_total: 0\n", " training_iteration: 1\n", " trial_id: 27b7e2be\n", " warmup_time: 0.0069200992584228516\n", " \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001b[2m\u001b[36m(objective pid=45446)\u001b[0m 2022-07-22 15:11:26,749\tINFO trainable.py:655 -- Restored on 127.0.0.1 from checkpoint: /Users/kai/ray_results/bohb_exp_2/objective_27c59a80_10_activation=relu,height=29.1650,steps=100,width=4.2700_2022-07-22_15-11-18/checkpoint_tmp49d063\n", "\u001b[2m\u001b[36m(objective pid=45446)\u001b[0m 2022-07-22 15:11:26,749\tINFO trainable.py:663 -- Current state after restoring: {'_iteration': 0, '_timesteps_total': 0, '_time_total': 0.10353732109069824, '_episodes_total': 0}\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Result for objective_27c59a80:\n", " date: 2022-07-22_15-11-26\n", " done: false\n", " episodes_total: 0\n", " experiment_id: 20a5d76dc18749e4b1c9f15c5d8b43cf\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 22.916501000037474\n", " neg_mean_loss: -22.916501000037474\n", " node_ip: 127.0.0.1\n", " pid: 45446\n", " time_since_restore: 0.10502910614013672\n", " time_this_iter_s: 0.10502910614013672\n", " time_total_s: 0.20856642723083496\n", " timestamp: 1658499086\n", " timesteps_since_restore: 0\n", " timesteps_total: 0\n", " training_iteration: 1\n", " trial_id: 27c59a80\n", " warmup_time: 0.007359027862548828\n", " \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001b[2m\u001b[36m(objective pid=45401)\u001b[0m 2022-07-22 15:11:27,287\tINFO trainable.py:655 -- Restored on 127.0.0.1 from checkpoint: /Users/kai/ray_results/bohb_exp_2/objective_2397442c_1_activation=tanh,height=32.8422,steps=100,width=12.1847_2022-07-22_15-11-11/checkpoint_tmp2e0d09\n", "\u001b[2m\u001b[36m(objective pid=45401)\u001b[0m 2022-07-22 15:11:27,287\tINFO trainable.py:663 -- Current state after restoring: {'_iteration': 0, '_timesteps_total': 0, '_time_total': 0.535153865814209, '_episodes_total': 0}\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Result for objective_2397442c:\n", " date: 2022-07-22_15-11-27\n", " done: false\n", " episodes_total: 0\n", " experiment_id: 1a4ebf62df50443492dc6df792fcb67a\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 14.284216630043918\n", " neg_mean_loss: -14.284216630043918\n", " node_ip: 127.0.0.1\n", " pid: 45401\n", " time_since_restore: 0.1044008731842041\n", " time_this_iter_s: 0.1044008731842041\n", " time_total_s: 0.6395547389984131\n", " timestamp: 1658499087\n", " timesteps_since_restore: 0\n", " timesteps_total: 0\n", " training_iteration: 1\n", " trial_id: 2397442c\n", " warmup_time: 0.010488033294677734\n", " \n", "Result for objective_278eba4c:\n", " date: 2022-07-22_15-11-29\n", " done: false\n", " episodes_total: 0\n", " experiment_id: 90186993d7ff42698c4615640d47d896\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 17.29821256734647\n", " neg_mean_loss: -17.29821256734647\n", " node_ip: 127.0.0.1\n", " pid: 45454\n", " time_since_restore: 0.1037449836730957\n", " time_this_iter_s: 0.1037449836730957\n", " time_total_s: 0.6844677925109863\n", " timestamp: 1658499089\n", " timesteps_since_restore: 0\n", " timesteps_total: 0\n", " training_iteration: 1\n", " trial_id: 278eba4c\n", " warmup_time: 0.006754875183105469\n", " \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\u001b[2m\u001b[36m(objective pid=45454)\u001b[0m 2022-07-22 15:11:29,879\tINFO trainable.py:655 -- Restored on 127.0.0.1 from checkpoint: /Users/kai/ray_results/bohb_exp_2/objective_278eba4c_6_activation=relu,height=-27.0179,steps=100,width=13.5770_2022-07-22_15-11-18/checkpoint_tmp2835d4\n", "\u001b[2m\u001b[36m(objective pid=45454)\u001b[0m 2022-07-22 15:11:29,879\tINFO trainable.py:663 -- Current state after restoring: {'_iteration': 0, '_timesteps_total': 0, '_time_total': 0.5807228088378906, '_episodes_total': 0}\n", "\u001b[2m\u001b[36m(objective pid=45455)\u001b[0m 2022-07-22 15:11:29,909\tINFO trainable.py:655 -- Restored on 127.0.0.1 from checkpoint: /Users/kai/ray_results/bohb_exp_2/objective_27b7e2be_9_activation=relu,height=-51.2093,steps=100,width=8.9495_2022-07-22_15-11-18/checkpoint_tmpd7ea63\n", "\u001b[2m\u001b[36m(objective pid=45455)\u001b[0m 2022-07-22 15:11:29,910\tINFO trainable.py:663 -- Current state after restoring: {'_iteration': 0, '_timesteps_total': 0, '_time_total': 0.9150340557098389, '_episodes_total': 0}\n", "\u001b[2m\u001b[36m(objective pid=45453)\u001b[0m 2022-07-22 15:11:29,930\tINFO trainable.py:655 -- Restored on 127.0.0.1 from checkpoint: /Users/kai/ray_results/bohb_exp_2/objective_25b64488_3_activation=tanh,height=-48.4518,steps=100,width=10.1191_2022-07-22_15-11-14/checkpoint_tmp11824e\n", "\u001b[2m\u001b[36m(objective pid=45453)\u001b[0m 2022-07-22 15:11:29,930\tINFO trainable.py:663 -- Current state after restoring: {'_iteration': 0, '_timesteps_total': 0, '_time_total': 0.5960800647735596, '_episodes_total': 0}\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Result for objective_27b7e2be:\n", " date: 2022-07-22_15-11-30\n", " done: false\n", " episodes_total: 0\n", " experiment_id: fdc43ca37ed44cde857ca150a8f1e84f\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 14.879072389639937\n", " neg_mean_loss: -14.879072389639937\n", " node_ip: 127.0.0.1\n", " pid: 45455\n", " time_since_restore: 0.10332393646240234\n", " time_this_iter_s: 0.10332393646240234\n", " time_total_s: 1.0183579921722412\n", " timestamp: 1658499090\n", " timesteps_since_restore: 0\n", " timesteps_total: 0\n", " training_iteration: 1\n", " trial_id: 27b7e2be\n", " warmup_time: 0.006285190582275391\n", " \n", "Result for objective_25b64488:\n", " date: 2022-07-22_15-11-30\n", " done: false\n", " episodes_total: 0\n", " experiment_id: 75e7c1ad20a2495cac29630df6c3c782\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 0\n", " iterations_since_restore: 1\n", " mean_loss: 6.154820228591976\n", " neg_mean_loss: -6.154820228591976\n", " node_ip: 127.0.0.1\n", " pid: 45453\n", " time_since_restore: 0.1026160717010498\n", " time_this_iter_s: 0.1026160717010498\n", " time_total_s: 0.6986961364746094\n", " timestamp: 1658499090\n", " timesteps_since_restore: 0\n", " timesteps_total: 0\n", " training_iteration: 1\n", " trial_id: 25b64488\n", " warmup_time: 0.006460905075073242\n", " \n", "Result for objective_25b64488:\n", " date: 2022-07-22_15-11-35\n", " done: false\n", " episodes_total: 0\n", " experiment_id: 75e7c1ad20a2495cac29630df6c3c782\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 46\n", " iterations_since_restore: 47\n", " mean_loss: -3.634865890857194\n", " neg_mean_loss: 3.634865890857194\n", " node_ip: 127.0.0.1\n", " pid: 45453\n", " time_since_restore: 5.1935131549835205\n", " time_this_iter_s: 0.10786604881286621\n", " time_total_s: 5.78959321975708\n", " timestamp: 1658499095\n", " timesteps_since_restore: 0\n", " timesteps_total: 0\n", " training_iteration: 47\n", " trial_id: 25b64488\n", " warmup_time: 0.006460905075073242\n", " \n", "Result for objective_25b64488:\n", " date: 2022-07-22_15-11-40\n", " done: false\n", " episodes_total: 0\n", " experiment_id: 75e7c1ad20a2495cac29630df6c3c782\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 93\n", " iterations_since_restore: 94\n", " mean_loss: -3.740036002402735\n", " neg_mean_loss: 3.740036002402735\n", " node_ip: 127.0.0.1\n", " pid: 45453\n", " time_since_restore: 10.256795167922974\n", " time_this_iter_s: 0.10682511329650879\n", " time_total_s: 10.852875232696533\n", " timestamp: 1658499100\n", " timesteps_since_restore: 0\n", " timesteps_total: 0\n", " training_iteration: 94\n", " trial_id: 25b64488\n", " warmup_time: 0.006460905075073242\n", " \n", "Result for objective_25b64488:\n", " date: 2022-07-22_15-11-40\n", " done: true\n", " episodes_total: 0\n", " experiment_id: 75e7c1ad20a2495cac29630df6c3c782\n", " hostname: Kais-MacBook-Pro.local\n", " iterations: 99\n", " iterations_since_restore: 100\n", " mean_loss: -3.74634537130406\n", " neg_mean_loss: 3.74634537130406\n", " node_ip: 127.0.0.1\n", " pid: 45453\n", " time_since_restore: 10.935801029205322\n", " time_this_iter_s: 0.10489487648010254\n", " time_total_s: 11.531881093978882\n", " timestamp: 1658499100\n", " timesteps_since_restore: 0\n", " timesteps_total: 0\n", " training_iteration: 100\n", " trial_id: 25b64488\n", " warmup_time: 0.006460905075073242\n", " \n" ] } ], "source": [ "tuner = tune.Tuner(\n", " objective,\n", " tune_config=tune.TuneConfig(\n", " metric=\"mean_loss\",\n", " mode=\"min\",\n", " search_alg=algo,\n", " scheduler=scheduler,\n", " num_samples=num_samples,\n", " ),\n", " run_config=air.RunConfig(\n", " name=\"bohb_exp_2\",\n", " stop={\"training_iteration\": 100},\n", " ),\n", ")\n", "results = tuner.fit()" ] }, { "cell_type": "markdown", "id": "5bf0dd87", "metadata": {}, "source": [ "Here again are the hyperparameters found to minimize the mean loss of the\n", "defined objective." ] }, { "cell_type": "code", "execution_count": 18, "id": "1ae613e4", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Best hyperparameters found were: {'activation': 'tanh', 'height': -48.451797714080236, 'steps': 100, 'width': 10.119125894538891}\n" ] } ], "source": [ "print(\"Best hyperparameters found were: \", results.get_best_result().config)" ] }, { "cell_type": "code", "execution_count": 19, "id": "6b83ef6d", "metadata": { "tags": [ "remove-cell" ] }, "outputs": [], "source": [ "ray.shutdown()" ] } ], "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": "3.7.7" }, "orphan": true, "vscode": { "interpreter": { "hash": "3c0d54d489a08ae47a06eae2fd00ff032d6cddb527c382959b7b2575f6a8167f" } } }, "nbformat": 4, "nbformat_minor": 5 }