{
"cells": [
{
"cell_type": "markdown",
"id": "130d0e72-62b8-4d38-8989-28b2e4a4ef48",
"metadata": {
"tags": []
},
"source": [
"# Running an R Script with BOA\n",
"\n",
"This notebook demonstrates how to:\n",
"\n",
"Write a basic Wrapper script in R and have BOA launch your optimization using the BOA CLI interface. See {mod}`instructions for creating a model wrapper <.boa.wrappers>` for more details about creating a wrapper script.\n",
"You can also look at {doc}`instructions for configurations files` for more details on creating a configuration file."
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "27dcc4de-d3d0-4865-aa1e-667d2b0ff2b1",
"metadata": {
"tags": [
"remove-cell"
]
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"[WARNING 07-13 14:30:45] ax.service.utils.with_db_settings_base: Ax currently requires a sqlalchemy version below 2.0. This will be addressed in a future release. Disabling SQL storage in Ax for now, if you would like to use SQL storage please install Ax with mysql extras via `pip install ax-platform[mysql]`.\n"
]
},
{
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" function inject_raw_css(css) {\n",
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" element.appendChild(document.createTextNode(css));\n",
" document.body.appendChild(element);\n",
" }\n",
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" var js_urls = [\"https://cdn.holoviz.org/panel/1.2.0/dist/bundled/jquery/jquery.slim.min.js\", \"https://cdn.holoviz.org/panel/1.2.0/dist/bundled/plotlyplot/plotly-2.18.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-3.2.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.2.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.2.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.2.0.min.js\", \"https://cdn.holoviz.org/panel/1.2.0/dist/panel.min.js\"];\n",
" var js_modules = [];\n",
" var js_exports = {};\n",
" var css_urls = [];\n",
" var inline_js = [ function(Bokeh) {\n",
" Bokeh.set_log_level(\"info\");\n",
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"function(Bokeh) {} // ensure no trailing comma for IE\n",
" ];\n",
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" for (var i = 0; i < inline_js.length; i++) {\n",
" inline_js[i].call(root, root.Bokeh);\n",
" }\n",
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" if (Bokeh != undefined && !reloading) {\n",
"\tvar NewBokeh = root.Bokeh;\n",
"\tif (Bokeh.versions === undefined) {\n",
"\t Bokeh.versions = new Map();\n",
"\t}\n",
"\tif (NewBokeh.version !== Bokeh.version) {\n",
"\t Bokeh.versions.set(NewBokeh.version, NewBokeh)\n",
"\t}\n",
"\troot.Bokeh = Bokeh;\n",
" }} else if (Date.now() < root._bokeh_timeout) {\n",
" setTimeout(run_inline_js, 100);\n",
" } else if (!root._bokeh_failed_load) {\n",
" console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
" root._bokeh_failed_load = true;\n",
" }\n",
" root._bokeh_is_initializing = false\n",
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"\n",
" function load_or_wait() {\n",
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" // to determine whether there is an ongoing attempt to initialize\n",
" // bokeh, however for backward compatibility we also try to ensure\n",
" // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n",
" // before older versions are fully initialized.\n",
" if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n",
" root._bokeh_is_initializing = false;\n",
" root._bokeh_onload_callbacks = undefined;\n",
" console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n",
" load_or_wait();\n",
" } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n",
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" } else {\n",
" Bokeh = root.Bokeh;\n",
" bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n",
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" setTimeout(load_or_wait, 100)\n",
"}(window));"
],
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i < links.length; i++) {\n var link = links[i]\n if (link.href != null) {\n\texisting_stylesheets.push(link.href)\n }\n }\n for (var i = 0; i < css_urls.length; i++) {\n var url = css_urls[i];\n if (existing_stylesheets.indexOf(url) !== -1) {\n\ton_load()\n\tcontinue;\n }\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n } if (((window['Plotly'] !== undefined) && (!(window['Plotly'] instanceof HTMLElement))) || window.requirejs) {\n var urls = ['https://cdn.holoviz.org/panel/1.2.0/dist/bundled/plotlyplot/plotly-2.18.0.min.js'];\n for (var i = 0; i < urls.length; i++) {\n skip.push(urls[i])\n }\n } if (((window['jsPanel'] !== undefined) && (!(window['jsPanel'] instanceof HTMLElement))) || window.requirejs) {\n var urls = ['https://cdn.holoviz.org/panel/1.2.0/dist/bundled/floatpanel/jspanel4@4.12.0/dist/jspanel.js', 'https://cdn.holoviz.org/panel/1.2.0/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal.js', 'https://cdn.holoviz.org/panel/1.2.0/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip.js', 'https://cdn.holoviz.org/panel/1.2.0/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint.js', 'https://cdn.holoviz.org/panel/1.2.0/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout.js', 'https://cdn.holoviz.org/panel/1.2.0/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu.js', 'https://cdn.holoviz.org/panel/1.2.0/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock.js'];\n for (var i = 0; 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"source": [
"# This notebook uses hidden cells to import and display things so\n",
"# that it can be ran regullary to make sure the documentation\n",
"# is up to date and not broken (as opposed to a markdown file\n",
"# that would have an exmaple written once and get out of date\n",
"# as the code base changes)\n",
"\n",
"# These hidden cells are only responsible for rerunning\n",
"# the documentation to ensure it is correct.\n",
"# the actual relavent part of the documentation\n",
"# are the non hidden parts\n",
"import pathlib\n",
"import re\n",
"import shutil\n",
"\n",
"from IPython.display import Code\n",
"\n",
"import boa"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "a1149922-0d89-4146-9236-7ff758f44435",
"metadata": {
"tags": [
"remove-cell"
]
},
"outputs": [],
"source": [
"boa_dir = pathlib.Path().resolve().parent.parent\n",
"r_dir = boa_dir / \"tests/scripts/other_langs/r_package_streamlined\"\n",
"config_path = r_dir / \"config.yaml\"\n",
"wrapper_script_path = r_dir / \"run_model.R\"\n",
"hartman6_path = r_dir.parent / \"r_utils/hartman6.R\"\n",
"\n",
"config = boa.load_jsonlike(config_path)\n",
"ex_name = config[\"optimization_options\"][\"experiment\"][\"name\"]\n",
"total_trials = config[\"optimization_options\"][\"trials\"]"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "66812670-9c0b-4ddb-9dfd-5ff0cbb45a3f",
"metadata": {
"tags": [
"remove-cell"
]
},
"outputs": [],
"source": [
"# Remove old runs to have a clean slate for this example\n",
"old_runs = pathlib.Path().resolve().glob(f\"{ex_name}*\")\n",
"for path in old_runs:\n",
" shutil.rmtree(path)\n",
"old_runs = r_dir.glob(f\"{ex_name}*\")\n",
"for path in old_runs:\n",
" shutil.rmtree(path)"
]
},
{
"cell_type": "markdown",
"id": "74999810-5017-46f2-9ea6-d19e6ac55164",
"metadata": {},
"source": [
"## Configuration File Overview\n",
"\n",
"config.yaml"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "6050297d-3485-48bc-bcba-49b8e1f0eb0d",
"metadata": {
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"text/html": [
"optimization_options:\n",
" objective_options:\n",
" objectives:\n",
" - name: metric\n",
" experiment:\n",
" name: "r_streamlined_run"\n",
" trials: 15\n",
"\n",
"parameters:\n",
" x0:\n",
" 'bounds': [ 0, 1 ]\n",
" 'type': 'range'\n",
" 'value_type': 'float'\n",
" x1:\n",
" 'bounds': [ 0, 1]\n",
" 'type': 'range'\n",
" 'value_type': 'float'\n",
" x2:\n",
" 'bounds': [ 0, 1 ]\n",
" 'type': 'range'\n",
" 'value_type': 'float'\n",
" x3:\n",
" 'bounds': [ 0, 1]\n",
" 'type': 'range'\n",
" 'value_type': 'float'\n",
" x4:\n",
" 'bounds': [ 0, 1 ]\n",
" 'type': 'range'\n",
" 'value_type': 'float'\n",
" x5:\n",
" 'bounds': [ 0, 1]\n",
" 'type': 'range'\n",
" 'value_type': 'float'\n",
"\n",
"script_options:\n",
" # notice here that this is a shell command\n",
" # this is what BOA will do to launch your script\n",
" # it will also pass as a command line argument the current trial directory\n",
" # that is being parameterized\n",
"\n",
" # This can either be a relative path or absolute path\n",
" # (by default when BOA launches from a config file\n",
" # it uses the config file directory as your working directory)\n",
" # here config.yaml and run_model.R are in the same directory\n",
" run_model: Rscript run_model.R\n",
"\n",
"\n",
"# options only needed by the model and not BOA\n",
"# You can put anything here that your model might need\n",
"# We don't need anything extra so we leave it commented out\n",
"# model_options:\n",
" # the_question: 42\n",
"# load in any libraries and modules we need\n",
"library(jsonlite)\n",
"source("../r_utils/hartman6.R")\n",
"\n",
"# This is where we read in from BOA the command line argument.\n",
"# If in your script, you use any other command line arguments,\n",
"# generally BOA's trial_dir should be the last command line arugment,\n",
"# so taking the last one should generally be safe.\n",
"args <- commandArgs(trailingOnly=TRUE)\n",
"trial_dir <- args[length(args)]\n",
"\n",
"# this this trial_dir folder there are 2 files supplied by BOA,\n",
"# a parameters.json that has just the parameters, and a trial.json\n",
"# that includes the parameters and a lot more in case you need it.\n",
"# Most people will only need the parameters.json\n",
"param_path <- file.path(trial_dir, "parameters.json")\n",
"data <- read_json(path=param_path)\n",
"\n",
"# The parameter keys config from whatever you named them in your\n",
"# config file, which you are free to change.\n",
"x0 <- data$x0\n",
"x1 <- data$x1\n",
"x2 <- data$x2\n",
"x3 <- data$x3\n",
"x4 <- data$x4\n",
"x5 <- data$x5\n",
"X <- c(x0, x1, x2, x3, x4, x5)\n",
"\n",
"# This is where we actually run our "model".\n",
"# Here we are using a synthetic function called hartman6\n",
"# But you could substitute it for your own model in\n",
"# a number of ways.\n",
"res <- hartman6(X)\n",
"\n",
"# In this case, we directly ran the model, so we are getting back a number\n",
"# or nan, so we know if it succeeded or failed. If you are submitting a job\n",
"# to an HPC (a super computer) queue, this might work, or you might have to\n",
"# rely on another method. Other options could be relying on log file output\n",
"# or information from querying the queue itself,\n",
"# though those may be better as stand alone `Set Trial Status Scripts`\n",
"if (!is.na(res)) {\n",
"\n",
" # if it was a success, we don't even need to write out trial status,\n",
" # it is assumed a success if we write out data and don't fail\n",
" out_data <- list(\n",
" metric=res\n",
" # trial_status=unbox("COMPLETED") # this is optional if it succeeds\n",
" )\n",
"\n",
"} else {\n",
"\n",
" # If we fail, then we do need to include a trial status, and mark it as failed.\n",
" out_data <- list(\n",
" trial_status=unbox("FAILED")\n",
" )\n",
"}\n",
"\n",
"json_data <- toJSON(out_data, pretty = TRUE)\n",
"write(json_data, file.path(trial_dir, "output.json"))\n",
"hartman6 <- function(X) {\n",
" out <- tryCatch(\n",
" {\n",
" alpha <- c(1.0, 1.2, 3.0, 3.2)\n",
" A <- c(10, 3, 17, 3.5, 1.7, 8,\n",
" 0.05, 10, 17, 0.1, 8, 14,\n",
" 3, 3.5, 1.7, 10, 17, 8,\n",
" 17, 8, 0.05, 10, 0.1, 14)\n",
" A <- matrix(A, 4, 6, byrow=TRUE)\n",
" P <- 10^(-4) * c(1312, 1696, 5569, 124, 8283, 5886,\n",
" 2329, 4135, 8307, 3736, 1004, 9991,\n",
" 2348, 1451, 3522, 2883, 3047, 6650,\n",
" 4047, 8828, 8732, 5743, 1091, 381)\n",
" P <- matrix(P, 4, 6, byrow=TRUE)\n",
"\n",
" Xmat <- matrix(rep(X,times=4), 4, 6, byrow=TRUE)\n",
" inner_sum <- rowSums(A[,1:6]*(Xmat-P[,1:6])^2)\n",
" outer_sum <- sum(alpha * exp(-inner_sum))\n",
" y <- -outer_sum\n",
" return(y)\n",
" },\n",
" error=function(cond) {\n",
" return(NA)\n",
" }\n",
" )\n",
" return(out)\n",
"}\n",
"[WARNING 07-13 14:30:49] ax.service.utils.with_db_settings_base: Ax currently requires a sqlalchemy version below 2.0. This will be addressed in a future release. Disabling SQL storage in Ax for now, if you would like to use SQL storage please install Ax with mysql extras via `pip install ax-platform[mysql]`.\n",
"[INFO 07-13 14:30:50] ax.service.utils.instantiation: Created search space: SearchSpace(parameters=[RangeParameter(name='x0', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x1', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x2', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x3', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x4', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x5', parameter_type=FLOAT, range=[0.0, 1.0])], parameter_constraints=[]).\n",
"[INFO 07-13 14:30:50] ax.modelbridge.dispatch_utils: Using Models.GPEI since there are more ordered parameters than there are categories for the unordered categorical parameters.\n",
"[INFO 07-13 14:30:50] ax.modelbridge.dispatch_utils: Calculating the number of remaining initialization trials based on num_initialization_trials=None max_initialization_trials=None num_tunable_parameters=6 num_trials=None use_batch_trials=False\n",
"[INFO 07-13 14:30:50] ax.modelbridge.dispatch_utils: calculated num_initialization_trials=12\n",
"[INFO 07-13 14:30:50] ax.modelbridge.dispatch_utils: num_completed_initialization_trials=0 num_remaining_initialization_trials=12\n",
"[INFO 07-13 14:30:50] ax.modelbridge.dispatch_utils: Using Bayesian Optimization generation strategy: GenerationStrategy(name='Sobol+GPEI', steps=[Sobol for 12 trials, GPEI for subsequent trials]). Iterations after 12 will take longer to generate due to model-fitting.\n",
"[INFO 07-13 14:30:50] Scheduler: `Scheduler` requires experiment to have immutable search space and optimization config. Setting property immutable_search_space_and_opt_config to `True` on experiment.\n",
"[INFO 2023-07-13 14:30:50,865 MainProcess] boa: \n",
"\n",
"##############################################\n",
"\n",
"\n",
"BOA Experiment Run\n",
"Output Experiment Dir: [/path/to/your/dir/]/r_streamlined_run_20230713T143050\n",
"Start Time: 20230713T143050\n",
"Version: 0.8.7.dev4+gae30cf2.d20230713\n",
"\n",
"##############################################\n",
"\n",
"[INFO 07-13 14:30:50] Scheduler: Running trials [0]...\n",
"[INFO 07-13 14:30:52] Scheduler: Running trials [1]...\n",
"[INFO 07-13 14:30:54] Scheduler: Running trials [2]...\n",
"[INFO 07-13 14:30:56] Scheduler: Running trials [3]...\n",
"[INFO 07-13 14:30:57] Scheduler: Running trials [4]...\n",
"[INFO 07-13 14:30:59] Scheduler: Running trials [5]...\n",
"[INFO 07-13 14:31:00] Scheduler: Running trials [6]...\n",
"[INFO 07-13 14:31:01] Scheduler: Running trials [7]...\n",
"[INFO 07-13 14:31:04] Scheduler: Running trials [8]...\n",
"[INFO 07-13 14:31:07] Scheduler: Running trials [9]...\n",
"[INFO 07-13 14:31:08] Scheduler: Retrieved COMPLETED trials: 0 - 9.\n",
"[INFO 07-13 14:31:08] Scheduler: Fetching data for trials: 0 - 9.\n",
"[INFO 2023-07-13 14:31:08,745 MainProcess] boa: Saved JSON-serialized state of optimization to `[/path/to/your/dir/]/r_streamlined_run_20230713T143050/scheduler.json`.\n",
"Boa version: 0.8.7.dev4+gae30cf2.d20230713\n",
"[INFO 2023-07-13 14:31:08,803 MainProcess] boa: Trials so far: 10\n",
"Running trials: \n",
"Will Produce next trials from generation step: Sobol\n",
"Best trial so far: {9: {'metric': -0.5032}}\n",
"[INFO 07-13 14:31:08] Scheduler: Running trials [10]...\n",
"[INFO 07-13 14:31:09] Scheduler: Running trials [11]...\n",
"[INFO 07-13 14:31:15] Scheduler: Running trials [12]...\n",
"[INFO 07-13 14:31:16] ax.modelbridge.torch: The observations are identical to the last set of observations used to fit the model. Skipping model fitting.\n",
"[INFO 07-13 14:31:21] Scheduler: Running trials [13]...\n",
"[INFO 07-13 14:31:22] ax.modelbridge.torch: The observations are identical to the last set of observations used to fit the model. Skipping model fitting.\n",
"[INFO 07-13 14:31:24] Scheduler: Running trials [14]...\n",
"[INFO 07-13 14:31:26] Scheduler: Retrieved COMPLETED trials: 10 - 14.\n",
"[INFO 07-13 14:31:26] Scheduler: Fetching data for trials: 10 - 14.\n",
"[INFO 2023-07-13 14:31:26,333 MainProcess] boa: Saved JSON-serialized state of optimization to `[/path/to/your/dir/]/r_streamlined_run_20230713T143050/scheduler.json`.\n",
"Boa version: 0.8.7.dev4+gae30cf2.d20230713\n",
"[INFO 2023-07-13 14:31:26,360 MainProcess] boa: Trials so far: 15\n",
"Running trials: \n",
"Will Produce next trials from generation step: GPEI\n",
"Best trial so far: {12: {'metric': -0.6201}}\n",
"[INFO 2023-07-13 14:31:26,375 MainProcess] boa: Saved JSON-serialized state of optimization to `[/path/to/your/dir/]/r_streamlined_run_20230713T143050/scheduler.json`.\n",
"Boa version: 0.8.7.dev4+gae30cf2.d20230713\n",
"[INFO 2023-07-13 14:31:26,400 MainProcess] boa: Trials so far: 15\n",
"Running trials: \n",
"Will Produce next trials from generation step: GPEI\n",
"Best trial so far: {12: {'metric': -0.6201}}\n",
"[INFO 2023-07-13 14:31:26,422 MainProcess] boa: \n",
"\n",
"##############################################\n",
"\n",
"Trials Completed!\n",
"BOA Experiment Run\n",
"Output Experiment Dir: [/path/to/your/dir/]/r_streamlined_run_20230713T143050\n",
"Start Time: 20230713T143050\n",
"Version: 0.8.7.dev4+gae30cf2.d20230713\n",
"End Time: 20230713T143126\n",
"Total Run Time: 35.53495001792908\n",
"\n",
" trial_index arm_name trial_status ... x3 x4 x5\n",
"0 0 0_0 COMPLETED ... 0.755183 0.548820 0.555407\n",
"1 1 1_0 COMPLETED ... 0.441893 0.777394 0.218111\n",
"2 2 2_0 COMPLETED ... 0.833717 0.685323 0.358227\n",
"3 3 3_0 COMPLETED ... 0.337164 0.706950 0.410019\n",
"4 4 4_0 COMPLETED ... 0.842163 0.989052 0.966872\n",
"5 5 5_0 COMPLETED ... 0.081540 0.828128 0.128949\n",
"6 6 6_0 COMPLETED ... 0.138704 0.598400 0.496507\n",
"7 7 7_0 COMPLETED ... 0.723201 0.459715 0.961720\n",
"8 8 8_0 COMPLETED ... 0.614263 0.018990 0.856079\n",
"9 9 9_0 COMPLETED ... 0.324603 0.855542 0.100329\n",
"10 10 10_0 COMPLETED ... 0.955197 0.150812 0.603905\n",
"11 11 11_0 COMPLETED ... 0.646193 0.756861 0.555784\n",
"12 12 12_0 COMPLETED ... 0.301131 0.897643 0.021916\n",
"13 13 13_0 COMPLETED ... 0.379400 0.892975 0.053183\n",
"14 14 14_0 COMPLETED ... 0.280032 0.808321 0.174706\n",
"\n",
"[15 rows x 11 columns]\n",
"\n",
"##############################################\n",
"