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2nd committee meeting setup + best hyperparams range
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,132 @@ | ||
| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "## Import experiments from former MLflow UI\n", | ||
| "\n", | ||
| "\n", | ||
| "this is a workaround if mlflow does not react with too many experiments on Euler" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 1, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "import mlflow\n", | ||
| "import pandas as pd\n", | ||
| "\n", | ||
| "# Read the CSV file\n", | ||
| "df = pd.read_csv(\"models/intermediate_rtrac5c_r0r3_le2y_cpu_t10.csv\")" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 2, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "# df.columns.tolist()" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 3, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "experiment_name = \"euler_imported3\"\n", | ||
| "mlflow.create_experiment(experiment_name)\n", | ||
| "\n", | ||
| "# Get the experiment ID\n", | ||
| "experiment = mlflow.get_experiment_by_name(experiment_name)\n", | ||
| "experiment_id = experiment.experiment_id\n", | ||
| "\n", | ||
| "# Define the custom order for the models\n", | ||
| "model_order = {\n", | ||
| " \"linreg\": 1,\n", | ||
| " \"trac\": 2,\n", | ||
| " \"xgb\": 3,\n", | ||
| " \"nn_reg\": 4,\n", | ||
| " \"nn_class\": 5,\n", | ||
| " \"nn_corn\": 6,\n", | ||
| " \"rf\": 7,\n", | ||
| "}\n", | ||
| "\n", | ||
| "# Iterate over the rows of the DataFrame and log each run\n", | ||
| "for _, row in df.iterrows():\n", | ||
| " with mlflow.start_run(experiment_id=experiment_id):\n", | ||
| " # Log the metrics, parameters, and tags from the CSV\n", | ||
| " for key, value in row.items():\n", | ||
| " if key.startswith(\"metrics.\"):\n", | ||
| " metric_name = key.split(\".\", 1)[1]\n", | ||
| " mlflow.log_metric(metric_name, value)\n", | ||
| " elif key.startswith(\"params.\"):\n", | ||
| " param_name = key.split(\".\", 1)[1]\n", | ||
| " mlflow.log_param(param_name, value)\n", | ||
| " elif key == \"model\":\n", | ||
| " mlflow.log_param(\"model\", value)\n", | ||
| " # Log the model order as a separate parameter\n", | ||
| " mlflow.log_param(\"model_order\", model_order.get(value, 999))\n", | ||
| " elif key == \"time_total_s\":\n", | ||
| " mlflow.log_metric(\"time_total_s\", value)\n", | ||
| " elif key.startswith(\"tags.\"):\n", | ||
| " tag_name = key.split(\".\", 1)[1]\n", | ||
| " mlflow.set_tag(tag_name, value)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 4, | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "name": "stdout", | ||
| "output_type": "stream", | ||
| "text": [ | ||
| "[2024-05-05 13:41:53 +0200] [35348] [INFO] Starting gunicorn 21.2.0\n", | ||
| "[2024-05-05 13:41:53 +0200] [35348] [INFO] Listening at: http://127.0.0.1:5004 (35348)\n", | ||
| "[2024-05-05 13:41:53 +0200] [35348] [INFO] Using worker: sync\n", | ||
| "[2024-05-05 13:41:53 +0200] [35350] [INFO] Booting worker with pid: 35350\n", | ||
| "[2024-05-05 13:41:53 +0200] [35352] [INFO] Booting worker with pid: 35352\n", | ||
| "[2024-05-05 13:41:53 +0200] [35353] [INFO] Booting worker with pid: 35353\n", | ||
| "[2024-05-05 13:41:53 +0200] [35354] [INFO] Booting worker with pid: 35354\n", | ||
| "^C\n", | ||
| "[2024-05-05 13:44:47 +0200] [35348] [INFO] Handling signal: int\n", | ||
| "[2024-05-05 13:44:47 +0200] [35352] [INFO] Worker exiting (pid: 35352)\n", | ||
| "[2024-05-05 13:44:47 +0200] [35350] [INFO] Worker exiting (pid: 35350)\n", | ||
| "[2024-05-05 13:44:47 +0200] [35354] [INFO] Worker exiting (pid: 35354)\n", | ||
| "[2024-05-05 13:44:47 +0200] [35353] [INFO] Worker exiting (pid: 35353)\n" | ||
| ] | ||
| } | ||
| ], | ||
| "source": [ | ||
| "! mlflow ui --port 5004" | ||
| ] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": "ritme_wclasso_f", | ||
| "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": "3.8.0" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 2 | ||
| } |
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