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models quickstart - new colab #617

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123 changes: 123 additions & 0 deletions colabs/intro/run_quickstart.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"##Use W&B to track, visualize, and manage machine learning experiments of any size.\n",
"To authenticate your machine with W&B, you need a W&B API key.\n",
"Save key to Google Colab Secrets under name WANDB_API_KEY. Enable notebook access for key.\n",
"\n",
"A [run](/models/runs/) is a core element of W&B. You use runs to [track metrics](/models/track/), [create logs](/models/track/log/), track artifacts, and more.\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"!pip install wandb"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import wandb\n",
"import os\n",
"from google.colab import userdata\n",
"\n",
"os.environ[\"WANDB_API_KEY\"] = userdata.get(\"WANDB_API_KEY\")\n",
"\n",
"\n",
"wandb.login()\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Set up project and track hyperparameters\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import wandb\n",
"\n",
"# Project that the run is recorded to\n",
"project = \"my-run-quickstart\"\n",
"\n",
"# Hyperparameters\n",
"config = {\n",
" \"epochs\": 10,\n",
" \"lr\": 0.01,\n",
"}\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"\n",
"## Create a machine learning training experiment\n",
"\n",
"This mock training script logs simulated accuracy and loss metrics to W&B.\n",
"\n",
"\n",
"Initialize a W&B run object with [`wandb.init()`](/models/ref/python/experiments/run/). Use a dictionary for the `config` parameter\n",
"to specify hyperparameter names and values. Within the `with` statement, you can log metrics and other information to W&B.\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"\n",
"import random\n",
"\n",
"\n",
"with wandb.init(project=project, config=config) as run:\n",
" offset = random.random() / 5\n",
" print(f\"lr: {config['lr']}\")\n",
"\n",
" for epoch in range(2, config[\"epochs\"]):\n",
" acc = 1 - 2**-config[\"epochs\"] - random.random() / config[\"epochs\"] - offset\n",
" loss = 2**-config[\"epochs\"] + random.random() / config[\"epochs\"] + offset\n",
"\n",
" print(f\"epoch={epoch}, accuracy={acc:.4f}, loss={loss:.4f}\")\n",
" run.log({\"epoch\": epoch, \"accuracy\": acc, \"loss\": loss})\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Visit the custom \"View run\" link in the prior cell's output (or go to wandb.ai/home) to view recorded metrics such as accuracy and loss and how they changed during each training step. W&B Runs show the loss and accuracy tracked from each run. Each run object appears in the Runs page with auto-generated names."
]
}
],
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
},
"language_info": {
"name": "python"
}
},
"nbformat": 4,
"nbformat_minor": 0
}