{ "cells": [ { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "# An overview of GluonTS" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "### Opensource python toolkit based on Apache MXNet and Gluon\n", "\n", "- Implementations of state of the art models\n", "- Baseline models\n", "- Tools for model evaluation and comparison\n", "- Dataloaders and iterators" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "### Models:\n", "- DeepAR\n", "- Deep factor\n", "- DeepState\n", "- Wavenet\n", "- Transformer models \n", "- Seq-2-seq models\n", "- etc." ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "## Components of GluonTS" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "notes" } }, "source": [ "### Dataset\n", "- **Dataset** abstraction for providing uniform access to data across different input formats\n", "- In GluonTS, any Dataset is just an Iterable over dictionaries mapping string keys to arbitrary values\n", "- There are two variations of dataset: **FileDataSet** and **ListDataset**\n", "- In order to implement your own dataset:\n", " - you will need to derive a class from `gluonts.dataset.common.Dataset`, and\n", " - implement `__iter__`, and `__len__`\n", " - more information can be found [here](https://github.com/awslabs/gluon-ts/blob/master/src/gluonts/dataset/common.py).\n" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "notes" } }, "source": [ "- A dataset object requires start and target (pandas timestamp)\n", "- Please note that your data does not require to have a timestamp field but should be aggregated as ***fixed-length intervals***.\n", "- You shall need to pass a frequency parameter, which is compatible with pandas frequency.\n", "- **ListDataset** to access data stored in memory as a list of dictionaries." ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "### Dataset" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "fragment" } }, "source": [ "```python\n", "from gluonts.dataset.common import ListDataset\n", "\n", "training_data = ListDataset(\n", " [{\"start\": df.index[0], \"target\": df.value[:\"2015-04-05 00:00:00\"]}],\n", " freq = \"5min\"\n", ")\n", "```" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "### The Estimator and the Predictor\n", "- An **Estimator** represents a model that can be trained on a dataset to yield\n", "- a **Predictor**, which can later be used to make predictions on unseen data.\n" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "fragment" } }, "source": [ "```python\n", "from gluonts.model.deepar import DeepAREstimator\n", "from gluonts.trainer import Trainer\n", "\n", "estimator = DeepAREstimator(freq=\"5min\", \n", " prediction_length=36, \n", " trainer=Trainer(epochs=10))\n", "```" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "notes" } }, "source": [ "```python\n", "from gluonts.model.deepar import DeepAREstimator \n", "```\n", "- `DeepArEstimator` is an abstraction for models. \n", "- Other supported estimators include:\n", " - Seq2SeqEstimator\n", " - CanonicalRNNEstimator\n", " - SimpleFeedForwardEstimator\n", " - WaveNetEstimator" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "### Predictor\n", "- you can call your estimator's **train** methods to kick-off training.\n", "- train will return a **predictor** object after completes the training.\n", "- You can then use the predictor object in order to make inference." ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "fragment" } }, "source": [ "```python\n", "predictor = estimator.train(training_data)\n", "```" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "### Evaluation\n", "- You can use the predictor in order to create a forecast:\n" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "fragment" } }, "source": [ "```python\n", "from gluonts.evaluation.backtest import make_evaluation_predictions\n", "\n", "forecast_it, ts_it = make_evaluation_predictions(\n", " test_data, \n", " predictor, \n", " num_samples=100)\n", "forecasts = list(forecast_it)\n", "tss = list(ts_it)\n", "```" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "notes" } }, "source": [ "```python\n", "def plot_forecasts(tss, forecasts, past_length):\n", " for target, forecast in islice(zip(tss, forecasts)):\n", " ax = target[-past_length:].plot(figsize=(12, 5), linewidth=2)\n", " forecast.plot(color='g')\n", " plt.grid(which='both')\n", " plt.legend([\"observations\", \"median prediction\", \"90% confidence interval\", \"50% confidence interval\"])\n", " plt.show()\n", "```" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "### Plotting the forecast\n", "- Plotting the forecast gives you a qualitative feel for the model output." ] }, { "attachments": { "image.png": { "image/png": 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" } }, "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "fragment" } }, "source": [ "```python\n", "plot_forecasts(tss, forecasts, past_length=150, num_plots=3)\n", "```\n", "![image.png](attachment:image.png)" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "### Evaluator class\n", "- **Evaluator** provides a multi-metric quantitative evaluation of the model." ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "fragment" } }, "source": [ "```python\n", "from gluonts.evaluation import Evaluator\n", "\n", "evaluator = Evaluator(quantiles=[0.5], seasonality=1)\n", "agg_metrics, item_metrics = evaluator(iter(tss), iter(forecasts), num_series=len(test_data))\n", "```" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "```python\n", "agg_metrics\n", "\n", "{'MSE': 163.59102376302084,\n", " 'abs_error': 1090.9220886230469,\n", " 'abs_target_sum': 5658.0,\n", " 'abs_target_mean': 52.38888888888889,\n", " 'seasonal_error': 18.833625618877182,\n", " 'MASE': 0.5361500323952336,\n", " 'sMAPE': 0.21201368270827592,\n", " 'MSIS': 21.446000940010823,\n", " 'QuantileLoss[0.5]': 1090.9221000671387,\n", " 'Coverage[0.5]': 0.34259259259259256,\n", " 'RMSE': 12.790270668090681,\n", " 'NRMSE': 0.24414090352665138,\n", " 'ND': 0.19281054942082837,\n", " 'wQuantileLoss[0.5]': 0.19281055144346743,\n", " 'mean_wQuantileLoss': 0.19281055144346743,\n", " 'MAE_Coverage': 0.15740740740740744}\n", "```" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "# Lab 1\n", " \n", "Optional: [Descriptive statistics](../part2/descriptive_stats.ipynb)\n", " \n", " \n", "[Build and train a DeepAR model with GluonTS](../part3/twitter_volume_forecast.ipynb)\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "slideshow": { "slide_type": "notes" } }, "outputs": [], "source": [] } ], "metadata": { 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