{ "cells": [ { "cell_type": "markdown", "id": "52143102", "metadata": {}, "source": [ "# Time Series Forecasting\n", "\n", "In this tutorial, we will go through how to forecast with `GenTS` models and datasets. \n", "\n", "## Problem setting\n", "Given a look back window, $\\mathbf{x}_{\\text{obs}} \\in \\mathbb{R}^{L \\times D}$, we are interested in the conditional distribution, i.e. $p(\\mathbf{x}_{\\text{target}} \\mid \\mathbf{x}_{\\text{obs}})$. From this distribution, we can sample possible forecasts $\\hat{\\mathbf{x}}_{\\text{target}} \\in \\mathbb{R}^{T \\times D}$" ] }, { "cell_type": "markdown", "id": "106de7d6", "metadata": {}, "source": [ "## Implementation\n", "### 1. import modules" ] }, { "cell_type": "code", "execution_count": 1, "id": "1489bcad", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/home/wcx/anaconda3/envs/gents/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", " from .autonotebook import tqdm as notebook_tqdm\n", "CUDA extension for cauchy multiplication not found. Install by going to extensions/cauchy/ and running `python setup.py install`. This should speed up end-to-end training by 10-50%\n", "Falling back on slow Cauchy kernel. Install at least one of pykeops or the CUDA extension for efficiency.\n", "Falling back on slow Vandermonde kernel. Install pykeops for improved memory efficiency.\n" ] } ], "source": [ "import torch\n", "from gents.dataset import Spiral2D\n", "from gents.model import VanillaDDPM\n", "from gents.evaluation import predict_visual, crps\n", "from lightning import Trainer" ] }, { "cell_type": "markdown", "id": "f7d87805", "metadata": {}, "source": [ "### 2. setup datamodule and model\n", "Here, we set $L=T=32$ for an example. Note that `condition='predict'` and `obs_len=32` is also required for datamodule and model for setup." ] }, { "cell_type": "code", "execution_count": 2, "id": "b1aedf41", "metadata": {}, "outputs": [], "source": [ "dm = Spiral2D(\n", " seq_len=32,\n", " obs_len=32,\n", " batch_size=64,\n", " data_dir=\"../data\",\n", " condition=\"predict\",\n", ")\n", "model = VanillaDDPM(\n", " obs_len=dm.obs_len, seq_len=dm.seq_len, seq_dim=dm.seq_dim, condition=\"predict\"\n", ")" ] }, { "cell_type": "markdown", "id": "06b25dc7", "metadata": {}, "source": [ "### 3. setup training\n", "Utilizing `lightning`/`pytorch-lightning`, one can easily set:\n", "- GPU devices\n", "- Training epochs/steps\n", "- Callbacks\n", "- etc.." ] }, { "cell_type": "code", "execution_count": 3, "id": "73227496", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "GPU available: True (cuda), used: True\n", "TPU available: False, using: 0 TPU cores\n", "HPU available: False, using: 0 HPUs\n", "You are using a CUDA device ('NVIDIA GeForce RTX 3080 Ti') that has Tensor Cores. To properly utilize them, you should set `torch.set_float32_matmul_precision('medium' | 'high')` which will trade-off precision for performance. For more details, read https://pytorch.org/docs/stable/generated/torch.set_float32_matmul_precision.html#torch.set_float32_matmul_precision\n", "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2,3]\n", "\n", " | Name | Type | Params | Mode \n", "------------------------------------------\n", "0 | backbone | DiT | 1.2 M | train\n", "------------------------------------------\n", "1.2 M Trainable params\n", "512 Non-trainable params\n", "1.2 M Total params\n", "4.734 Total estimated model params size (MB)\n", "85 Modules in train mode\n", "0 Modules in eval mode\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Downloading 2DSpiral dataset in ../data/2DSpiral.pt\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "`Trainer.fit` stopped: `max_epochs=10` reached.\n" ] } ], "source": [ "trainer = Trainer(max_epochs=10, devices=[0], enable_progress_bar=False)\n", "trainer.fit(model, dm)" ] }, { "cell_type": "markdown", "id": "146abe3d", "metadata": {}, "source": [ "### 4. forecasting on the test set\n", "Here `n_sample=10` means we sample $\\hat{\\mathbf{x}}_{\\text{target}} \\in \\mathbb{R}^{T \\times D}$ 10 times. The tensor shape of `gen_data` is `[batch_size, T, D, n_sample]`" ] }, { "cell_type": "code", "execution_count": 4, "id": "e3622147", "metadata": {}, "outputs": [], "source": [ "# testing\n", "dm.setup(\"test\")\n", "real_data = torch.cat([batch[\"seq\"] for batch in dm.test_dataloader()])\n", "cond_data = torch.cat([batch[\"c\"] for batch in dm.test_dataloader()])\n", "\n", "gen_data = model.sample(\n", " n_sample=10,\n", " condition=cond_data,\n", ")" ] }, { "cell_type": "markdown", "id": "5dbfc16c", "metadata": {}, "source": [ "### 5. Evaluation\n", "`GenTS` provides a plot function for visualizing probabilistic forecasts, as well as some metrics like CRPS to quantitative evaluation" ] }, { "cell_type": "code", "execution_count": 5, "id": "e071e81b", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "np.float64(0.011574582569024659)" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "predict_visual(\n", " real_data=real_data,\n", " gen_data=gen_data,\n", " data_mask=torch.ones_like(real_data).bool(),\n", " # uncomment the following line to save the plot\n", " # save_root='./predict.png'\n", ")\n", "crps(real_data[:,dm.obs_len:], gen_data)" ] } ], "metadata": { "kernelspec": { "display_name": "gents", "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": "3.10.19" } }, "nbformat": 4, "nbformat_minor": 5 }