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Applying black to previous changes. Adding a simplicial dataloader an…
…d some transforms that add data to the simplicial complexes such as neighborhood matrices. Experiments with simplicial complex neural networks started in experiment_scconv.ipynb, but still not available.
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|---|---|---|
| @@ -0,0 +1,204 @@ | ||
| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "code", | ||
| "outputs": [], | ||
| "source": [ | ||
| "%load_ext autoreload\n", | ||
| "%autoreload 2" | ||
| ], | ||
| "metadata": { | ||
| "collapsed": false, | ||
| "ExecuteTime": { | ||
| "end_time": "2024-04-26T15:57:14.612479Z", | ||
| "start_time": "2024-04-26T15:57:14.576630Z" | ||
| } | ||
| }, | ||
| "id": "e1447e3b250fa124", | ||
| "execution_count": 1 | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "outputs": [ | ||
| { | ||
| "ename": "ModuleNotFoundError", | ||
| "evalue": "No module named 'topomodelx'", | ||
| "output_type": "error", | ||
| "traceback": [ | ||
| "\u001B[1;31m---------------------------------------------------------------------------\u001B[0m", | ||
| "\u001B[1;31mModuleNotFoundError\u001B[0m Traceback (most recent call last)", | ||
| "Cell \u001B[1;32mIn[35], line 7\u001B[0m\n\u001B[0;32m 5\u001B[0m \u001B[38;5;28;01mfrom\u001B[39;00m \u001B[38;5;21;01mmantra\u001B[39;00m\u001B[38;5;21;01m.\u001B[39;00m\u001B[38;5;21;01mtransforms\u001B[39;00m \u001B[38;5;28;01mimport\u001B[39;00m OrientableToClassTransform, SimplicialComplexTransform\n\u001B[0;32m 6\u001B[0m \u001B[38;5;28;01mfrom\u001B[39;00m \u001B[38;5;21;01mmantra\u001B[39;00m\u001B[38;5;21;01m.\u001B[39;00m\u001B[38;5;21;01mdataloaders\u001B[39;00m \u001B[38;5;28;01mimport\u001B[39;00m SimplicialDataLoader\n\u001B[1;32m----> 7\u001B[0m \u001B[38;5;28;01mfrom\u001B[39;00m \u001B[38;5;21;01mtopomodelx\u001B[39;00m\u001B[38;5;21;01m.\u001B[39;00m\u001B[38;5;21;01mutils\u001B[39;00m\u001B[38;5;21;01m.\u001B[39;00m\u001B[38;5;21;01msparse\u001B[39;00m \u001B[38;5;28;01mimport\u001B[39;00m from_sparse\n", | ||
| "\u001B[1;31mModuleNotFoundError\u001B[0m: No module named 'topomodelx'" | ||
| ] | ||
| } | ||
| ], | ||
| "source": [ | ||
| "from mantra.simplicial import SimplicialDataset\n", | ||
| "import torch\n", | ||
| "import numpy as np\n", | ||
| "import torchvision.transforms as transforms\n", | ||
| "from mantra.transforms import OrientableToClassTransform, SimplicialComplexTransform\n", | ||
| "from mantra.dataloaders import SimplicialDataLoader\n", | ||
| "from topomodelx.utils.sparse import from_sparse" | ||
| ], | ||
| "metadata": { | ||
| "collapsed": true, | ||
| "ExecuteTime": { | ||
| "end_time": "2024-04-26T16:17:56.006222Z", | ||
| "start_time": "2024-04-26T16:17:55.890296Z" | ||
| } | ||
| }, | ||
| "id": "initial_id", | ||
| "execution_count": 35 | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "outputs": [], | ||
| "source": [ | ||
| "from mantra.transforms import SimplicialComplexDegreeTransform, SimplicialComplexEdgeCoadjacencyDegreeTransform, \\\n", | ||
| " SimplicialComplexEdgeAdjacencyDegreeTransform, SimplicialComplexTriangleCoadjacencyDegreeTransform, \\\n", | ||
| " OrientableToClassSimplicialComplexTransform, DimTwoHodgeLaplacianSimplicialComplexTransform, \\\n", | ||
| " DimOneHodgeLaplacianDownSimplicialComplexTransform, DimOneHodgeLaplacianUpSimplicialComplexTransform, \\\n", | ||
| " DimZeroHodgeLaplacianSimplicialComplexTransform\n", | ||
| "\n", | ||
| "tr = transforms.Compose(\n", | ||
| " [SimplicialComplexTransform(), \n", | ||
| " SimplicialComplexDegreeTransform(),\n", | ||
| " SimplicialComplexEdgeCoadjacencyDegreeTransform(),\n", | ||
| " SimplicialComplexEdgeAdjacencyDegreeTransform(),\n", | ||
| " SimplicialComplexTriangleCoadjacencyDegreeTransform(),\n", | ||
| " DimZeroHodgeLaplacianSimplicialComplexTransform(),\n", | ||
| " DimOneHodgeLaplacianUpSimplicialComplexTransform(),\n", | ||
| " DimOneHodgeLaplacianDownSimplicialComplexTransform(),\n", | ||
| " DimTwoHodgeLaplacianSimplicialComplexTransform(),\n", | ||
| " OrientableToClassSimplicialComplexTransform()]\n", | ||
| " )" | ||
| ], | ||
| "metadata": { | ||
| "collapsed": false, | ||
| "ExecuteTime": { | ||
| "end_time": "2024-04-26T16:16:25.339696Z", | ||
| "start_time": "2024-04-26T16:16:25.243304Z" | ||
| } | ||
| }, | ||
| "id": "258c13ed23fc24a9", | ||
| "execution_count": 32 | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "outputs": [], | ||
| "source": [ | ||
| "dataset = SimplicialDataset(root=\"./data\", transform=tr)\n", | ||
| "dloader = SimplicialDataLoader(dataset, batch_size=3, shuffle=False)" | ||
| ], | ||
| "metadata": { | ||
| "collapsed": false, | ||
| "ExecuteTime": { | ||
| "end_time": "2024-04-26T16:16:25.802979Z", | ||
| "start_time": "2024-04-26T16:16:25.696147Z" | ||
| } | ||
| }, | ||
| "id": "b7a030f18bfe7035", | ||
| "execution_count": 33 | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "outputs": [ | ||
| { | ||
| "name": "stdout", | ||
| "output_type": "stream", | ||
| "text": [ | ||
| "[tensor([[3.],\n", | ||
| " [3.],\n", | ||
| " [3.],\n", | ||
| " [3.]]), tensor([[4.],\n", | ||
| " [3.],\n", | ||
| " [4.],\n", | ||
| " [4.],\n", | ||
| " [3.]]), tensor([[5.],\n", | ||
| " [3.],\n", | ||
| " [4.],\n", | ||
| " [5.],\n", | ||
| " [4.],\n", | ||
| " [3.]])]\n", | ||
| "[tensor([[4., 4.],\n", | ||
| " [4., 4.],\n", | ||
| " [4., 4.],\n", | ||
| " [4., 4.],\n", | ||
| " [4., 4.],\n", | ||
| " [4., 4.]]), tensor([[5., 4.],\n", | ||
| " [6., 4.],\n", | ||
| " [6., 4.],\n", | ||
| " [5., 4.],\n", | ||
| " [5., 4.],\n", | ||
| " [5., 4.],\n", | ||
| " [6., 4.],\n", | ||
| " [5., 4.],\n", | ||
| " [5., 4.]]), tensor([[6., 4.],\n", | ||
| " [7., 4.],\n", | ||
| " [8., 4.],\n", | ||
| " [7., 4.],\n", | ||
| " [6., 4.],\n", | ||
| " [5., 4.],\n", | ||
| " [6., 4.],\n", | ||
| " [7., 4.],\n", | ||
| " [6., 4.],\n", | ||
| " [7., 4.],\n", | ||
| " [6., 4.],\n", | ||
| " [5., 4.]])]\n", | ||
| "[tensor([[3.],\n", | ||
| " [3.],\n", | ||
| " [3.],\n", | ||
| " [3.]]), tensor([[3.],\n", | ||
| " [3.],\n", | ||
| " [3.],\n", | ||
| " [3.],\n", | ||
| " [3.],\n", | ||
| " [3.]]), tensor([[3.],\n", | ||
| " [3.],\n", | ||
| " [3.],\n", | ||
| " [3.],\n", | ||
| " [3.],\n", | ||
| " [3.],\n", | ||
| " [3.],\n", | ||
| " [3.]])]\n" | ||
| ] | ||
| } | ||
| ], | ||
| "source": [ | ||
| "# Take the first batch\n", | ||
| "batch, signals_belonging, len_batch = next(iter(dloader))" | ||
| ], | ||
| "metadata": { | ||
| "collapsed": false, | ||
| "ExecuteTime": { | ||
| "end_time": "2024-04-26T16:16:32.741466Z", | ||
| "start_time": "2024-04-26T16:16:32.618291Z" | ||
| } | ||
| }, | ||
| "id": "3220794957955b0f", | ||
| "execution_count": 34 | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": "Python 3", | ||
| "language": "python", | ||
| "name": "python3" | ||
| }, | ||
| "language_info": { | ||
| "codemirror_mode": { | ||
| "name": "ipython", | ||
| "version": 2 | ||
| }, | ||
| "file_extension": ".py", | ||
| "mimetype": "text/x-python", | ||
| "name": "python", | ||
| "nbconvert_exporter": "python", | ||
| "pygments_lexer": "ipython2", | ||
| "version": "2.7.6" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 5 | ||
| } |
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