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* Initial commit that uncovered the issue. * Small update to the notebook.
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{ | ||
"cells": [ | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"import fibad" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"# Create an instance of a fibad object, instantiated (implicitly) with the default configuration file\n", | ||
"fibad_instance = fibad.Fibad()" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"# Update a few of the configuration parameters\n", | ||
"fibad_instance.config[\"model\"][\"name\"] = \"ExampleCNN\"\n", | ||
"fibad_instance.config[\"data_set\"][\"name\"] = \"CifarDataSet\"\n", | ||
"fibad_instance.config[\"data_loader\"][\"batch_size\"] = 64" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"# Begin training the Example CNN model using the CIFAR-10 dataset\n", | ||
"fibad_instance.train()" | ||
] | ||
} | ||
], | ||
"metadata": { | ||
"kernelspec": { | ||
"display_name": "fibad", | ||
"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": "3.11.9" | ||
} | ||
}, | ||
"nbformat": 4, | ||
"nbformat_minor": 2 | ||
} |
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