Directories
¶
| Path | Synopsis |
|---|---|
|
Package adult provides a `InMemoryDataset` implementation for UCI Adult Census dataset.
|
Package adult provides a `InMemoryDataset` implementation for UCI Adult Census dataset. |
|
demo
Linear generates random synthetic data, based on some linear mode + noise.
|
Linear generates random synthetic data, based on some linear mode + noise. |
|
Package cifar provides a library of tools to download and manipulate Cifar-10 dataset.
|
Package cifar provides a library of tools to download and manipulate Cifar-10 dataset. |
|
demo
Demo for cifar library: it implements 2 models, a FNN and a CNN.
|
Demo for cifar library: it implements 2 models, a FNN and a CNN. |
|
demo
demo for Dogs vs Cats library: you can run this program in 3 different ways:
|
demo for Dogs vs Cats library: you can run this program in 3 different ways: |
|
Package imdb contains code to download and prepare datasets with IMDB Dataset of 50k Movie Reviews.
|
Package imdb contains code to download and prepare datasets with IMDB Dataset of 50k Movie Reviews. |
|
demo
IMDB Movie Review library (imdb) demo: you can run this program in 4 different ways:
|
IMDB Movie Review library (imdb) demo: you can run this program in 4 different ways: |
|
Linear generates random synthetic data, based on some linear mode + noise.
|
Linear generates random synthetic data, based on some linear mode + noise. |
|
Package notebook allows one to check if running within a notebook.
|
Package notebook allows one to check if running within a notebook. |
|
bashkernel
Package bashkernel implements tools to output rich content to a Jupyter notebook running the bash_kernel (https://github.com/takluyver/bash_kernel).
|
Package bashkernel implements tools to output rich content to a Jupyter notebook running the bash_kernel (https://github.com/takluyver/bash_kernel). |
|
gonb/margaid
Package margaid implements automatic plotting of all metrics registered in a trainer, using the Margaid library (https://github.com/erkkah/margaid/) to draw SVG, and GoNB (https://github.com/janpfeifer/gonb/) to display it in a Jupyter Notebook.
|
Package margaid implements automatic plotting of all metrics registered in a trainer, using the Margaid library (https://github.com/erkkah/margaid/) to draw SVG, and GoNB (https://github.com/janpfeifer/gonb/) to display it in a Jupyter Notebook. |
|
gonb/plotly
Package plotly uses GoNB plotly support (`github.com/janpfeifer/gonb/gonbui/plotly`) to plot both on dynamic plots while training or to quickly plot the results of a previously saved plot results in a checkpoints directory.
|
Package plotly uses GoNB plotly support (`github.com/janpfeifer/gonb/gonbui/plotly`) to plot both on dynamic plots while training or to quickly plot the results of a previously saved plot results in a checkpoints directory. |
|
gonb/plots
Package plots define common types and utilities to the different plot libraries.
|
Package plots define common types and utilities to the different plot libraries. |
|
Package ogbnmag provides `Download` method for the corresponding dataset, and some dataset tools
|
Package ogbnmag provides `Download` method for the corresponding dataset, and some dataset tools |
|
fnn
Package fnn implements a feed-forward neural network for the OGBN-MAG problem.
|
Package fnn implements a feed-forward neural network for the OGBN-MAG problem. |
|
gnn
Package gnn implements a generic GNN modeling based on [TF-GNN MtAlbis].
|
Package gnn implements a generic GNN modeling based on [TF-GNN MtAlbis]. |
|
Package oxfordflowers102 provides tools to download and cache the dataset and a `train.Dataset` implementation that can be used to train models using GoMLX (http://github.com/gomlx/gomlx/).
|
Package oxfordflowers102 provides tools to download and cache the dataset and a `train.Dataset` implementation that can be used to train models using GoMLX (http://github.com/gomlx/gomlx/). |
|
diffusion
Package diffusion contains an example diffusion model, trained on Oxford Flowers 102 dataset.
|
Package diffusion contains an example diffusion model, trained on Oxford Flowers 102 dataset. |
Click to show internal directories.
Click to hide internal directories.