neural-netz:0.1.0

packages/preview/neural-netz/0.1.0/LICENSE

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+MIT No Attribution
+
+Permission is hereby granted, free of charge, to any person obtaining a copy of this
+software and associated documentation files (the "Software"), to deal in the Software
+without restriction, including without limitation the rights to use, copy, modify,
+merge, publish, distribute, sublicense, and/or sell copies of the Software, and to
+permit persons to whom the Software is furnished to do so.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED,
+INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A
+PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
+OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
+SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

packages/preview/neural-netz/0.1.0/README.md

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+# neural-netz
+Visualize Neural Network Architectures in high-quality diagrams using [Typst](https://typst.app), with style and API inspired by [PlotNeuralNet](https://github.com/HarisIqbal88/PlotNeuralNet).
+
+<p align="center">
+<img src="gallery/features/FCN-8(cold).png" alt="Example of Neural Net visualizaiton with cold color palette" width="750px"/>
+<img src="gallery/networks/FCN-8.png" alt="Example of Neural Net visualizaiton with warm color palette" width="750px"/>
+</p>
+
+Under the hood, this package only uses the native Typst package [CeTZ](https://typst.app/universe/package/cetz/) for building the diagrams.
+
+# Usage
+
+Simply import the package in order to call its drawing function:
+```typ
+#import "@preview/neural-netz:0.1.0"
+```
+You can then call `draw-network` which has the following arguments:
+```typ
+draw-network(
+  layers,
+  connections: (),
+  palette: "warm",
+  show-legend: false,
+  scale: 100%,
+  stroke-thickness: 1,
+  depth-multiplier: 0.3,
+  show-relu: false,
+)
+```
+See the examples in the following section to understand how to use it. Alternatively, you can also start from already written architecture examples (see the Examples section).
+
+# Getting started
+
+Here are a few simple features for getting started.
+
+### Basic layout
+
+```typ
+#draw-network((
+    (type: "input", image-file: "default"), // You can also specify a custom image path
+    (type: "conv", offset: 2), // Next layers are automatically connected with arrows
+    (type: "conv", offset: 2),
+    (type: "pool"), // Pool layers are sticked to previous convolution block
+    (type: "conv", widths: (1, 1), offset: 3) // you can offset layers
+))
+```
+<p align="center">
+<img src="gallery/features/basic-layout.png" alt="Basic layout example" width="350px"/>
+</p>
+
+### Dimensions and labels
+
+```typ
+#draw-network((
+    (
+      type: "convres", // Each layer type has its own color
+      widths: (1, 2),
+      channels: (32, 64, 128), // An extra channel will be used as diagonal axis label
+      height: 6,
+      depth: 8,
+      label: "residual convolution",
+    ),
+    (
+      type: "pool",
+      channels: ("", "text also works"),
+      height: 4,
+      depth: 6,
+    ),
+    (
+      type: "conv",
+      widths: (1.5, 1.5),
+      height: 2,
+      depth: 3,
+      label: "whole block label",
+      offset: 3,
+    )
+))
+```
+<p align="center">
+<img src="gallery/features/dimensions-labels.png" alt="Dimensions and labels example" width="350"/>
+</p>
+
+Additionally, if you network does not fit the page width of your Typst document, you can reduce the scale by giving `scale: 50%` as argument of `draw-network`
+
+
+### Adding other connexions
+
+```typ
+#draw-network((
+  (type: "conv", label: "A", name: "a"),
+  (type: "conv", label: "B", name: "b", offset: 2),
+  (type: "conv", label: "C", name: "c", offset: 2),
+  (type: "conv", label: "D", name: "d", offset: 2),
+  (type: "conv", label: "E", name: "e", offset: 2),
+), connections: (
+  (from: "a", to: "c", type: "skip", mode: "depth", label: "depth mode", pos: 6),
+  (from: "b", to: "d", type: "skip", mode: "flat", label: "flat mode", pos: 5),
+  (from: "c", to: "e", type: "skip", mode: "air", label: "air mode (+touch layer instead of arrow)", pos: 5, touch-layer: true),
+),
+palette: "cold", // There is a "warm" and a "cold" color palette.
+show-relu: true // visualize relu using darker color on convolution layers
+)
+```
+<p align="center">
+<img src="gallery/features/connexions.png" alt="Adding connexions example" width="350"/>
+</p>
+
+# Examples
+Here are a few network architectures implemented with neural-netz (more examples can be found [in the repo](https://github.com/edgaremy/neural-netz/tree/5c434055a5bcf83eee75ab88ad5a7ac77c430feb/examples/networks)).
+
+<h3 style="text-align: center;">ResNet18</h3>
+<p align="center">
+<img src="gallery/networks/ResNet18.png" alt="ResNet18 visualization" width="500"/>
+</p>
+<p style="text-align: center;"><a href="https://github.com/edgaremy/neural-netz/blob/5c434055a5bcf83eee75ab88ad5a7ac77c430feb/examples/networks/ResNet18.typ">code for this image</a></p>
+
+<h3 style="text-align: center;">U-Net</h3>
+<p align="center">
+<img src="gallery/networks/U-Net.png" alt="U-Net visualization" width="500"/>
+</p>
+<p style="text-align: center;"><a href="https://github.com/edgaremy/neural-netz/blob/5c434055a5bcf83eee75ab88ad5a7ac77c430feb/examples/networks/U-Net.typ">code for this image</a></p>
+
+<h3 style="text-align: center;">FCN-8</h3>
+<p align="center">
+<img src="gallery/networks/FCN-8.png" alt="FCN-8 visualization" width="500"/>
+</p>
+<p style="text-align: center;"><a href="https://github.com/edgaremy/neural-netz/blob/5c434055a5bcf83eee75ab88ad5a7ac77c430feb/examples/networks/FCN-8.typ">code for this image</a></p>
+
+
+# Acknowledgements
+
+This package could not have existed without the great Python+LaTeX visualization package [PlotNeuralNet](https://github.com/HarisIqbal88/PlotNeuralNet) made by Haris Iqbal. It proposes an elegant way for viewing neural networks, and its visual style was obviously a strong inspiration for the implementation of neural-netz.
+
+Default input image was [taken from iNaturalist](https://www.inaturalist.org/observations/205901632) (colors are slightly edited).
+
+If you feel like contributing to this package (bug fixes, features, code refactoring), feel free to [make a PR to the neural-netz repo](https://github.com/edgaremy/neural-netz/pulls) :)