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CarloLucibello authored Jan 3, 2025
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Expand Up @@ -31,9 +31,9 @@ pkg> add Tsunami

## Usage

Define your model subtyping the `FluxModule` abstract type, implement a few required methods, then let the `Trainer` train the model on your dataset with `Tsunami.fit!`. Tsunami will handle all of the boilerplate (training loop, loggin, gpu movement, validation, ...).
Define your model by subtyping the `FluxModule` abstract type, implement a few required methods, then let the `Trainer` train the model on your dataset with `Tsunami.fit!`. Tsunami will handle the boilerplate (training loop, logging, gpu movement, validation, ...).

In the following script we train a Multilayer Perceptron on the FashionMNIST dataset using Tsunami:
In the following script, we train a Multilayer Perceptron on the FashionMNIST dataset using Tsunami:
```julia
using Flux, Optimisers, Statistics, Tsunami, MLDatasets
using CUDA # or AMDGPU, Metal, ... for GPU support
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Release notes:

Breaking changes:

  • Devices indexing now starts from 1, as in MLDataDevices.gpu_device.

Highlights:

  • Updated to Flux v0.16.
  • Models (i.e. subtypes of FluxModule) are now not required to be mutable.
  • Tsunami.fit is deprecated in favor of Tsunami.fit!.
  • Added Trainer option to use Enzyme for automatic differentiation
  • Improved test infrastructure.
  • Improved documentation.

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Registration pull request updated: JuliaRegistries/General/122286

Tagging

After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.

This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:

git tag -a v0.2.0 -m "<description of version>" 14d2785e1dc5538faf74e9603629d7335296ad9c
git push origin v0.2.0

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