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https://github.com/owkin/GrAIdient/actions/workflows/unit-tests.yml)
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GrAIdient is a framework that allows deep learning models to be developed using the internal GPU of a Mac, unlocking researchers to more easily train and run AI models on their own computers.
GrAIdient exposes the graph of layers, providing a unique way to design deep learning models for greater understanding, control and reproducibility.
Though deeply grounded to the data driven pipeline, the goal is to challenge the very understanding of deep learning models and inject human intelligence where relevant; to transition from black box models to white box models, and all the gradients in between.
Check out this toy VGG example and its documentation to get started with GrAIdient today!
Add the following dependency to your Package.swift
manifest:
.package(url: "https://github.com/owkin/GrAIdient.git", .branch("main")),
The documentation is divided into several sections:
Read below to learn how to take part in improving GrAIdient.
All notable changes to GrAIdient will be documented in the changelog.
Read our contributing guide to learn about our development process and how to build and test your changes to GrAIdient.
GrAIdient has adopted a Code of Conduct that we expect project participants to adhere to. Please read the full text so that you can understand what actions will and will not be tolerated.
GrAIdient, GrAITestsUtils and GrAITests are MIT licenced.
GrAIExamples and GrAITorchTests both depend on PythonKit and are Apache 2.0 licensed.
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Stars: 56 |
Last commit: 8 hours ago |
🪜 layer_1d: Softmax1D, DotProduct1D & Constant1D (#49)
🪜 feat: remove activation from layer (#47)
🪜 feat: LayerMerge1D, Sum1D, Concat1D, Concat2D (#43)
🪜 layer_2d: Deconvolution2D (#42)
🪜 feat: getDeltaWeightsGPU per sample API (#41)
🐛 fix: use buffers for neuron selection in SelectNeurons1D (#50)
🐛 fix: model context max id (#45)
🐛 fix: remove error when data input may indicate lower batch size (#44)
📚 docs: change project description and add links (#57)
📚 docs: PropertyListEncoder by default (#51)
🎉 refactor: logo (#46)
🎉 refactor!: re brand the framework (#40)
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