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<!DOCTYPE HTML>
<html lang="en">
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<title>Torchbearer: Advanced model fitting for PyTorch</title>
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<body>
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<a class="navbar-brand scroll-link" href="#top">
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Torchbearer
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</ol>
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</div>
<div id="about" class="about-container p-sm-5">
<div class="container">
<div class="row">
<div class="col-lg-6 my-2">
<div class="list-group">
<a href="https://github.com/pytorchbearer/torchbearer/releases/tag/0.5.2" class="list-group-item list-group-item-action">
<div class="d-flex w-100 justify-content-between">
<h5 class="mb-1">Version 0.5.2 released!</h5>
<small class="text-muted">28/01/2020</small>
</div>
<p class="mb-1">Now with support for PyTorch 1.4.0! Click for release notes</p>
<!-- <small class="text-muted">Donec id elit non mi porta.</small> -->
</a>
<a href="https://github.com/pytorchbearer/torchbearer/releases/tag/0.5.1" class="list-group-item list-group-item-action">
<div class="d-flex w-100 justify-content-between">
<h5 class="mb-1">Version 0.5.1 released!</h5>
<small class="text-muted">06/11/2019</small>
</div>
<p class="mb-1">Now with support for PyTorch 1.3.0, Manifold MixUp and more! Click for release notes</p>
<!-- <small class="text-muted">Donec id elit non mi porta.</small> -->
</a>
<a href="https://github.com/pytorchbearer/torchbearer/releases/tag/0.5.0" class="list-group-item list-group-item-action">
<div class="d-flex w-100 justify-content-between">
<h5 class="mb-1">Version 0.5.0 released!</h5>
<small class="text-muted">17/09/2019</small>
</div>
<p class="mb-1">Now with support for PyTorch 1.2.0. Click for release notes</p>
<!-- <small class="text-muted">Donec id elit non mi porta.</small> -->
</a>
<a href="https://pytorch.org/ecosystem" class="list-group-item list-group-item-action">
<div class="d-flex w-100 justify-content-between">
<h5 class="mb-1">Now in the PyTorch Ecosystem!</h5>
<small class="text-muted">16/09/2019</small>
</div>
<p class="mb-1">Click to take a look</p>
</a>
<a href="https://github.com/pytorchbearer/torchbearer/releases/tag/0.4.0" class="list-group-item list-group-item-action">
<div class="d-flex w-100 justify-content-between">
<h5 class="mb-1">Version 0.4.0 released!</h5>
<small class="text-muted">5/07/2019</small>
</div>
<p class="mb-1">Click for release notes</p>
<!-- <small class="text-muted">Donec id elit non mi porta.</small> -->
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</div>
</div>
<div class="col-lg-6 my-2">
<p class="lead">
Torchbearer is a <a href="https://pytorch.org">PyTorch</a> model fitting
library aiming to dramatically reduce the amount of boilerplate code you
need to write without limiting the power and accesibility of PyTorch.
Brought to you by the <a href="https://www.vlc.ecs.soton.ac.uk/">Vision,
Learning and Control (VLC) group</a> at the University of Southampton.
</p>
</div>
</div>
<!-- <div class="row"> -->
<!-- <div class="col-lg-4 px-5 hide-lg">
<img src="assets/img/logo_dark.svg" class="w-100 logo">
</div> -->
<!-- <div class="col"> -->
<!-- <h1 class="display-4 mb-5">The Torchbearer Project</h1> -->
<!-- <p class="lead">
Torchbearer is a <a href="https://pytorch.org">PyTorch</a> model fitting
library aiming to dramatically reduce the amount of boilerplate code you
need to write without limiting the power and accesibility of PyTorch.
Brought to you by the <a href="https://www.vlc.ecs.soton.ac.uk/">Vision,
Learning and Control (VLC) group</a> at the University of Southampton.
</p> -->
<!-- </div>
</div> -->
<!-- <div class="alert alert-primary" role="alert">
16 / 09 / 2019: Torchbearer is now part of the <a href="https://pytorch.org/ecosystem">PyTorch ecosystem</a>!
</div>
<div class="alert alert-primary" role="alert">
XX / XX / 2019: <a>Version 0.4.0</a> released!
</div>
<a href="https://torchbearer.readthedocs.io" class="btn btn-primary w-100">Read the docs!</a> -->
</div>
</div>
<div id="install" class="install-container p-sm-5 py-2 pb-5">
<div class="container">
<!-- <div class="row">
<div class="mx-auto mb-5">
<h1 class="display-4">Install</h1>
</div>
</div> -->
<!-- <div class="row">
<div class="col">
<h1 class="display-5">torchbearer</h1>
</div>
</div> -->
<div class="row mx-1">
<div class="col-sm left-col p-2 m-1">
Install
</div>
<div class="col-sm-9">
<div class="row">
<div class="col-sm code copy right-col p-2 m-1" data-toggle="tooltip" data-placement="bottom" title="Click to Copy">
pip install torchbearer
<div class="copy-icon">
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</div>
</div>
</div>
</div>
</div>
<div class="row mx-1">
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Install from source
</div>
<div class="col-sm-9">
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<div class="col-sm code copy right-col p-2 m-1" data-toggle="tooltip" data-placement="bottom" title="Click to Copy">
pip install git+https://github.com/pytorchbearer/torchbearer
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<i class="fas fa-copy fa-fw"></i>
</div>
</div>
</div>
</div>
</div>
<div class="row mx-1">
<div class="col-sm left-col p-2 m-1">
Supported PyTorch versions
</div>
<div class="col-sm-9">
<div class="row">
<div class="col-sm p-2 m-1 text-center">
1.0.0
</div>
<div class="col-sm p-2 m-1 text-center">
1.1.0
</div>
<div class="col-sm p-2 m-1 text-center">
1.2.0
</div>
</div>
</div>
</div>
<div class="row mx-1">
<div class="col-sm left-col p-2 m-1">
Supported Python versions
</div>
<div class="col-sm-9">
<div class="row">
<div class="col-sm p-2 m-1 text-center">
2.7
</div>
<div class="col-sm p-2 m-1 text-center">
3.5
</div>
<div class="col-sm p-2 m-1 text-center">
3.6
</div>
<div class="col-sm p-2 m-1 text-center">
3.7
</div>
</div>
</div>
</div>
</div>
</div>
<div id="links" class="links-container p-sm-5 py-2 pb-5">
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<a href="https://github.com/pytorchbearer/torchbearer">Find us on GitHub</a>
</div>
<div class="col col-lg-4 text-center">
<a href="https://torchbearer.readthedocs.io">Read the docs</a>
</div>
<div class="col col-lg-4 text-center">
<a href="https://twitter.com/EcsVlc">Follow us on Twitter</a>
</div>
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<h5 class="card-title">Read the docs!</h5>
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<h1 class="display-5">visual</h1>
</div>
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PyTorch
</div>
<div class="col-sm-9">
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<div class="col-sm right-col p-2 m-1">
1.1.0
</div>
</div>
</div>
</div>
<div class="row mx-1">
<div class="col-sm left-col p-2 m-1">
Python
</div>
<div class="col-sm-9">
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<div class="col-sm right-col p-2 m-1">
2.7
</div>
<div class="col-sm right-col p-2 m-1">
3.5
</div>
<div class="col-sm right-col p-2 m-1">
3.6
</div>
<div class="col-sm right-col p-2 m-1">
3.7
</div>
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pip install torchbearer-visual
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PyTorch
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1.1.0
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Python
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2.7
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3.5
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3.6
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3.7
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pip install torchbearer-variational
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<p class="card-text">A detailed exploration of callbacks in torchbearer, with some useful visualisations.</p>
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<p class="card-text">A demonstration of the LiveLossPlot callback included in torchbearer.</p>
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<p class="card-text">A guide showing how to perform half and mixed precision training in torchbearer with NVIDIA Apex.</p>
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Deep Learning
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<p class="card-text">Train a linear support vector machine (SVM) using torchbearer, with an interactive visualisation!</p>
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