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<p>SINGA is a distributed deep learning library.</p>
<p>This release includes following changes:</p>
<ul>
<li><p>Enhance distributed training</p>
<ul>
<li>Add support for configuration of number of GPUs to be used.</li>
<li>Increase max epoch for better convergence.</li>
<li>Print intermediate mini-batch information.</li>
<li>Add support for switching between CPU and GPU devices.</li>
</ul></li>
<li><p>Enhance example code</p>
<ul>
<li>Update the args of normalize forward function in the transforms of the BloodMnist example.</li>
<li>Update the xceptionnet in the cnn example.</li>
<li>Add arguments for weight decay, momentum and learning rates in the cnn example.</li>
<li>Add training scripts for more datasets and model types in the cnn example.</li>
<li>Add resnet dist version for the large dataset cnn example.</li>
<li>Add cifar 10 multi process for the large dataset cnn example.</li>
<li>Add sparsification implementation for mnist in the large dataset cnn example.</li>
<li>Update the cifar datasets downloading to local directories.</li>
<li>Extend the cifar datasets load function for customized directorires.</li>
</ul></li>
<li><p>Enhance the webpage</p>
<ul>
<li>Update online documentation for distributed training.</li>
</ul></li>
<li><p>Promote code quality</p>
<ul>
<li>Update inline comments for prepreocessing and data loading.</li>
</ul></li>
<li><p>Update the PIL image module</p></li>
<li><p>Update the runtime Dockerfile</p></li>
<li><p>Update the conda files</p></li>
</ul>
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