Accelerate Deep Learning with Intel® Extension for PyTorch*
See how to use Intel® Extension for PyTorch* for training and inference on the MedMNIST datasets. These datasets are a collection of 10 MNIST-like open datasets on various medical-imaging classification tasks, such as pathology, chest X-ray, and optical coherence tomography (OCT) images. The demonstration runs on Intel® Tiber™ Developer Cloud. It is compared against stock PyTorch and shows the performance gain that Intel Extension for PyTorch offers.
Séverine Habert is a deep learning software engineer at Intel who helps data scientists use AI Tools. She holds a PhD in medical imaging from Technical University of Munich.
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产品和性能信息
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性能因用途、配置和其他因素而异。请访问 www.Intel.cn/PerformanceIndex 了解更多信息。