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Real Time Inference on Raspberry Pi 4 (30 fps!)#Created On: Feb 08, 2022 | Last Updated: Jan 16, 2024 | Last Verified: Nov 05, 2024 Author: Tristan Rice PyTorch has out of the box support for Raspberry Pi 4. This tutorial will guide you on how to setup a Raspberry Pi 4 for running PyTorch and run a MobileNet v2 classification model in real time (30 fps+) on the CPU. This was all tested with Raspbe
PyTorch Profiler With TensorBoard#Created On: Apr 20, 2021 | Last Updated: Oct 31, 2024 | Last Verified: Nov 05, 2024 This tutorial demonstrates how to use TensorBoard plugin with PyTorch Profiler to detect performance bottlenecks of the model. Warning The TensorBoard integration with the PyTorch profiler is now deprecated. Instead, use Perfetto or the Chrome trace to view trace.json files. After
Finetuning Torchvision Models#Created On: Jun 01, 2023 | Last Updated: Jun 01, 2023 | Last Verified: Nov 05, 2024 This tutorial has been moved to https://pytorch.org/tutorials/intermediate/torchvision_tutorial.html It will redirect in 3 seconds.
Reproducibility# Created On: Sep 11, 2018 | Last Updated On: Nov 26, 2024 Completely reproducible results are not guaranteed across PyTorch releases, individual commits, or different platforms. Furthermore, results may not be reproducible between CPU and GPU executions, even when using identical seeds. However, there are some steps you can take to limit the number of sources of nondeterministic be
Deep Learning for NLP with Pytorch¶ Author: Robert Guthrie This tutorial will walk you through the key ideas of deep learning programming using Pytorch. Many of the concepts (such as the computation graph abstraction and autograd) are not unique to Pytorch and are relevant to any deep learning toolkit out there. I am writing this tutorial to focus specifically on NLP for people who have never writ
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