SPEED The official PyTorch implementation of our NeurIPS 2023 paper: Sparse Parameterization for Epitomic Dataset Distillation Xing Wei, Anjia Cao, Funing Yang, and Zhiheng Ma. GitHub maintainer: Anjia Cao Highlight 🔖Brief Introduction The success of deep learning relies heavily on large and diverse...
PyTorch DataLoader num_workers Test - Speed Things Up Welcome to this neural network programming series. In this episode, we will see how we can speed up the neural network training process by utilizing the multiple process capabilities of the PyTorch DataLoader class. Without further ado, let...
Assign User on Comment Significantly speed up save_cache_artifacts #155178 Sign in to view logs Summary Jobs assign Run details Usage Workflow file Triggered via issue March 3, 2025 17:22 pytorchmergebot commented on #148227 3ca1a25 Status Success Total duration 23s Artifacts – assigntome-...
Anindya Dey, PhD August 6, 2024 28 min read This is a bit different from what the books say. Peng Qian August 17, 2024 9 min read Latest picks: Time Series Forecasting with Deep Learning and Attention Mechanism Data Science Your daily dose of data science ...
GPU speed and memory difference between einsum and matmul - PyTorch Forums 这篇帖子讨论了在 PyTorch 中使用 einsum 和 matmul 两个操作的性能差异,特别是在 GPU(NVIDIA A6000)上运行时的速度和内存使用情况。以下是关键点的总结: 代码设置 • 创建了两个张量(tensor1 和 tensor2),具有特定的维度。
【 请问神龙AI AGspeed支持pytorch 2.0吗？】支持的，目前整合为AIACC2.0的大包了，后面文档会更新...
即:run.num_workers。 ,此外, ,因此,主进程不需要从磁盘读取数据;相反,这些数据已经在内存中准备好了。 这个例子中,我们看到了20%的加速效果,那么你可能会想, 我们考虑一个工人可能足够让队列中充满了主进程的数据,然后将更多的数据添加到队列中,不会在速度上做任何事情。我们在这里看到的就是这些, ...
Deepytorch Training支持多种PyTorch、CUDA以及Python版本。版本对应关系如下所示: PyTorch Version CUDA Runtime Version Python Version 1.10.x 11.1/11.3 3.8/3.9 1.11.x 11.3 3.8/3.9/3.10 1.12.x 11.3/11.6 3.8/3.9/3.10 1.13.x 11.6/11.7 3.8/3.9/3.10 2.0.x 11.7/11.8 3.8/3.9/3.10/3.11 2.1.x 11.8...
Tensors and Dynamic neural networks in Python with strong GPU acceleration - Significantly speed up save_cache_artifacts (#148227) · pytorch/pytorch@57addfc
🐛 Bug When I update the pytorch to 1.7, the cudatoolkit is updated automaticlly to 11.0, and I find the speed of the same code is slower too much than before. So I change the version of the cudatoolkit back to 10.2, the speed is normal. ...