我最早接触到tensorflow的时候就感觉：tensor被这帮家伙滥用了。实际上在机器学习里tensor就是n维数组，和...
In [7]: t.storage() Out[7]: 2.0 3.0 4.0 5.0 6.0 7.0 [torch.FloatStorage of size 6] 需要注意的是tensor可以只是part of a storage,比如接下来的例子中t_ 只有3个元素,但它的storage仍然是6个元素 In [4]: t_= t[1] In [5]: t_ Out[5]: tensor([5., 6., 7.]) In [6]: t_....
This post discusses tensor methods, how they are used in NVIDIA, and how they are central to the next generation of AI algorithms. Tensors in modern machine learning Tensors, which generalize matrices to more than two dimensions, are everywhere in modern machine learning. From deep neural netwo...
Tensor2Tensor, orT2Tfor short, is a library of deep learning models and datasets designed to make deep learning more accessible andaccelerate ML research. T2T was developed by researchers and engineers in theGoogle Brain teamand a community of users. It is now deprecated — we keep it running...
Ansor:Generating High-Performance Tensor Program for Deep Learning Abstract 高性能的张量程序对于保证深度神经网络的高效执行十分关键,但是在不同硬件平台上获取高性能的张量程序并不容易。近年的研究中,深度学习系统依赖硬件供应商提供的算子库,或者多种搜索策略来获得高性能的张量程序。这些方法可能需要较多的工程上的...
TensorLy-Torch is a Python library for deep tensor networks that builds on top of TensorLy and PyTorch. It allows to easily leverage tensor methods in a deep learning setting and comes with all batteries included. Website: http://tensorly.org/torch/ Source-code: https://github.com/tensorly/...
generation of Tensor Cores are faster than ever on a broad array of AI and high-performance computing (HPC) tasks. From 4X speedups in training trillion-parameter generative AI models to a 30X increase in inference performance, NVIDIA Tensor Cores accelerate all workloads for modern AI factories...
Deep neural networks (DNNs) have enabled impressive breakthroughs in various artificial intelligence (AI) applications recently due to its capability of learning high-level features from big data. However, the current demand of DNNs for computational resources especially the storage consumption is growing...
Inferencia de Deep Learning A30 presenta innovadoras características para optimizar las cargas de trabajo de inferencia. Acelera los procesos de precisión con diversas opciones, desde FP64 hasta TF32 e INT4. El A30 soporta hasta cuatro MIG por GPU y permite que varias redes funcionen si...
Neural network models have quickly taken advantage of NVIDIA Tensor Cores for deep learning since their introduction in the Tesla V100 GPU last year.