🐛 Describe the bug We are tying to use TorchFunctionMode to convert the input tensors of SDPA to DTensor (if they are not). Unfortunately this approach fails. Digging into the detail, this seems to be a fundamental limitation of checkpoi...
A high-throughput and memory-efficient inference and serving engine for LLMs. Extended for Rubra function calling models - [Core][Optimization] change python dict to pytorch tensor (#4607) · rubra-ai/vllm@63575bc
It is important to also include field programmable gate arrays (FPGAs) and application-specific integrated circuits (ASICs) like tensor processing units (TPUs) to this framework. The 28 TFLOPS is assumed here based of NVIDIA’s advertisement of the V100 performance as well as on Microsoft’s ...
We trained ResNet-34 on the ImageNet59dataset. The ImageNet dataset has 1.3 M images in the training set and 50 k images in the test set. Images in the ImageNet dataset are preprocessed by following the same preprocessing steps as that of the Pytorch baseline model. Training images...
the feature map is compressed into two tensors of sizeC×1×1. Then, the two vectors are input into the MLP (Multi-Layer Perceptron) respectively, and the output of the MLP is merged by element-by-element summation. Finally, the channel attention weight graphWd(d=1,…,D)(whereDrepresen...
guopengf commented Sep 23, 2024 • edited by pytorch-bot bot 🐛 Describe the bug The following code defines a 3d convolution layer and we run inference under AMP. For the input tensor with the shape of [1, 128, 248, 248, 248], the peak memory usage from the nvidia-smi command...
Tensors and Dynamic neural networks in Python with strong GPU acceleration - Checkpoint doesn't work with torch_function if torch_function change tensor metadata · pytorch/pytorch@eb08ada
Instead of returning None for unused variables, a tensor with all-zeros is returned. Fixes [141301](#141301) Pull Request resolved: #142518 Approved by: https://github.com/ydwu4main ciflow/xpu/143663 … ciflow/binaries_wheel/143663 bohnstingl authored and pytorchmergebot committed Dec 19...
The original issue came from a misunderstanding of pipeline-parallel vs tensor-parallel. When using pipeline-parallelism, adding additional bandwidth would have no effect. The solution was to use tensor-parallel instead, which significantly increased throughput with additional bandwidth....
🐛 Describe the bug When you create a MaskedTensor and change it to cuda, the data is the only one that change to cuda. When we use a reduction function on cuda MaskedTensor (sum, to_tensor, etc), it will always fail since the mask in on ...