Subscrib

Log In

Cannot train Tao Toolkit UNet model in version v4.0.0 and v4.0.1

Cannot train Tao Toolkit UNet model in version v4.0.0 and v4.0.1

Excuse me @Bin_Zhao_NV @Morganh I’ve changed gpus from Tesla P100 to Tesla V100 and tried to train Tao Toolkit UNet model with 4 gpus in version v4.0.0 and v4.0.1 again. However. I still got the error message: device CUDA:0 not supported by XLA service while setting up XLA_GPU_JIT device number 0. This is the result in the process of training UNet when I ran the command nvidia-smi. Is this a bug for Tao Toolkit v4.0.0 and v4.0.1 ? When I trained UNet in the version v3.22.05, it seemed tha

Access the Entire Tutorial Library

Train smarter with NVIDIA pre-trained models and TAO Transfer Learning Toolkit on Microsoft Azure - Microsoft Community Hub

Digital Twin and Artificial Intelligence-Empowered Panoramic Video Streaming

SFM Series Drawing, Double Row by Samtec Inc. Datasheet

Performance comparison between IML-TYLCVs and the top 5 baseline models

Foam FLOW-3D

Molecular Catalysts for N2 Reduction: State of the Art, Mechanism, and Challenges - Roux - 2017 - ChemPhysChem - Wiley Online Library

Remote Sensing, Free Full-Text

Imaging With Equivariant Deep Learning

S32K344 Evaluation Board for Mobile Robotics with 100BASE-T1 and Six CANFD

Roelens Vacation Rentals: Salty Shoreline, Cape Coral in Florida – Roelens Vacation Rentals

Land, Free Full-Text

Training the RetinaNet or ResNet18 model with TAO Toolkit and deploying it with DeepStream and Triton, Developing and Deploying Vision AI with Dell and NVIDIA Metropolis

The training process of Tao-Toolkit-API unet is always in Inf status - TAO Toolkit - NVIDIA Developer Forums