Inference with Torch-TensorRT Deep Learning Prediction for Beginners - CPU vs CUDA vs TensorRT
This course provides an introduction to Torch-TensorRT deep learning prediction for beginners. It covers the steps to clone Torch-TensorRT, install and setup Docker, install Nvidia Container Toolkit and Nvidia Docker 2, and two container options for Torch-TensorRT. Participants will learn how to import Pytorch, load a model, and run inference on CPU, CUDA, and TensorRT. This course is ideal for those looking to get started with deep learning prediction. ▼
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Course Feature
Cost:
Free
Provider:
Youtube
Certificate:
Paid Certification
Language:
English
Start Date:
On-Demand
Course Overview
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Updated in [February 21st, 2023]
This course provides a comprehensive introduction to using Torch-TensorRT on Nvidia GPUs. It covers everything from setting up a Docker container, installing Nvidia Container Toolkit and Nvidia Docker 2, loading ResNet50 and a sample image in Pytorch, training with ResNet50, using the softmax function, and mapping ImageNet class number to names, to benchmarking functions, running CPU and CUDA benchmarks, tracing models, converting traced models to Torch-TensorRT models, and running TensorRT benchmarks.
Possible Development Paths: Learners of this course can use their newfound knowledge to develop applications that use Torch-TensorRT on Nvidia GPUs. They can also use their knowledge to develop applications that use other deep learning frameworks such as TensorFlow, Caffe, and Theano. Additionally, learners can use their knowledge to develop applications that use other GPU-accelerated libraries such as cuDNN and cuBLAS.
Learning Suggestions: Learners of this course should consider taking courses on other deep learning frameworks such as TensorFlow, Caffe, and Theano. Additionally, learners should consider taking courses on other GPU-accelerated libraries such as cuDNN and cuBLAS. Learners should also consider taking courses on computer vision, natural language processing, and machine learning. Finally, learners should consider taking courses on software engineering and data science.
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