EfficientNets are a family of image classification models, which achieve state-of-the-art accuracy, being an order-of-magnitude smaller and faster.
The following section lists the requirements that you need to meet in order to start training the EfficientNet model.
Requirements
This repository contains Dockerfile which extends the TensorFlow NGC container and encapsulates some dependencies. Aside from these dependencies, ensure you have the following components:
- NVIDIA Docker
- [TensorFlow 21.09-py3] NGC container or later
- Supported GPUs:
For more information about how to get started with NGC containers, refer to the following sections from the NVIDIA GPU Cloud Documentation and the Deep Learning Documentation:
- Getting Started Using NVIDIA GPU Cloud
- Accessing And Pulling From The NGC Container Registry
- Running TensorFlow
As an alternative to the use of the Tensorflow2 NGC container, to set up the required environment or create your own container, refer to the versioned NVIDIA Container Support Matrix.
For multi-node, the sample provided in this repository requires Enroot and Pyxis set up on a SLURM cluster.