mlp_random_tensorflow2

Multi-Layer TensorFlow2 Model

Overview

The example presents a simple Multi-Layer model implemented in TensorFlow2

Example consists of following scripts:

• server.py - start the model with Triton Inference Server
• client.py - execute HTTP/gRPC requests to the deployed model

Requirements

The example requires the tensorflow package. It can be installed in your current environment using pip:

pip install tensorflow

Or you can use NVIDIA TensorFlow container:

docker run -it --gpus 1 --shm-size 8gb -v {repository_path}:{repository_path} -w {repository_path} nvcr.io/nvidia/tensorflow:24.03-tf2-py3 bash

If you select to use container we recommend to install NVIDIA Container Toolkit.

Quick Start

The step-by-step guide:

1. Install PyTriton following the installation instruction
2. Install the additional packages using install.sh

./install.sh

3. In current terminal start the model on Triton using server.py

./server.py

4. Open new terminal tab (ex. Ctrl + T on Ubuntu) or window
5. Go to the example directory
6. Run the client.py to perform queries on model:

./client.py