Compile with Framework API and Deploy on EC2 Inf1

Description

Neuron developer flow on EC2

You can use a single inf1 instance as a development environment to compile and deploy Neuron models. In this developer flow, you provision an EC2 inf1 instance using a Deep Learming AMI (DLAMI) and execute the two steps of the development flow in the same instance. The DLAMI comes pre-packaged with the Neuron frameworks, compiler, and required runtimes to complete the flow. Development happens through Jupyter Notebooks or using a secure shell (ssh) connection in terminal. Follow the steps bellow to setup your environment.

Note

Model compilation can be executed on a non-inf1 instance for later deployment. Follow the same EC2 Developer Flow Setup using other instance families and leverage Amazon Simple Storage Service (S3) to share the compiled models between different instances.

Setup Environment

1. Launch an Inf1 Instance

  • Please follow the instructions at launch an Amazon EC2 Instance to Launch an Inf1 instance, when choosing the instance type at the EC2 console. Please make sure to select the correct instance type. To get more information about Inf1 instances sizes and pricing see Inf1 web page.

  • When choosing an Amazon Machine Image (AMI) make sure to select Deep Learning AMI with Conda Options. Please note that Neuron Conda environments are supported only in Ubuntu 18 DLAMI and Amazon Linux2 DLAMI, Neuron Conda environments are not supported in Amazon Linux DLAMI.

  • After launching the instance, follow the instructions in Connect to your instance to connect to the instance

Note

You can also launch the instance from AWS CLI, please see AWS CLI commands to launch inf1 instances.

2. Set up a development environment

Enable PyTorch-Neuron

Important

For successful installation or update to Neuron 1.16.0 and newer from previous releases:
  • Stop Neuron Runtime 1.x daemon (neuron-rtd) by running: sudo systemctl stop neuron-rtd

  • Uninstall neuron-rtd by running: sudo apt remove aws-neuron-runtime or sudo yum remove aws-neuron-runtime

  • Install or upgrade to latest Neuron driver (aws-neuron-dkms) by following the “Setup Guide” instructions.

  • Visit Introducing Neuron Runtime 2.x (libnrt.so) for more information.

Note

For a successful installation or update, execute each line of the instructions below separately or copy the contents of the code block into a script file and source its contents.

# Note: There is no DLAMI Conda environment for this framework version
#       Framework will be installed/updated inside a Python environment

# Update OS packages
sudo apt-get update -y

###############################################################################################################
# Before installing or updating aws-neuron-dkms:
# - Stop any existing Neuron runtime 1.0 daemon (neuron-rtd) by calling: 'sudo systemctl stop neuron-rtd'
###############################################################################################################

################################################################################################################
# To install or update to Neuron versions 1.16.0 and newer from previous releases:
# - DO NOT skip 'aws-neuron-dkms' install or upgrade step, you MUST install or upgrade to latest Neuron driver
################################################################################################################

# Install OS headers
sudo apt-get install linux-headers-$(uname -r) -y

# Install Neuron Driver
sudo apt-get install aws-neuron-dkms -y

####################################################################################
# Warning: If Linux kernel is updated as a result of OS package update
#          Neuron driver (aws-neuron-dkms) should be re-installed after reboot
####################################################################################

# Install Neuron Tools
sudo apt-get install aws-neuron-tools -y

export PATH=/opt/aws/neuron/bin:$PATH

# Activate PyTorch
source activate aws_neuron_pytorch_p36

# Set Pip repository  to point to the Neuron repository
pip config set global.extra-index-url https://pip.repos.neuron.amazonaws.com

#Install Neuron PyTorch
pip install torch-neuron neuron-cc[tensorflow] torchvision

Enable TensorFlow-Neuron

Important

For successful installation or update to Neuron 1.16.0 and newer from previous releases:
  • Stop Neuron Runtime 1.x daemon (neuron-rtd) by running: sudo systemctl stop neuron-rtd

  • Uninstall neuron-rtd by running: sudo apt remove aws-neuron-runtime or sudo yum remove aws-neuron-runtime

  • Install or upgrade to latest Neuron driver (aws-neuron-dkms) by following the “Setup Guide” instructions.

  • Visit Introducing Neuron Runtime 2.x (libnrt.so) for more information.

Note

For a successful installation or update, execute each line of the instructions below separately or copy the contents of the code block into a script file and source its contents.

# Note: There is no DLAMI Conda environment for this framework version
#       Framework will be installed/updated inside a Python environment

# Update OS packages
sudo apt-get update -y

###############################################################################################################
# Before installing or updating aws-neuron-dkms:
# - Stop any existing Neuron runtime 1.0 daemon (neuron-rtd) by calling: 'sudo systemctl stop neuron-rtd'
###############################################################################################################

################################################################################################################
# To install or update to Neuron versions 1.16.0 and newer from previous releases:
# - DO NOT skip 'aws-neuron-dkms' install or upgrade step, you MUST install or upgrade to latest Neuron driver
################################################################################################################

# Install OS headers
sudo apt-get install linux-headers-$(uname -r) -y

# Install Neuron Driver
sudo apt-get install aws-neuron-dkms -y

####################################################################################
# Warning: If Linux kernel is updated as a result of OS package update
#          Neuron driver (aws-neuron-dkms) should be re-installed after reboot
####################################################################################

# Install Neuron Tools
sudo apt-get install aws-neuron-tools -y

# Install Neuron TensorBoard
pip install tensorboard-plugin-neuron

export PATH=/opt/aws/neuron/bin:$PATH

# Install Python venv and activate Python virtual environment to install    
# Neuron pip packages.
sudo apt-get install -y python3-venv g++
python3 -m venv tensorflow_venv
source tensorflow_venv/bin/activate
pip install -U pip


# Instal Jupyter notebook kernel 
pip install ipykernel 
python -m ipykernel install --user --name tensorflow_venv --display-name "Python (Neuron TensorFlow)"
pip install jupyter notebook
pip install environment_kernels


# Set Pip repository  to point to the Neuron repository
pip config set global.extra-index-url https://pip.repos.neuron.amazonaws.com

#Install Neuron TensorFlow
pip install tensorflow-neuron[cc]

# Optional: Install Neuron TensorFlow model server
sudo apt-get install tensorflow-model-server-neuron --allow-change-held-packages -y

Enable Apache MXNet (Incubating)

Important

For successful installation or update to Neuron 1.16.0 and newer from previous releases:
  • Stop Neuron Runtime 1.x daemon (neuron-rtd) by running: sudo systemctl stop neuron-rtd

  • Uninstall neuron-rtd by running: sudo apt remove aws-neuron-runtime or sudo yum remove aws-neuron-runtime

  • Install or upgrade to latest Neuron driver (aws-neuron-dkms) by following the “Setup Guide” instructions.

  • Visit Introducing Neuron Runtime 2.x (libnrt.so) for more information.

Note

For a successful installation or update, execute each line of the instructions below separately or copy the contents of the code block into a script file and source its contents.

# Note: There is no DLAMI Conda environment for this framework version
#       Framework will be installed/updated inside a Python environment

# Update OS packages
sudo apt-get update -y

###############################################################################################################
# Before installing or updating aws-neuron-dkms:
# - Stop any existing Neuron runtime 1.0 daemon (neuron-rtd) by calling: 'sudo systemctl stop neuron-rtd'
###############################################################################################################

################################################################################################################
# To install or update to Neuron versions 1.16.0 and newer from previous releases:
# - DO NOT skip 'aws-neuron-dkms' install or upgrade step, you MUST install or upgrade to latest Neuron driver
################################################################################################################

# Install OS headers
sudo apt-get install linux-headers-$(uname -r) -y

# Install Neuron Driver
sudo apt-get install aws-neuron-dkms -y

####################################################################################
# Warning: If Linux kernel is updated as a result of OS package update
#          Neuron driver (aws-neuron-dkms) should be re-installed after reboot
####################################################################################

# Install Neuron Tools
sudo apt-get install aws-neuron-tools -y

export PATH=/opt/aws/neuron/bin:$PATH

# Activate MXNet
source activate aws_neuron_mxnet_p36

# Set Pip repository  to point to the Neuron repository
pip config set global.extra-index-url https://pip.repos.neuron.amazonaws.com

#Install Neuron MXNet
wget https://aws-mx-pypi.s3-us-west-2.amazonaws.com/1.8.0/aws_mx_cu110-1.8.0-py2.py3-none-manylinux2014_x86_64.whl
pip3 install aws_mx_cu110-1.8.0-py2.py3-none-manylinux2014_x86_64.whl
pip install mx_neuron neuron-cc

3. Set up Jupyter notebook

To develop from a Jupyter notebook see Jupyter Notebook QuickStart

You can also run a Jupyter notebook as a script, first enable the ML framework Conda or Python environment of your choice and see Running Jupyter Notebook as script for instructions.