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Neuron SDK Release 2.21.0
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‎conf.py‎

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#top_banner_message="<span>&#9888;</span><a class='reference internal' style='color:white;' href='https://awsdocs-neuron.readthedocs-hosted.com/en/latest/general/setup/setup-troubleshooting.html#gpg-key-update'> Neuron repository GPG key for Ubuntu installation has expired, see instructions how to update! </a>"
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top_banner_message="Neuron 2.21.0 Beta is released! check <a class='reference internal' style='color:white;' href='https://awsdocs-neuron.readthedocs-hosted.com/en/latest/release-notes/index.html#latest-neuron-release'> What's New </a> and <a class='reference internal' style='color:white;' href='https://awsdocs-neuron.readthedocs-hosted.com/en/latest/general/announcements/index.html'> Announcements </a>"
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top_banner_message="Neuron 2.21.0 is released! check <a class='reference internal' style='color:white;' href='https://awsdocs-neuron.readthedocs-hosted.com/en/latest/release-notes/index.html#latest-neuron-release'> What's New </a> and <a class='reference internal' style='color:white;' href='https://awsdocs-neuron.readthedocs-hosted.com/en/latest/general/announcements/index.html'> Announcements </a>"
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html_theme = "sphinx_book_theme"
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html_theme_options = {

‎containers/tutorials/k8s-prerequisite.rst‎

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* The template installs the EFA driver. Please note that the libfabric version should match between the AMI and the workload containers.
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* It uses the `EKS optimized accelerated AMI <https://docs.aws.amazon.com/eks/latest/userguide/eks-optimized-ami.html#gpu-ami>`__ which has the necessary neuron components installed. The template uses AMI for Kubernetes version 1.25. Please update to appropriate version.
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* The template adds trn1.32xlarge nodes to the cluster. Please update to the desired instance type.
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* Trn2 instance types use a default LNC (Logical NeuronCore Configuration) setting of `2`, if you want to change it to `1`, update the UserData section of the launch template to a new LNC setting as shown below, and deploy the new/updated version of launch template.
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.. code-block:: bash
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--==BOUNDARY==
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Content-Type: text/x-shellscript; charset="us-ascii"
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#!/bin/bash
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set -ex
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config_dir=/opt/aws/neuron
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config_file=${config_dir}/logical_nc_config
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[ -d "$config_dir" ] || mkdir -p "$config_dir"
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[ -f "$config_file" ] || touch "$config_file"
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if ! grep -q "^NEURON_LOGICAL_NC_CONFIG=1$" "$config_file" 2>/dev/null; then
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printf "NEURON_LOGICAL_NC_CONFIG=1" >> "$config_file"
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fi
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--==BOUNDARY==--
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Finally, run the following command to create cloud formation stack:
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‎dlami/index.rst‎

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Neuron Multi Framework DLAMI
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----------------------------
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Neuron Deep Learning AMI (DLAMI) is a multi-framework DLAMI that supports multiple Neuron framework/libraries. Each DLAMI is pre-installed with Neuron drivers and support all Neuron instance types. Each virtual environment that corresponds to a specific Neuron framework/library
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comes pre-installed with all the Neuron libraries including Neuron compiler and Neuron run-time needed for you to easily get started.
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Neuron Deep Learning AMI (DLAMI) is a multi-framework DLAMI that supports multiple Neuron framework/libraries. Each DLAMI is pre-installed with Neuron drivers and support all Neuron instance types. Each virtual environment that corresponds to a specific Neuron framework/library
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comes pre-installed with all the Neuron libraries including Neuron compiler and Neuron run-time needed for you to easily get started.
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Multi Framework DLAMIs supported
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:class: table-smaller-font-size
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* - Operating System
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- Neuron Instances Supported
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- Neuron Instances Supported
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- DLAMI Name
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* - Ubuntu 22.04
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- Inf1, Inf2, Trn1, Trn1n
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- Inf2, Trn1, Trn1n, Trn2
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- Deep Learning AMI Neuron (Ubuntu 22.04)
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* - Amazon Linux 2023
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- Inf1, Inf2, Trn1, Trn1n
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- Inf2, Trn1, Trn1n, Trn2
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- Deep Learning AMI Neuron (Amazon Linux 2023)
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:class: table-smaller-font-size
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* - Neuron Framework/Libraries supported
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- Virtual Environment
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- Virtual Environment
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* - PyTorch Neuron 2.1 (Torch NeuronX , NeuronX Distributed)
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- /opt/aws_neuronx_venv_pytorch_2_1
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* - PyTorch 2.5 Torch NeuronX, NxD Core
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- /opt/aws_neuronx_venv_pytorch_2_5
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* - PyTorch Neuron 1.13.1 (Torch NeuronX , NeuronX Distributed)
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- /opt/aws_neuronx_venv_pytorch_1_13
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* - PyTorch 2.5 NxD Training, Torch NeuronX
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- /opt/aws_neuronx_venv_pytorch_2_5_nxd_training
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* - Transformers NeuronX (PyTorch 2.1)
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- /opt/aws_neuronx_venv_transformers_neuronx
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* - PyTorch 2.5 NxD Inference, Torch NeuronX
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- /opt/aws_neuronx_venv_pytorch_2_5_nxd_inference
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* - Tensorflow Neuron 2.10 (Tensorflow NeuronX)
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* - JAX 0.4 NeuronX
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- /opt/aws_neuronx_venv_jax_0_4
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* - Tensorflow 2.10 NeuronX
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- /opt/aws_neuronx_venv_tensorflow_2_10
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* - PyTorch Neuron 1.13.1 (Inf1) (Torch Neuron)
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- /opt/aws_neuron_venv_pytorch_1_13_inf1
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* - Transformers NeuronX (PyTorch 2.5)
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- /opt/aws_neuronx_venv_pytorch_2_5_transformers
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* - Tensorflow 2.10 (Inf1) (Tensorflow Neuron)
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* - Tensorflow 2.10 Neuron (Inf1)
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- /opt/aws_neuron_venv_tensorflow_2_10_inf1
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You can easily get started with the multi-framework DLAMI through AWS console by following this :ref:`setup guide <setup-ubuntu22-multi-framework-dlami>` . If you are looking to
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use the Neuron DLAMI in your cloud automation flows , Neuron also supports :ref:`SSM parameters <ssm-parameter-neuron-dlami>` to easily retrieve the latest DLAMI id.
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You can easily get started with the multi-framework DLAMI through AWS console by following this :ref:`setup guide <setup-ubuntu22-multi-framework-dlami>`. If you are looking to
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use the Neuron DLAMI in your cloud automation flows, Neuron also supports :ref:`SSM parameters <ssm-parameter-neuron-dlami>` to easily retrieve the latest DLAMI id.
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Neuron Single Framework DLAMI
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-----------------------------
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Neuron supports single framework DLAMIs that correspond to a single framework version (ex:- PyTorch 1.13). Each DLAMI is pre-installed with Neuron drivers and supports all Neuron instance types. Each virtual environment corresponding to a specific
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Neuron framework/library comes pre-installed with all the relevant Neuron libraries including Neuron compiler and Neuron run-time.
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Neuron supports single framework DLAMIs that correspond to a single framework version (ex:- TensorFlow 2.10). Each DLAMI is pre-installed with Neuron drivers and supports all Neuron instance types. Each virtual environment corresponding to a specific
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Neuron framework/library comes pre-installed with all the relevant Neuron libraries including Neuron compiler and Neuron run-time.
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:class: table-smaller-font-size
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* - Framework
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- Operating System
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- Operating System
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* - PyTorch 2.1
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- Ubuntu 22.04
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- Inf2, Trn1, Trn1n
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- Deep Learning AMI Neuron PyTorch 2.1 (Ubuntu 22.04)
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* - PyTorch 1.13
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* - Tensorflow 2.10
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- Ubuntu 22.04
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- Inf1, Inf2, Trn1, Trn1n
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- Deep Learning AMI Neuron PyTorch 1.13 (Ubuntu 22.04)
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* - PyTorch 1.13
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- Ubuntu 20.04
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- Inf1, Inf2, Trn1, Trn1n
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- Deep Learning AMI Neuron PyTorch 1.13 (Ubuntu 20.04)
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- Inf1, Inf2, Trn1, Trn1n, Trn2
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- Deep Learning AMI Neuron TensorFlow 2.10 (Ubuntu 22.04)
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- Ubuntu 20.04
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- Inf2, Trn1, Trn1n
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- Deep Learning AMI Neuron TensorFlow 2.10 (Ubuntu 20.04)
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- Inf2, Trn1, Trn1n
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- Deep Learning AMI Neuron TensorFlow 2.10 (Ubuntu 20.04)
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- Neuron Libraries supported
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- Virtual Environment
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- torch-neuronx, neuronx-distributed
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- /opt/aws_neuron_venv_pytorch
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- torch-neuronx, neuronx-distributed
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- /opt/aws_neuron_venv_pytorch
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* - Deep Learning AMI Neuron PyTorch 1.13 (Ubuntu 22.04)
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- torch-neuron
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- /opt/aws_neuron_venv_pytorch_inf1
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* - Deep Learning AMI Neuron PyTorch 1.13 (Ubuntu 20.04)
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- torch-neuronx, neuronx-distributed
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- /opt/aws_neuron_venv_pytorch
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- torch-neuron
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* - Deep Learning AMI Neuron TensorFlow 2.10 (Ubuntu 22.04)
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- tensorflow-neuronx
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- /opt/aws_neuron_venv_tensorflow
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You can easily get started with the single framework DLAMI through AWS console by following one of the corresponding setup guides . If you are looking to
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use the Neuron DLAMI in your cloud automation flows , Neuron also supports :ref:`SSM parameters <ssm-parameter-neuron-dlami>` to easily retrieve the latest DLAMI id.
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- /opt/aws_neuronx_venv_tensorflow_2_10
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* - Deep Learning AMI Neuron TensorFlow 2.10 (Ubuntu 20.04)
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- tensorflow-neuronx
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- /opt/aws_neuron_venv_tensorflow_2_10
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* - Deep Learning AMI Neuron TensorFlow 2.10 (Ubuntu 22.04)
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- tensorflow-neuron (Inf1)
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- /opt/aws_neuron_venv_tensorflow_2_10_inf1
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You can easily get started with the single framework DLAMI through AWS console by following one of the corresponding setup guides . If you are looking to
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use the Neuron DLAMI in your cloud automation flows , Neuron also supports :ref:`SSM parameters <ssm-parameter-neuron-dlami>` to easily retrieve the latest DLAMI id.
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Neuron Base DLAMI
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Finding specific DLAMI image id with the latest neuron release
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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You can find the DLAMI that supports latest Neuron SDK by using the SSM get-parameter.
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You can find the DLAMI that supports latest Neuron SDK by using the SSM get-parameter.
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.. code-block::
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SSM Parameter Prefix
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""""""""""""""""""""
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.. list-table::
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:widths: 20 39
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:widths: 20 39
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:header-rows: 1
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:align: left
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* - Deep Learning AMI Neuron (Ubuntu 22.04)
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- /aws/service/neuron/dlami/multi-framework/amazon-linux-2023
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* - Deep Learning AMI Neuron PyTorch 2.1 (Ubuntu 22.04)
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- /aws/service/neuron/dlami/pytorch-2.1/ubuntu-22.04
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- /aws/service/neuron/dlami/pytorch-1.13/ubuntu-22.04
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* - Deep Learning AMI Neuron TensorFlow 2.10 (Ubuntu 22.04)
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- /aws/service/neuron/dlami/tensorflow-2.10/ubuntu-22.04
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You can find all available parameters supported in Neuron DLAMis via CLI
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.. code-block::
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aws ssm get-parameters-by-path \
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--region us-east-1 \
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--path /aws/service/neuron \
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"""""""""""""""""""""""""""""""""""""""""""""""""""""
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You can use CLI to find the latest DLAMI id and also launch the instance simulataneuosly.
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Below code snippet shows an example of launching inf2 instance using multi-framework DLAMI
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Below code snippet shows an example of launching inf2 instance using multi-framework DLAMI
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.. code-block::
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aws ec2 run-instances \
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--region us-east-1 \
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--image-id resolve:ssm:/aws/service/neuron/dlami/pytorch-1.13/amazon-linux-2/latest/image_id \
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--image-id resolve:ssm:/aws/service/neuron/dlami/tensorflow-2.10/ubuntu-22.04/latest/image_id \
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--count 1 \
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--instance-type inf2.48xlarge \
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--key-name <my-key-pair> \
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"""""""""""""""""""""""""""""""""""""
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SSM Parameters can also be used directly in launch templates. So, you can update your Auto Scaling groups to use new AMI IDs without needing to create new launch templates or new versions of launch templates each time an AMI ID changes.
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SSM Parameters can also be used directly in launch templates. So, you can update your Auto Scaling groups to use new AMI IDs without needing to create new launch templates or new versions of launch templates each time an AMI ID changes.
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Ref: https://docs.aws.amazon.com/autoscaling/ec2/userguide/using-systems-manager-parameters.html
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‎frameworks/mxnet-neuron/setup/mxnet-install-prev-al2023.rst‎

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.. tab-set::
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.. tab-item:: Neuron 2.20.0
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.. program-output:: python3 src/helperscripts/n2-helper.py --install-type=install --category=compiler_framework --framework=mxnet --framework-version=1.8.0 --neuron-version=2.20.0 --file=src/helperscripts/n2-manifest.json --os=amazonlinux2023 --instance=inf1 --ami=non-dlami
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.. program-output:: python3 src/helperscripts/n2-helper.py --install-type=install --category=compiler_framework --framework=mxnet --framework-version=1.8.0 --neuron-version=2.18.0 --file=src/helperscripts/n2-manifest.json --os=amazonlinux2023 --instance=inf1 --ami=non-dlami
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‎frameworks/mxnet-neuron/setup/mxnet-install-prev-u20.rst‎

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.. program-output:: python3 src/helperscripts/n2-helper.py --install-type=install --category=compiler_framework --framework=mxnet --framework-version=1.8.0 --neuron-version=2.20.0 --file=src/helperscripts/n2-manifest.json --os=ubuntu20 --instance=inf1 --ami=non-dlami
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‎frameworks/mxnet-neuron/setup/mxnet-install-prev-u22.rst‎

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.. tab-item:: Neuron 2.20.0
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.. program-output:: python3 src/helperscripts/n2-helper.py --install-type=install --category=compiler_framework --framework=mxnet --framework-version=1.8.0 --neuron-version=2.20.0 --file=src/helperscripts/n2-manifest.json --os=ubuntu22 --instance=inf1 --ami=non-dlami
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.. program-output:: python3 src/helperscripts/n2-helper.py --install-type=install --category=compiler_framework --framework=mxnet --framework-version=1.8.0 --neuron-version=2.18.0 --file=src/helperscripts/n2-manifest.json --os=ubuntu22 --instance=inf1 --ami=non-dlami
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‎frameworks/tensorflow/tensorflow-neuron/setup/tensorflow-install-prev-al2023.rst‎

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.. program-output:: python3 src/helperscripts/n2-helper.py --install-type=install --category=compiler_framework --framework=tensorflow --framework-version=2.10.1 --neuron-version=2.20.0 --file=src/helperscripts/n2-manifest.json --os=amazonlinux2023 --instance=inf1 --ami=non-dlami
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.. program-output:: python3 src/helperscripts/n2-helper.py --install-type=install --category=compiler_framework --framework=tensorflow --framework-version=2.10.1 --neuron-version=2.19.0 --file=src/helperscripts/n2-manifest.json --os=amazonlinux2023 --instance=inf1 --ami=non-dlami
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.. tab-item:: Neuron 2.18.0
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.. program-output:: python3 src/helperscripts/n2-helper.py --install-type=install --category=compiler_framework --framework=tensorflow --framework-version=2.10.1 --neuron-version=2.18.0 --file=src/helperscripts/n2-manifest.json --os=amazonlinux2023 --instance=inf1 --ami=non-dlami
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.. tab-item:: Neuron 2.17.0
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.. program-output:: python3 src/helperscripts/n2-helper.py --install-type=install --category=compiler_framework --framework=tensorflow --framework-version=2.10.1 --neuron-version=2.17.0 --file=src/helperscripts/n2-manifest.json --os=amazonlinux2023 --instance=inf1 --ami=non-dlami

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