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environments tensorflow 2.16 cuda12

github-actions[bot] edited this page Apr 12, 2025 · 12 revisions

tensorflow-2.16-cuda12

Overview

An environment for deep learning with Tensorflow containing the Azure ML SDK and additional python packages.

Version: 12

Tags

Tensorflow : 2.16 GPU : Cuda12 OS : Ubuntu20.04 Training Preview Python : 3.10

View in Studio: https://ml.azure.com/registries/azureml/environments/tensorflow-2.16-cuda12/version/12

Docker image: mcr.microsoft.com/azureml/curated/tensorflow-2.16-cuda12:12

Docker build context

Dockerfile

# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.

FROM mcr.microsoft.com/azureml/o16n-base/python-assets:20250310.v1 AS inferencing-assets

# Tag: 12.8.1-cudnn-devel-ubuntu22.04
# Env: CUDA_VERSION=12.8.1
# Env: NCCL_VERSION=2.12.7-1
# Env: NV_CUDNN_VERSION=9

# DisableDockerDetector "Preferred to use nvidia registry over MCR mirror"

FROM nvcr.io/nvidia/cuda:12.8.1-cudnn-devel-ubuntu22.04

USER root:root

ARG IMAGE_NAME=None
ARG BUILD_NUMBER=None

ENV com.nvidia.cuda.version $CUDA_VERSION
ENV com.nvidia.volumes.needed nvidia_driver
ENV LANG=C.UTF-8 LC_ALL=C.UTF-8
ENV DEBIAN_FRONTEND noninteractive
ENV LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64
ENV NCCL_DEBUG=INFO
ENV HOROVOD_GPU_ALLREDUCE=NCCL

# Install Common Dependencies
RUN apt-get update && \
    apt-get install -y --no-install-recommends \
    curl \
    git \
    wget \
    zlib1g-dev \
	librdmacm-dev \
	libibverbs-dev \
    dh-make \
    # Vulnerability fixes
    libgnutls30 \
    libc-bin \
    libgssapi-krb5-2 \
    libpam-cap \
    libtasn1-6 \
    libk5crypto3 \
    libcap2 && \
    apt-get clean -y && \
    rm -rf /var/lib/apt/lists/* 
               
# Update to latest redis       
RUN apt-get update && apt-get install -y lsb-release && \
    curl -fsSL https://packages.redis.io/gpg | gpg --dearmor -o /usr/share/keyrings/redis-archive-keyring.gpg && \
    echo "deb [signed-by=/usr/share/keyrings/redis-archive-keyring.gpg] https://packages.redis.io/deb $(lsb_release -cs) main" | tee /etc/apt/sources.list.d/redis.list && \
    apt-get update && apt-get install -y redis

# Inference
# Copy logging utilities, nginx and rsyslog configuration files, IOT server binary, etc.
COPY --from=inferencing-assets /artifacts /var/
RUN apt-get update && \
    apt-get install -y --no-install-recommends \
        libcurl4 \
        liblttng-ust1 \
        libunwind8 \
        libxml++2.6-2v5 \
        nginx-light \
        psmisc \
        rsyslog \
        runit \
        unzip && \
    apt-get clean && rm -rf /var/lib/apt/lists/* && \
    cp /var/configuration/rsyslog.conf /etc/rsyslog.conf && \
    cp /var/configuration/nginx.conf /etc/nginx/sites-available/app && \
    ln -s /etc/nginx/sites-available/app /etc/nginx/sites-enabled/app && \
    rm -f /etc/nginx/sites-enabled/default
ENV SVDIR=/var/runit
ENV WORKER_TIMEOUT=300
EXPOSE 5001 8883 8888
# Stores image version information and log it while running inferencing server for better Debuggability
RUN if [ "$BUILD_NUMBER" != "None" ] && [ "$IMAGE_NAME" != "None" ]; then echo "${IMAGE_NAME}, Materializaton Build:${BUILD_NUMBER}" > /IMAGE_INFORMATION ; fi

# Conda Environment
ENV MINICONDA_VERSION py310_23.10.0-1
ENV PATH /opt/miniconda/bin:$PATH
RUN wget -qO /tmp/miniconda.sh https://repo.anaconda.com/miniconda/Miniconda3-${MINICONDA_VERSION}-Linux-x86_64.sh && \
    bash /tmp/miniconda.sh -bf -p /opt/miniconda && \
    conda update --all -c conda-forge -y && \
    conda clean -ay && \
    rm -rf /opt/miniconda/pkgs && \
    rm /tmp/miniconda.sh && \
    find / -type d -name __pycache__ | xargs rm -rf   

# Open-MPI-UCX installation
RUN mkdir /tmp/ucx && \
    cd /tmp/ucx && \
        wget -q https://github.com/openucx/ucx/releases/download/v1.17.0/ucx-1.17.0.tar.gz && \
        tar zxf ucx-1.17.0.tar.gz && \
	cd ucx-1.17.0 && \
        ./configure --prefix=/usr/local --enable-optimizations --disable-assertions --disable-params-check --enable-mt && \
        make -j $(nproc --all) && \
        make install && \
        rm -rf /tmp/ucx

# Open-MPI installation
ENV OPENMPI_VERSION 4.1.0
RUN mkdir /tmp/openmpi && \
    cd /tmp/openmpi && \
    wget https://download.open-mpi.org/release/open-mpi/v4.1/openmpi-${OPENMPI_VERSION}.tar.gz && \
    tar zxf openmpi-${OPENMPI_VERSION}.tar.gz && \
    cd openmpi-${OPENMPI_VERSION} && \
    ./configure --with-ucx=/usr/local/ --enable-mca-no-build=btl-uct --enable-orterun-prefix-by-default && \
    make -j $(nproc) all && \
    make install && \
    ldconfig && \
    rm -rf /tmp/openmpi
    	
# Msodbcsql17 installation
RUN curl https://packages.microsoft.com/keys/microsoft.asc | apt-key add - && \
    curl https://packages.microsoft.com/config/ubuntu/22.04/prod.list > /etc/apt/sources.list.d/mssql-release.list && \
    apt-get update && \
    ACCEPT_EULA=Y apt-get install -y msodbcsql17 unixodbc-dev

#Cmake Installation
RUN apt-get update && \
    apt-get install -y cmake

# rdma-core
RUN apt-get update && \
    apt-get install -y --no-install-recommends rdma-core && \
    apt-get clean && rm -rf /var/lib/apt/lists/*

#Install latest version of nccl-rdma-sharp-plugins
RUN cd /tmp && \
    mkdir -p /usr/local/nccl-rdma-sharp-plugins && \
    apt install -y dh-make zlib1g-dev && \
    git clone -b v2.1.0 https://github.com/Mellanox/nccl-rdma-sharp-plugins.git && \
    cd nccl-rdma-sharp-plugins && \
    ./autogen.sh && \
    ./configure --prefix=/usr/local/nccl-rdma-sharp-plugins --with-cuda=/usr/local/cuda --without-ucx && \
    make && \
    make install

# set env var to find nccl rdma plugins inside this container
ENV LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/nccl-rdma-sharp-plugins/lib

WORKDIR /

ENV CONDA_PREFIX=/azureml-envs/tensorflow-2.16-cuda12
ENV CONDA_DEFAULT_ENV=$CONDA_PREFIX
ENV PATH=$CONDA_PREFIX/bin:$PATH

# Enable debug
RUN apt-get update && \
    apt-get install --reinstall -y openssl libssl-dev openssh-server openssh-client && \
    apt-get clean && \
    rm -rf /var/lib/apt/lists/*

# Create conda environment
COPY conda_dependencies.yaml .
RUN conda env create -p $CONDA_PREFIX -f conda_dependencies.yaml -q && \
    rm conda_dependencies.yaml && \
    conda run -p $CONDA_PREFIX pip cache purge && \
    conda clean -a -y

RUN conda run -p $CONDA_PREFIX

RUN HOROVOD_WITH_TENSORFLOW=1 pip install horovod[tensorflow]

# Reinstall OpenSSL inside Conda
RUN conda run -p $CONDA_PREFIX conda install -c conda-forge openssl=3.0.2

# This is needed for mpi to locate libpython
ENV LD_LIBRARY_PATH=$CONDA_PREFIX/lib:$LD_LIBRARY_PATH

ENV TF_USE_LEGACY_KERAS=1
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