environments automl dnn vision gpu - Azure/azureml-assets GitHub Wiki

automl-dnn-vision-gpu

Overview

GPU based environment for finetuning AutoML legacy models for image tasks.

Version: 45

Tags

OS : Ubuntu20.04 Training Preview

View in Studio: https://ml.azure.com/registries/azureml/environments/automl-dnn-vision-gpu/version/45

Docker image: mcr.microsoft.com/azureml/curated/automl-dnn-vision-gpu:45

Docker build context

Dockerfile

FROM mcr.microsoft.com/aifx/acpt/stable-ubuntu2004-cu121-py310-torch222:biweekly.202410.2


ENV AZUREML_CONDA_ENVIRONMENT_PATH /azureml-envs/azureml-automl-dnn-vision-gpu
# Prepend path to AzureML conda environment
ENV PATH $AZUREML_CONDA_ENVIRONMENT_PATH/bin:$PATH

COPY --from=mcr.microsoft.com/azureml/mlflow-ubuntu20.04-py38-cpu-inference:20230306.v3 /var/mlflow_resources/mlflow_score_script.py /var/mlflow_resources/mlflow_score_script.py

ENV MLFLOW_MODEL_FOLDER="mlflow-model"
# ENV AML_APP_ROOT="/var/mlflow_resources"
# ENV AZUREML_ENTRY_SCRIPT="mlflow_score_script.py"

# Inference requirements
COPY --from=mcr.microsoft.com/azureml/o16n-base/python-assets:20230419.v1 /artifacts /var/
RUN /var/requirements/install_system_requirements.sh && \
    cp /var/configuration/rsyslog.conf /etc/rsyslog.conf && \
    cp /var/configuration/nginx.conf /etc/nginx/sites-available/app && \
    ln -sf /etc/nginx/sites-available/app /etc/nginx/sites-enabled/app && \
    rm -f /etc/nginx/sites-enabled/default
ENV SVDIR=/var/runit
ENV WORKER_TIMEOUT=400
EXPOSE 5001 8883 8888

ENV ENABLE_METADATA=true

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

# vulnearbility fix
RUN pip install pyarrow==14.0.2

ENV LD_LIBRARY_PATH $AZUREML_CONDA_ENVIRONMENT_PATH/lib:$LD_LIBRARY_PATH
# dummy number to change when needing to force rebuild without changing the definition: 1
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