environments ai ml automl gpu - Azure/azureml-assets GitHub Wiki
An environment used by Azure ML AutoML for training models.
Version: 9
OS : Ubuntu20.04
Training
Preview
OpenMpi : 4.1.0
Python : 3.9
View in Studio: https://ml.azure.com/registries/azureml/environments/ai-ml-automl-gpu/version/9
Docker image: mcr.microsoft.com/azureml/curated/ai-ml-automl-gpu:9
FROM mcr.microsoft.com/azureml/openmpi4.1.0-cuda11.1-cudnn8-ubuntu20.04:20241111.v1
USER root
ENV AZUREML_CONDA_ENVIRONMENT_PATH /azureml-envs/azureml-automl-dnn-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"
ENV ENABLE_METADATA=true
RUN mkdir -p /etc/OpenCL/vendors && echo "libnvidia-opencl.so.1" > /etc/OpenCL/vendors/nvidia.icd
RUN apt-get update && echo 'success updated apt-get!'
RUN apt-get install -y --no-install-recommends cmake libboost-dev libboost-system-dev libboost-filesystem-dev
RUN conda create -p $AZUREML_CONDA_ENVIRONMENT_PATH python=3.9 pip=22.1.2 -y
RUN conda run -p $AZUREML_CONDA_ENVIRONMENT_PATH
###############################
# Pre-Build LightGBM
###############################
RUN cd /usr/local/src && mkdir lightgbm && cd lightgbm && \
git clone --recursive --branch v3.2.1 --depth 1 https://github.com/microsoft/LightGBM && \
cd LightGBM && mkdir build && cd build && \
cmake -DUSE_GPU=1 -DOpenCL_LIBRARY=/usr/local/cuda/lib64/libOpenCL.so -DOpenCL_INCLUDE_DIR=/usr/local/cuda/include/ .. && \
make -j4
###############################
# Install GPU LightGBM and XgBoost
###############################
RUN /bin/bash -c "cd /usr/local/src/lightgbm/LightGBM/python-package && python setup.py install --precompile && \
pip install --upgrade --force-reinstall xgboost==1.5.2 pandas==1.5.3"
# begin conda create
# Create conda environment
RUN conda install -p $AZUREML_CONDA_ENVIRONMENT_PATH \
# begin conda dependencies
numpy~=1.23.5 \
scikit-learn=1.5.1 \
holidays=0.29 \
setuptools-git \
setuptools=72.1.0 \
wheel=0.44.0 \
scipy=1.10.1 \
'psutil>5.0.0,<6.0.0' \
cudatoolkit=10.0.130 \
# end conda dependencies
-c conda-forge -c pytorch -c anaconda
# end conda create
# begin pip install
# Install pip dependencies
RUN pip install \
# begin pypi dependencies
azureml-core==1.58.0 \
azureml-mlflow==1.58.0.post3 \
azureml-pipeline-core==1.58.0 \
azureml-telemetry==1.58.0 \
azureml-defaults==1.58.0 \
azureml-interpret==1.58.0 \
azureml-responsibleai==1.58.0 \
azureml-automl-core==1.58.0 \
azureml-automl-runtime==1.58.0 \
azureml-train-automl-client==1.58.0 \
azureml-train-automl-runtime==1.58.0 \
azureml-dataset-runtime==1.58.0 \
'azureml-model-management-sdk==1.0.1b6.post1' \
'azure-identity>=1.16.1' \
'inference-schema' \
'py-cpuinfo==5.0.0' \
'prophet==1.1.4' \
'cryptography>=42.0.5' \
'requests>=2.31.0' \
'certifi>=2023.07.22'
# end pypi dependencies
# end pip install
ENV LD_LIBRARY_PATH $AZUREML_CONDA_ENVIRONMENT_PATH/lib:$LD_LIBRARY_PATH