Merge branch 'aws:main' into ruinon-dev

README.md

@@ -1,7 +1,7 @@
 ## Amazon SageMaker Distribution
 
 Amazon SageMaker Distribution is a set of Docker images that include popular frameworks for machine learning, data
-science and visualization.
+science and visualization. For the list of supported SageMaker Distributions images, see [SageMaker Distributions Images](supported_images.md#supported-image-versions).
 
 These images come in two variants, CPU and GPU, and include deep learning frameworks like PyTorch, TensorFlow and
 Keras; popular Python packages like numpy, scikit-learn and pandas; and IDEs like Jupyter Lab. The distribution contains

build_artifacts/v1/v1.9/v1.9.0/cpu.additional_packages_env.in

@@ -1 +1,3 @@
 conda-forge::langchain-aws[version='>=0.1.1,<0.2.0']
+conda-forge::amazon-sagemaker-jupyter-ai-q-developer[version='>=1.0.3,<2.0']
+conda-forge::amazon-q-developer-jupyterlab-ext[version='>=3.1.0,<4.0']

build_artifacts/v1/v1.9/v1.9.0/gpu.additional_packages_env.in

@@ -1 +1,3 @@
 conda-forge::langchain-aws[version='>=0.1.1,<0.2.0']
+conda-forge::amazon-sagemaker-jupyter-ai-q-developer[version='>=1.0.3,<2.0']
+conda-forge::amazon-q-developer-jupyterlab-ext[version='>=3.1.0,<4.0']

build_artifacts/v2/v2.0/v2.0.0/cpu.additional_packages_env.in

@@ -0,0 +1,3 @@
+#Add any additional packages here
+conda-forge::mlflow[version='>=2.13.2,<3.0']
+conda-forge::sagemaker-mlflow[version='>=0.1.0,<1.0']

build_artifacts/v2/v2.0/v2.0.0/gpu.additional_packages_env.in

@@ -0,0 +1,3 @@
+#Add any additional packages here
+conda-forge::mlflow[version='>=2.13.2,<3.0']
+conda-forge::sagemaker-mlflow[version='>=0.1.0,<1.0']

supported_images.md

@@ -0,0 +1,25 @@
+## Supported Image Versions
+
+The tables below list the supported SageMaker Distribution image versions. SageMaker will only release functionality and security fixes for images versions present in the tables. When you are building images or pulling images from the ECR repository, it is highly recommended for you to choose the supported image versions from the tables below.
+
+### CPU Images
+
+| Image Major Version | Image Minor Version |     ECR Image URI     |
+|---------------------|---------------------|-----------------------|
+|1                    |1.8                  |public.ecr.aws/sagemaker/sagemaker-distribution:1.8-cpu    |
+|1                    |1.7                  |public.ecr.aws/sagemaker/sagemaker-distribution:1.7-cpu    |
+|1                    |1.6                  |public.ecr.aws/sagemaker/sagemaker-distribution:1.6-cpu    |
+|1                    |1.5                  |public.ecr.aws/sagemaker/sagemaker-distribution:1.5-cpu    |
+|1                    |1.4                  |public.ecr.aws/sagemaker/sagemaker-distribution:1.4-cpu    |
+|0                    |0.12                 |public.ecr.aws/sagemaker/sagemaker-distribution:0.12-cpu    |
+
+### GPU Images
+
+| Image Major Version | Image Minor Version |     ECR Image URI     |
+|---------------------|---------------------|-----------------------|
+|1                    |1.8                  |public.ecr.aws/sagemaker/sagemaker-distribution:1.8-gpu    |
+|1                    |1.7                  |public.ecr.aws/sagemaker/sagemaker-distribution:1.7-gpu    |
+|1                    |1.6                  |public.ecr.aws/sagemaker/sagemaker-distribution:1.6-gpu    |
+|1                    |1.5                  |public.ecr.aws/sagemaker/sagemaker-distribution:1.5-gpu    |
+|1                    |1.4                  |public.ecr.aws/sagemaker/sagemaker-distribution:1.4-gpu    |
+|0                    |0.12                 |public.ecr.aws/sagemaker/sagemaker-distribution:0.12-gpu    |

test/test_artifacts/v1/amazon-codewhisperer-jupyterlab-ext.test.Dockerfile → test/test_artifacts/v2/amazon-q-developer-jupyterlab-ext.test.Dockerfile

@@ -3,4 +3,4 @@ FROM $SAGEMAKER_DISTRIBUTION_IMAGE
 
 ARG MAMBA_DOCKERFILE_ACTIVATE=1
 
-CMD ["python", "-c", "import amazon_codewhisperer_jupyterlab_ext"]
+CMD ["python", "-c", "import amazon_q_developer_jupyterlab_ext"]

test/test_artifacts/v2/amazon-sagemaker-jupyter-ai-q-developer.test.Dockerfile

@@ -0,0 +1,6 @@
+ARG SAGEMAKER_DISTRIBUTION_IMAGE
+FROM $SAGEMAKER_DISTRIBUTION_IMAGE
+
+ARG MAMBA_DOCKERFILE_ACTIVATE=1
+
+CMD ["python", "-c", "import amazon_sagemaker_jupyter_ai_q_developer"]

test/test_artifacts/v2/mlflow.test.Dockerfile

@@ -0,0 +1,16 @@
+ARG SAGEMAKER_DISTRIBUTION_IMAGE
+FROM $SAGEMAKER_DISTRIBUTION_IMAGE
+
+ARG MAMBA_DOCKERFILE_ACTIVATE=1
+
+RUN python -c "import mlflow"
+
+RUN sudo apt-get update && sudo apt-get install -y git && \
+    git clone --recursive https://github.com/mlflow/mlflow.git && \
+    :
+
+WORKDIR "mlflow/"
+COPY --chown=$MAMBA_USER:$MAMBA_USER scripts/run_mlflow_tests.sh .
+RUN chmod +x run_mlflow_tests.sh
+# Run tests in run_matplotlib_tests.sh
+CMD ["./run_mlflow_tests.sh"]

test/test_artifacts/v2/sagemaker-mlflow.test.Dockerfile

@@ -0,0 +1,19 @@
+ARG SAGEMAKER_DISTRIBUTION_IMAGE
+FROM $SAGEMAKER_DISTRIBUTION_IMAGE
+
+ARG MAMBA_DOCKERFILE_ACTIVATE=1
+
+RUN python -c "import sagemaker_mlflow"
+
+RUN sudo apt-get update && sudo apt-get install -y git && \
+    git clone --recursive https://github.com/aws/sagemaker-mlflow.git && \
+    :
+
+# For running sagemaker-mlflow tests, we need pytest
+RUN micromamba install -y --freeze-installed -c conda-forge pytest
+
+WORKDIR "sagemaker-mlflow/"
+COPY --chown=$MAMBA_USER:$MAMBA_USER scripts/run_sagemaker_mlflow_tests.sh .
+RUN chmod +x run_sagemaker_mlflow_tests.sh
+# Run tests in run_matplotlib_tests.sh
+CMD ["./run_sagemaker_mlflow_tests.sh"]

test/test_artifacts/v2/scripts/run_mlflow_tests.sh

@@ -0,0 +1,30 @@
+#!/bin/bash
+
+set -e
+
+# Run examples for keras, pytorch, sklearn, tensorflow
+cd examples
+
+# keras
+cd keras/
+python train.py
+cd -
+
+# pytorch
+cd pytorch/
+python mnist_tensorboard_artifact.py
+cd -
+
+# sklearn
+for folder in "sklearn_autolog/" "sklearn_elasticnet_diabetes/linux/" "sklearn_elasticnet_wine/" "sklearn_logistic_regression/"; do
+  cd ${folder}
+  for file in *.py; do
+    python "$file" || exit $?
+  done
+  cd -
+done
+
+# tensorflow
+cd tensorflow/
+python train.py
+cd -

test/test_artifacts/v2/scripts/run_sagemaker_mlflow_tests.sh

@@ -0,0 +1,5 @@
+#!/bin/bash
+
+set -e
+
+pytest -s -rA -vv test/unit

test/test_dockerfile_based_harness.py

@@ -44,6 +44,7 @@
         ("amazon_sagemaker_sql_editor.test.Dockerfile", ["amazon_sagemaker_sql_editor"]),
         ("serve.test.Dockerfile", ["serve-langchain"]),
         ("langchain-aws.test.Dockerfile", ["langchain-aws"]),
+        ("mlflow.test.Dockerfile", ["mlflow"]),
     ],
 )
 def test_dockerfiles_for_cpu(
@@ -83,6 +84,8 @@ def test_dockerfiles_for_cpu(
         ("amazon_sagemaker_sql_editor.test.Dockerfile", ["amazon_sagemaker_sql_editor"]),
         ("serve.test.Dockerfile", ["serve-langchain"]),
         ("langchain-aws.test.Dockerfile", ["langchain-aws"]),
+        ("mlflow.test.Dockerfile", ["mlflow"]),
+        ("sagemaker-mlflow.test.Dockerfile", ["sagemaker-mlflow"]),
     ],
 )
 def test_dockerfiles_for_gpu(