release: v1.9.1

[claytonparnell]

Issue #, if available:

Description of changes:

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[claytonparnell]

Staleness Report: 1.9.1(gpu)

Package	Current Version in the Distribution image	Latest Relevant Version in Upstream
numpy	1.26.4	1.26.4
jinja2	3.1.4	3.1.4
pandas	2.1.4	2.1.4
altair	5.3.0	5.3.0
${\color{red}boto3}$	1.34.131	1.34.150
ipython	8.25.0	8.25.0
jupyter-lsp	2.2.5	2.2.5
amazon-sagemaker-jupyter-scheduler	3.1.2	3.1.2
amazon-sagemaker-sql-magic	0.1.3	0.1.3
jupyterlab-lsp	5.0.3	5.0.3
amazon_sagemaker_sql_editor	0.1.10	0.1.10
scipy	1.11.4	1.11.4
scikit-learn	1.4.2	1.4.2
pip	23.3.2	23.3.2
torchvision	0.15.2	0.15.2
autogluon	0.8.3	0.8.3
ipywidgets	8.1.3	8.1.3
notebook	7.1.3	7.1.3
aws-glue-sessions	1.0.6	1.0.6
conda	23.11.0	23.11.0
fastapi	0.110.3	0.110.3
jupyter-collaboration	1.1.0	1.1.0
jupyter-dash	0.4.2	0.4.2
jupyter-server-proxy	4.2.0	4.2.0
jupyterlab-git	0.50.1	0.50.1
keras	2.14.0	2.14.0
${\color{red}langchain-aws}$	0.1.6	0.1.12
matplotlib	3.8.4	3.8.4
nodejs	18.20.3	18.20.3
py-xgboost-gpu	1.7.6	1.7.6
thrift_sasl	0.4.3	0.4.3
pyhive	0.7.0	0.7.0
python-gssapi	1.8.3	1.8.3
python-lsp-server	1.11.0	1.11.0
pytorch-gpu	2.0.0	2.0.0
sagemaker-code-editor	1.1.0	1.1.0
sagemaker-headless-execution-driver	0.0.13	0.0.13
sagemaker-jupyterlab-emr-extension	0.1.9	0.1.9
sagemaker-jupyterlab-extension	0.3.2	0.3.2
sagemaker-kernel-wrapper	0.0.2	0.0.2
sagemaker-python-sdk	2.224.4	2.224.4
sagemaker-studio-analytics-extension	0.0.22	0.0.22
sasl	0.3.1	0.3.1
supervisor	4.2.5	4.2.5
tensorflow-gpu	2.14.0	2.14.0
uvicorn	0.30.3	0.30.3

Staleness Report: 1.9.1(cpu)

Package	Current Version in the Distribution image	Latest Relevant Version in Upstream
numpy	1.26.4	1.26.4
jinja2	3.1.4	3.1.4
pytorch	2.0.0	2.0.0
pandas	2.1.4	2.1.4
altair	5.3.0	5.3.0
${\color{red}boto3}$	1.34.131	1.34.150
ipython	8.25.0	8.25.0
jupyter-lsp	2.2.5	2.2.5
${\color{red}jupyterlab}$	4.1.6	4.1.8
amazon-q-developer-jupyterlab-ext	3.1.0	3.1.0
${\color{red}langchain}$	0.1.9	0.1.20
jupyter-ai	2.18.1	2.18.1
amazon-sagemaker-jupyter-ai-q-developer	1.0.7	1.0.7
jupyter-scheduler	2.7.1	2.7.1
amazon-sagemaker-jupyter-scheduler	3.1.2	3.1.2
amazon-sagemaker-sql-magic	0.1.3	0.1.3
jupyterlab-lsp	5.0.3	5.0.3
amazon_sagemaker_sql_editor	0.1.10	0.1.10
scipy	1.11.4	1.11.4
scikit-learn	1.4.2	1.4.2
pip	23.3.2	23.3.2
torchvision	0.15.2	0.15.2
autogluon	0.8.3	0.8.3
ipywidgets	8.1.3	8.1.3
notebook	7.1.3	7.1.3
aws-glue-sessions	1.0.6	1.0.6
conda	23.11.0	23.11.0
fastapi	0.110.3	0.110.3
jupyter-collaboration	1.1.0	1.1.0
jupyter-dash	0.4.2	0.4.2
jupyter-server-proxy	4.2.0	4.2.0
jupyterlab-git	0.50.1	0.50.1
keras	2.15.0	2.15.0
${\color{red}langchain-aws}$	0.1.6	0.1.12
matplotlib	3.8.4	3.8.4
nodejs	18.20.3	18.20.3
py-xgboost-cpu	1.7.6	1.7.6
thrift_sasl	0.4.3	0.4.3
pyhive	0.7.0	0.7.0
python-gssapi	1.8.3	1.8.3
python-lsp-server	1.11.0	1.11.0
sagemaker-code-editor	1.1.0	1.1.0
sagemaker-headless-execution-driver	0.0.13	0.0.13
sagemaker-jupyterlab-emr-extension	0.1.9	0.1.9
sagemaker-jupyterlab-extension	0.3.2	0.3.2
sagemaker-kernel-wrapper	0.0.2	0.0.2
sagemaker-python-sdk	2.224.4	2.224.4
sagemaker-studio-analytics-extension	0.0.22	0.0.22
sasl	0.3.1	0.3.1
supervisor	4.2.5	4.2.5
tensorflow	2.15.0	2.15.0
uvicorn	0.30.3	0.30.

[claytonparnell]

Failed tests

============================================================================================== short test summary info ===============================================================================================
FAILED test/test_dockerfile_based_harness.py::test_dockerfiles_for_gpu[keras.test.Dockerfile-required_packages0] - assert 1 == 0
FAILED test/test_dockerfile_based_harness.py::test_dockerfiles_for_gpu[scipy.test.Dockerfile-required_packages4] - assert 1 == 0
FAILED test/test_dockerfile_based_harness.py::test_dockerfiles_for_gpu[sm-python-sdk.test.Dockerfile-required_packages8] - assert 1 == 0
FAILED test/test_dockerfile_based_harness.py::test_dockerfiles_for_gpu[pytorch.examples.Dockerfile-required_packages9] - assert 1 == 0

Confirmed that these failed with the issues tracked

• keras - Fix keras tests for GPU based docker images #413
• scipy - Fix Scipy tests for GPU based docker images #30
• sm-python-sdk - sm-python-sdk test failures #316

pytorch succeeded when reran

[TRNWWZ]

Is this introduced recently?

[claytonparnell]

Yeah in 1.9.0 we switched to fix the gpu issue in 1.8. From 2.0 we switch back to standard tensorflow

[TRNWWZ]

May not related to this PR. But why in staleness report, pytorch and pytorch-gpu Latest Relevant Version in Upstream is only 2.0.0?

[claytonparnell]

May not related to this PR. But why in staleness report, pytorch and pytorch-gpu Latest Relevant Version in Upstream is only 2.0.0?

Since this is a patch release, the latest relevant version would be latest patch from v2.0. So since there's no 2.0.1, 2.0.0 is latest "relevant" version

[TRNWWZ]

Do we need the change to remove conda default channel and use conda-forge only in Docker file?

[claytonparnell]

Do we need the change to remove conda default channel and use conda-forge only in Docker file?

No, we're doing that change from 2.0. For v1 since it's breaking change we are keeping it the same