Merge branch 'master' into parknate-doc-fixes

Author: sage-maker

CHANGELOG.md

@@ -1,5 +1,15 @@
 # Changelog
 
+## v2.239.2 (2025-02-18)
+
+### Bug Fixes and Other Changes
+
+ * Add warning about not supporting torch.nn.SyncBatchNorm
+ * pass in inference_ami_version to model_based endpoint type
+ * Fix hyperparameter strategy docs
+ * Add framework_version to all TensorFlowModel examples
+ * Move RecordSerializer and RecordDeserializer to sagemaker.serializers and sagemaker.deserialzers
+
 ## v2.239.1 (2025-02-14)
 
 ### Bug Fixes and Other Changes

CONTRIBUTING.md

@@ -61,6 +61,10 @@ Before sending us a pull request, please ensure that:
    1. Follow the instructions at [Modifying an EBS Volume Using Elastic Volumes (Console)](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/requesting-ebs-volume-modifications.html#modify-ebs-volume) to increase the EBS volume size associated with the newly created EC2 instance.
    1. Wait 5-10min for the new EBS volume increase to finalize.
    1. Allow EC2 to claim the additional space by stopping and then starting your EC2 host.
+2. Set up a venv to manage dependencies:
+   1. `python -m venv ~/.venv/myproject-env` to create the venv
+   2. `source ~/.venv/myproject-env/bin/activate` to activate the venv
+   3. `deactivate` to exit the venv
 
 
 ### Pull Down the Code
@@ -74,8 +78,8 @@ Before sending us a pull request, please ensure that:
 ### Run the Unit Tests
 
 1. Install tox using `pip install tox`
-1. Install coverage using `pip install .[test]`
-1. cd into the sagemaker-python-sdk folder: `cd sagemaker-python-sdk` or `cd /environment/sagemaker-python-sdk`
+1. cd into the github project sagemaker-python-sdk folder: `cd sagemaker-python-sdk` or `cd /environment/sagemaker-python-sdk`
+1. Install coverage using `pip install '.[test]'`
 1. Run the following tox command and verify that all code checks and unit tests pass: `tox tests/unit`
 1. You can also run a single test with the following command: `tox -e py310 -- -s -vv <path_to_file><file_name>::<test_function_name>`
 1. You can run coverage via runcvoerage env : `tox -e runcoverage -- tests/unit` or `tox -e py310 -- tests/unit --cov=sagemaker --cov-append --cov-report xml`

VERSION

@@ -1 +1 @@
-2.239.2.dev0
+2.239.3.dev0

doc/frameworks/pytorch/using_pytorch.rst

@@ -375,6 +375,9 @@ To initialize distributed training in your script, call
 `torch.distributed.init_process_group
 <https://pytorch.org/docs/master/distributed.html#torch.distributed.init_process_group>`_
 with the desired backend and the rank of the current host.
+Warning: Some torch features, such as (and likely not limited to) ``torch.nn.SyncBatchNorm``
+is not supported and its existence in ``init_process_group`` will cause an exception during
+distributed training.
 
 .. code:: python