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documentation: update framework version links (#4178)
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src/sagemaker/chainer/estimator.py

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@@ -108,7 +108,7 @@ def __init__(
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framework_version (str): Chainer version you want to use for
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executing your model training code. Defaults to ``None``. Required unless
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``image_uri`` is provided. List of supported versions:
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https://github.com/aws/sagemaker-python-sdk#chainer-sagemaker-estimators.
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https://sagemaker.readthedocs.io/en/stable/frameworks/chainer/using_chainer.html#using-chainer-with-the-sagemaker-python-sdk.
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image_uri (str): If specified, the estimator will use this image
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for training and hosting, instead of selecting the appropriate
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SageMaker official image based on framework_version and

src/sagemaker/huggingface/model.py

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@@ -138,12 +138,10 @@ def __init__(
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unless ``image_uri`` is provided.
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tensorflow_version (str): TensorFlow version you want to use for
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executing your inference code. Defaults to ``None``. Required unless
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``pytorch_version`` is provided. List of supported versions:
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https://github.com/aws/sagemaker-python-sdk#huggingface-sagemaker-estimators.
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``pytorch_version`` is provided. The current supported version is ``2.4.1``.
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pytorch_version (str): PyTorch version you want to use for
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executing your inference code. Defaults to ``None``. Required unless
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``tensorflow_version`` is provided. List of supported versions:
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https://github.com/aws/sagemaker-python-sdk#huggingface-sagemaker-estimators.
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``tensorflow_version`` is provided. The current supported versions are ``1.7.1`` and ``1.6.0``.
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py_version (str): Python version you want to use for executing your
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model training code. Defaults to ``None``. Required unless
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``image_uri`` is provided.

src/sagemaker/mxnet/estimator.py

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@@ -77,7 +77,7 @@ def __init__(
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framework_version (str): MXNet version you want to use for executing
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your model training code. Defaults to `None`. Required unless
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``image_uri`` is provided. List of supported versions.
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https://github.com/aws/sagemaker-python-sdk#mxnet-sagemaker-estimators.
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https://aws.amazon.com/releasenotes/available-deep-learning-containers-images/.
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py_version (str): Python version you want to use for executing your
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model training code. One of 'py2' or 'py3'. Defaults to ``None``. Required
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unless ``image_uri`` is provided.

src/sagemaker/sklearn/estimator.py

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@@ -75,7 +75,7 @@ def __init__(
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framework_version (str): Scikit-learn version you want to use for
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executing your model training code. Defaults to ``None``. Required
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unless ``image_uri`` is provided. List of supported versions:
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https://github.com/aws/sagemaker-python-sdk#sklearn-sagemaker-estimators
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https://docs.aws.amazon.com/sagemaker/latest/dg/sklearn.html
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py_version (str): Python version you want to use for executing your
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model training code (default: 'py3'). Currently, 'py3' is the only
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supported version. If ``None`` is passed in, ``image_uri`` must be

src/sagemaker/tensorflow/estimator.py

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@@ -59,7 +59,7 @@ def __init__(
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framework_version (str): TensorFlow version you want to use for executing your model
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training code. Defaults to ``None``. Required unless ``image_uri`` is provided.
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List of supported versions:
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https://github.com/aws/sagemaker-python-sdk#tensorflow-sagemaker-estimators.
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https://aws.amazon.com/releasenotes/available-deep-learning-containers-images/.
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model_dir (str or PipelineVariable): S3 location where the checkpoint data and models
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can be exported to during training (default: None). It will be passed in the
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training script as one of the command line arguments. If not specified,

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