AWS sagemaker documentation change

Service: sagemaker · 2026-07-01 · Documentation low

File: sagemaker/latest/dg/augmented-manifest.md

Summary

Removed legacy SageMaker Python SDK v2 code examples and empty section headers for SDK v3

Security assessment

Changes consist of deleting deprecated SDK implementation examples. No security fixes, vulnerability patches, or security documentation additions detected.

Diff

diff --git a/sagemaker/latest/dg/augmented-manifest.md b/sagemaker/latest/dg/augmented-manifest.md
index e69fa9d65..b8c690844 100644
--- a//sagemaker/latest/dg/augmented-manifest.md
+++ b//sagemaker/latest/dg/augmented-manifest.md
@@ -136,3 +135,0 @@ The following shows how to train a model with an augmented manifest file using t
-SageMaker Python SDK v3
-    
-    
@@ -181,35 +177,0 @@ SageMaker Python SDK v3
-SageMaker Python SDK v2 (Legacy)
-    
-    
-    
-    import sagemaker
-    
-    # Create a model object set to using "Pipe" mode.
-    model = sagemaker.estimator.Estimator(
-        training_image,
-        role,
-        instance_count=1,
-        instance_type='ml.p3.2xlarge',
-        volume_size = 50,
-        max_run = 360000,
-        input_mode = 'Pipe',
-        output_path=s3_output_location,
-        sagemaker_session=session
-    )
-    
-    # Create a train data channel with S3_data_type as 'AugmentedManifestFile' and attribute names.
-    train_data = sagemaker.inputs.TrainingInput(
-        your_augmented_manifest_file,
-        distribution='FullyReplicated',
-        content_type='application/x-recordio',
-        s3_data_type='AugmentedManifestFile',
-        attribute_names=['source-ref', 'annotations'],
-        input_mode='Pipe',
-        record_wrapping='RecordIO'
-    )
-    
-    data_channels = {'train': train_data}
-    
-    # Train a model.
-    model.fit(inputs=data_channels, logs=True)
-