AWS sagemaker documentation change

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

File: sagemaker/latest/dg/sagemaker-hyperpod-trainium-sagemaker-training-jobs-pretrain-tutorial.md

Summary

Removed SageMaker Python SDK v2 (Legacy) code examples and empty section headers

Security assessment

Removal of deprecated SDK examples doesn't indicate security fixes. No security context provided.

Diff

diff --git a/sagemaker/latest/dg/sagemaker-hyperpod-trainium-sagemaker-training-jobs-pretrain-tutorial.md b/sagemaker/latest/dg/sagemaker-hyperpod-trainium-sagemaker-training-jobs-pretrain-tutorial.md
index 81212c703..ba53db4b7 100644
--- a//sagemaker/latest/dg/sagemaker-hyperpod-trainium-sagemaker-training-jobs-pretrain-tutorial.md
+++ b//sagemaker/latest/dg/sagemaker-hyperpod-trainium-sagemaker-training-jobs-pretrain-tutorial.md
@@ -97,3 +96,0 @@ You can use the following Python code to run a SageMaker training job using your
-SageMaker Python SDK v3
-    
-    
@@ -150,47 +146,0 @@ SageMaker Python SDK v3
-SageMaker Python SDK v2 (Legacy)
-    
-    
-    
-    import os
-    import sagemaker,boto3
-    from sagemaker.debugger import TensorBoardOutputConfig
-    
-    from sagemaker.pytorch import PyTorch
-    
-    sagemaker_session = sagemaker.Session()
-    role = sagemaker.get_execution_role()
-    
-    recipe_overrides = {
-        "run": {
-            "results_dir": "/opt/ml/model",
-        },
-        "exp_manager": {
-            "explicit_log_dir": "/opt/ml/output/tensorboard",
-        },
-        "data": {
-            "train_dir": "/opt/ml/input/data/train",
-        },
-        "model": {
-            "model_config": "/opt/ml/input/data/train/config.json",
-        },
-        "compiler_cache_url": "<compiler_cache_url>"
-    } 
-    
-    tensorboard_output_config = TensorBoardOutputConfig(
-        s3_output_path=os.path.join(output, 'tensorboard'),
-        container_local_output_path=overrides["exp_manager"]["explicit_log_dir"]
-    )
-    
-    estimator = PyTorch(
-        output_path=output_path,
-        base_job_name=f"llama-trn",
-        role=role,
-        instance_type="ml.trn1.32xlarge",
-        sagemaker_session=sagemaker_session,
-        training_recipe="training/llama/hf_llama3_70b_seq8k_trn1x16_pretrain",
-        recipe_overrides=recipe_overrides,
-    )
-    
-    estimator.fit(inputs={"train": "your-inputs"}, wait=True)
-    
-