AWS sagemaker documentation change

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

File: sagemaker/latest/dg/model-parallel-extended-features-pytorch-tensor-parallelism-examples.md

Summary

Removed SageMaker Python SDK v2 (Legacy) code examples for tensor parallelism configurations and estimator setups.

Security assessment

Changes involve removing outdated SDK examples without modifying security-related content. No security vulnerabilities, configurations, or security features are mentioned in the removed sections.

Diff

diff --git a/sagemaker/latest/dg/model-parallel-extended-features-pytorch-tensor-parallelism-examples.md b/sagemaker/latest/dg/model-parallel-extended-features-pytorch-tensor-parallelism-examples.md
index bcda5c9cb..7cee128d5 100644
--- a//sagemaker/latest/dg/model-parallel-extended-features-pytorch-tensor-parallelism-examples.md
+++ b//sagemaker/latest/dg/model-parallel-extended-features-pytorch-tensor-parallelism-examples.md
@@ -41,3 +40,0 @@ Extended memory-saving features are available through Deep Learning Containers f
-SageMaker Python SDK v3
-    
-    
@@ -94,37 +90,0 @@ SageMaker Python SDK v3
-SageMaker Python SDK v2 (Legacy)
-    
-    
-    
-    mpi_options = {
-        "enabled" : True,
-        "processes_per_host" : 8,               # 8 processes
-        "custom_mpi_options" : "--mca btl_vader_single_copy_mechanism none "
-    }
-                   
-    smp_options = {
-        "enabled":True,
-        "parameters": {
-            "pipeline_parallel_degree": 1,    # alias for "partitions"
-            "placement_strategy": "cluster",
-            **"tensor_parallel_degree": 4** ,      # tp over 4 devices
-            "ddp": True
-        }
-    }
-                  
-    smp_estimator = PyTorch(
-        entry_point='your_training_script.py', # Specify
-        role=role,
-        instance_type='ml.p3.16xlarge',
-        sagemaker_session=sagemaker_session,
-        framework_version='1.13.1',
-        py_version='py36',
-        instance_count=1,
-        distribution={
-            "smdistributed": {"modelparallel": smp_options},
-            "mpi": mpi_options
-        },
-        base_job_name="SMD-MP-demo",
-    )
-    
-    smp_estimator.fit('s3://my_bucket/my_training_data/')
-
@@ -230,3 +189,0 @@ Extended memory-saving features are available through Deep Learning Containers f
-SageMaker Python SDK v3
-    
-    
@@ -281,38 +237,0 @@ SageMaker Python SDK v3
-SageMaker Python SDK v2 (Legacy)
-    
-    
-    
-    mpi_options = {
-        "enabled" : True,
-        "processes_per_host" : 8,               # 8 processes
-        "custom_mpi_options" : "--mca btl_vader_single_copy_mechanism none "
-    }
-                   
-    smp_options = {
-        "enabled":True,
-        "parameters": {
-        "microbatches": 4,
-            "pipeline_parallel_degree": 2,    # alias for "partitions"
-            "placement_strategy": "cluster",
-            "tensor_parallel_degree": 2,      # tp over 2 devices
-            "ddp": True
-        }
-    }
-                  
-    smp_estimator = PyTorch(
-        entry_point='your_training_script.py', # Specify
-        role=role,
-        instance_type='ml.p3.16xlarge',
-        sagemaker_session=sagemaker_session,
-        framework_version='1.13.1',
-        py_version='py36',
-        instance_count=1,
-        distribution={
-            "smdistributed": {"modelparallel": smp_options},
-            "mpi": mpi_options
-        },
-        base_job_name="SMD-MP-demo",
-    )
-    
-    smp_estimator.fit('s3://my_bucket/my_training_data/')  
-