Question 245 of 1,672
MLS-C01 Modeling Practice Question
A team is training a deep learning model on SageMaker using a custom Docker container. The training job fails with 'OutOfMemoryError'. The instance type is ml.p3.2xlarge with 61 GB memory. Which change should increase available memory?
⚠ Common exam trap
The MLS-C01 exam often tests the misconception that 'OutOfMemoryError' always refers to GPU memory, leading candidates to choose batch size reduction, when in SageMaker containers it frequently indicates insufficient shared memory for data-loading processes.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Set the 'shm-size' parameter in the SageMaker training container to a larger value.
The 'OutOfMemoryError' in a SageMaker training container often stems from insufficient shared memory (/dev/shm) for data-loading workers, especially with PyTorch or TensorFlow dataloaders that use multiprocessing. Increasing the 'shm-size' parameter allocates more shared memory to the container, resolving the error without altering the model or instance type.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Reduce the batch size to use less memory.
Why it's wrong here
Reducing batch size lowers memory consumption but does not increase available memory.
- ✗
Use SageMaker distributed data parallelism to distribute the model across multiple instances.
Why it's wrong here
Distributed training spreads the workload but does not increase the memory of each individual instance.
- ✓
Set the 'shm-size' parameter in the SageMaker training container to a larger value.
Why this is correct
Increasing shared memory (/dev/shm) can resolve OutOfMemory errors in deep learning frameworks.
- ✗
Mount an Amazon FSx for Lustre file system to offload data.
Why it's wrong here
FSx for Lustre provides high-performance storage, not additional memory.
Visual reference
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Last reviewed: Jun 24, 2026
This MLS-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the MLS-C01 exam.
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