AI0-001 AI Implementation and Operations Practice Question
Exhibit
Refer to the exhibit. Error: RuntimeError: CUDA out of memory. Tried to allocate 2.00 GiB (GPU 0; 8.00 GiB total capacity; 6.50 GiB already allocated; 1.50 GiB free; 0 bytes cached) at /workspace/training.py:345
Based on the exhibit, which action is most likely to resolve the memory issue?
⚠ Common exam trap
CompTIA often tests the misconception that memory errors are solved by adding more data or changing hardware, when in fact the simplest and most common fix is adjusting the batch size to fit within available GPU memory.
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
✓
Reduce the batch size.
The exhibit shows an out-of-memory (OOM) error during training. Reducing the batch size decreases the memory footprint per iteration, allowing the model to fit within available GPU memory. This directly resolves the memory issue without altering the model architecture or data.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Add more training data.
Why it's wrong here
Adding data increases memory requirements and would worsen the error.
- ✗
Increase the learning rate.
Why it's wrong here
Learning rate does not affect memory usage.
- ✗
Switch to a CPU.
Why it's wrong here
CPU may still run out of memory if the problem is not addressed, and training would be slower.
- ✓
Reduce the batch size.
Why this is correct
Smaller batches reduce the memory allocated for intermediate tensors.
Visual reference
About these practice questions
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI0-001 practice question is part of Courseiva's free CompTIA 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 AI0-001 exam.