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PMLE Practice Question: A team has trained a sentiment analysis model…

A team has trained a sentiment analysis model using PyTorch on Vertex AI Training. They now want to deploy it for online predictions with low latency. Which TWO actions should they take? (Choose 2)

⚠ Common exam trap

Google Cloud often tests the misconception that converting to TensorFlow SavedModel is required for Vertex AI, but the platform supports PyTorch natively via custom containers, making conversion an unnecessary and potentially error-prone step.

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

Use a machine type with a GPU for faster inference.

GPU-accelerated inference significantly reduces latency for deep learning models like sentiment analysis, especially when using PyTorch, which has native CUDA support. Vertex AI Prediction supports GPU machine types (e.g., n1-standard-4 with NVIDIA T4) that can process batched requests faster than CPUs, directly addressing the low-latency requirement.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Create multiple model versions for A/B testing.

    Why it's wrong here

    A/B testing is for evaluation, not low latency.

  • Use a machine type with a GPU for faster inference.

    Why this is correct

    GPUs can accelerate inference for deep learning models.

  • Enable batch prediction instead of online prediction.

    Why it's wrong here

    Batch prediction is for high throughput, not low latency.

  • Convert the model to TensorFlow SavedModel format.

    Why it's wrong here

    Conversion is not necessary; PyTorch can be deployed as is.

  • Package the model in a custom container with a web server (e.g., FastAPI).

    Why this is correct

    Custom containers allow deploying PyTorch models on Vertex AI.

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JA

Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This PMLE practice question is part of Courseiva's free Google Cloud 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 PMLE exam.