Exam Professional Machine Learning Engineer topic 1 question 314 discussion

Actual exam question from Google's Professional Machine Learning Engineer

Question #: 314
Topic #: 1

[All Professional Machine Learning Engineer Questions]

You are training a large-scale deep learning model on a Cloud TPU. While monitoring the training progress through Tensorboard, you observe that the TPU utilization is consistently low and there are delays between the completion of one training step and the start of the next step. You want to improve TPU utilization and overall training performance. How should you address this issue?

A. Apply tf.data.Detaset.map with vectorized operations and parallelization.
B. Use tf.data.Detaset.interleave with multiple data sources.
C. Use tf.data.Detaset.cache on the dataset after the first epoch.
D. Implement tf.data.Detaset.prefetch in the data pipeline.

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Suggested Answer: D 🗳️

by hit_cloudie at May 21, 2025, 8:53 a.m.

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hit_cloudie

4 weeks, 1 day ago

Selected Answer: D

tf.data.Dataset.prefetch in the pipeline ✅ Correct — prefetch() overlaps data preprocessing with model execution, ensuring the next batch is prepared while the current batch is being processed, thus maximizing TPU utilization and minimizing idle time.

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