Google Professional Machine Learning Engineer
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You are training an object detection model using a Cloud TPU v2 in a project with tight budget constraints and a deadline approaching. The training process is taking significantly longer than expected, and initial profiling indicates that the input data processing is a bottleneck. You need to implement a cost-effective solution that reduces training time without requiring expensive hardware upgrades. Which of the following measures would be the BEST to address this issue? (Choose one)
Explanation:
The correct answer is to adjust the input function to enable parallel reads, parallel processing, and prefetch. This approach is cost-effective because it addresses the bottleneck in the data processing pipeline without the need for more expensive hardware upgrades. By optimizing the data pipeline, the model can be trained more efficiently, significantly reducing the training time while staying within budget constraints.