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Google Cloud Certified Professional Machine Learning Engineer · Google Cloud
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All options except D will impact the model accuracy
Configuring bfloat16 instead of float32 (D): This offers a good balance between speed, memory usage, and minimal code changes. Bfloat16 uses 16 bits per float value compared to 32 bits for float32. pen_spark expand_more This can significantly reduce memory usage while maintaining similar accuracy in many machine learning models, especially for image recognition tasks.expand_more It's a quick change with minimal impact on the code and potentially large gains in training speed.
"the Google hardware team chose bfloat16 for Cloud TPUs to improve hardware efficiency while maintaining the ability to train deep learning models accurately, all with minimal switching costs from float32"