Google Cloud Professional Machine Learning Engineer — Question 307
You need to train a ControlNet model with Stable Diffusion XL for an image editing use case. You want to train this model as quickly as possible. Which hardware configuration should you choose to train your model?
Answer options
- A. Configure one a2-highgpu-1g instance with an NVIDIA A100 GPU with 80 GB of RAM. Use float32 precision during model training.
- B. Configure one a2-highgpu-1g instance with an NVIDIA A100 GPU with 80 GB of RAM. Use bfloat16 quantization during model training.
- C. Configure four n1-standard-16 instances, each with one NVIDIA Tesla T4 GPU with 16 GB of RAM. Use float32 precision during model training.
- D. Configure four n1-standard-16 instances, each with one NVIDIA Tesla T4 GPU with 16 GB of RAM. Use floar16 quantization during model training.
Correct answer: B
Explanation
The correct answer is B because using bfloat16 quantization with the NVIDIA A100 GPU allows for faster training while maintaining the necessary precision for the model. Options A, C, and D either use a less efficient quantization method or insufficient hardware, leading to slower training times.