Your question is Mixed Precision Training. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
Explain mixed precision training and its benefits.
Provide a practical explanation covering FP16, BF16, and FP32; automatic mixed precision; gradient scaling; numerical stability; and when mixed precision may be inappropriate. Include production-quality Python code that demonstrates a training loop using PyTorch automatic mixed precision, plus an evaluation plan comparing accuracy, memory usage, and throughput with full FP32 training.