mixed_precision=bfloatPolicy)

You can mix and match the precision for parameters, gradients and buffers as you prefer:

```python
comboPolicy = MixedPrecision(
        # Param precision
        param_dtype=torch.bfloat16,
        # Gradient communication precision.
        reduce_dtype=torch.float32,
        # Buffer precision.
        buffer_dtype=torch.float32,
    )

For training with FP16, you will need to also use the ShardedGradScaler, which we will cover in subsequent posts. For BFloat16, it is a drop-in replacement.
AnyPrecision Optimizer - going beyond mixed precision with full BF16 training