code: def bfloat16_activations_var_getter(getter, *args, **kwargs):
    
    requested_dtype = kwargs["dtype"]
    if requested_dtype == tf.bfloat16:
      kwargs["dtype"] = tf.float32
    var = getter(*args, **kwargs)
    # This if statement is needed to guard the cast, because batch norm
    # assigns directly to the return value of this custom getter. The cast
    # makes the return value not a variable so it cannot be assigned. Batch
    # norm variables are always in fp32 so this if statement is never
    # triggered for them.
    if var.dtype.base_dtype != requested_dtype:
      var = tf.cast(var, requested_dtype)
    return var
docs: A custom getter function for float32 parameters and bfloat16 activations.
  
    Args:
      getter: custom getter
      *args: arguments
      **kwargs: keyword arguments
    Returns:
      variables with the correct dtype.
    Raises:
      KeyError: if "dtype" is not provided as a kwarg.