code: def replace_masked_values(tensor: torch.Tensor, mask: torch.Tensor, replace_with: float) -> torch.Tensor:
      
      if tensor.dim() != mask.dim():
          raise ConfigurationError("tensor.dim() (%d) != mask.dim() (%d)" % (tensor.dim(), mask.dim()))
      return tensor.masked_fill((1 - mask).byte(), replace_with)
docs: Replaces all masked values in ``tensor`` with ``replace_with``.  ``mask`` must be broadcastable
      to the same shape as ``tensor``. We require that ``tensor.dim() == mask.dim()``, as otherwise we
      won't know which dimensions of the mask to unsqueeze.
  
      This just does ``tensor.masked_fill()``, except the pytorch method fills in things with a mask
      value of 1, where we want the opposite.  You can do this in your own code with
      ``tensor.masked_fill((1 - mask).byte(), replace_with)``.