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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def masked_max(vector: torch.Tensor, mask: torch.Tensor, dim: int, keepdim: bool = False, min_val: float = -1e7) -> torch.Tensor: """ To calculate max along certain dimensions on masked values Parameters vector : ``torch.Tensor`` The vector to calculate max, assume unmasked parts are already zeros mask : ``torch.Tensor`` The mask of the vector. It must be broadcastable with vector. dim : ``int`` The dimension to calculate max keepdim : ``bool`` Whether to keep dimension min_val : ``float`` The minimal value for paddings Returns ------- A ``torch.Tensor`` of including the maximum values. """

    one_minus_mask = (1.0 - mask).byte()
    replaced_vector = vector.masked_fill(one_minus_mask, min_val)
    max_value, _ = replaced_vector.max(dim=dim, keepdim=keepdim)
    return max_value