Efficient Cumulative Product on Gorgonia Tensors in Go?

Question

I'm trying to find the best way to fund the cumulative product of a Gorgonia Tensor. For example:

T := ts.New(ts.WithShape(3,4), ts.WithBacking(ts.Range(ts.Float32,1,13)))
    for row := 1; row < 3; row++ {
        for col :=0; col < 4; col++ {
            val1, _ := T.At(row-1, col).(float32)
            val2, _ := T.At(row, col).(float32)
            newVal := val1*val2
            T.SetAt(newVal, row, col)
        }
    }

I want the output to be:

[1   2    3    4  ]
[5   12   21   32 ]
[45  120  231  384]

This works, but for modest sized tensors (500x50), it takes 2500 microseconds seconds per iteration. I need it to be much faster. The numpy .cumprod() takes about 10-20 microseconds for a similar computation. Is there a more efficient way to code this?

I'm using tensors because I need to do matrix multiplication, and I want to use float32 for memory constraints. If necessary, I could switch it to gonum matrices, but I would rather not have to spend the extra memory if there is a way to do it with float32.