### What changes were proposed in this pull request?
1, when `predictionCol` and `quantilesCol` are both set, we only need one prediction for each row: prediction is just the variable `lambda` in `predictQuantiles`;
2, in the computation of variable `quantiles` in `predictQuantiles`, a pre-computed vector `val baseQuantiles = $(quantileProbabilities).map(q => math.exp(math.log(-math.log1p(-q)) * scale))` can be reused for each row;
### Why are the changes needed?
avoid redundant computation in transform, like what we did in `ProbabilisticClassificationModel`, `GaussianMixtureModel`, etc
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
existing testsuite
Closes#30000 from zhengruifeng/aft_predict_transform_opt.
Authored-by: zhengruifeng <ruifengz@foxmail.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
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