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Make metric unit tests both more powerful and less prone to false err…
…ors. - When learners are expected to be deterministic, check metric against golden value (instead of valid range). This is the default behavior for the internal build. - Make it possible to run test with random seed-values. This way, tests measure the learning variance from changing the random seed, or equivalently, use a different random number generator (e.g., same are going in the external build). In this case, metrics are tested again metric range. - All metric range have been re-computed by running all tests 1000 times + adding 50% margin. In many cases, the new range is tighter than it was before. - Remove non-deterministic in tests outside of the random seed (if the seed is not fixed). This significantly reduce the variance of the test results. PiperOrigin-RevId: 568194822
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yggdrasil_decision_forests/learner/gradient_boosted_trees/gradient_boosted_trees_test.cc
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