[benchmark] Legacy factor

This adds optional `legacyFactor` to the `BenchmarkInfo`, which allows for linear modification of constants that unnecesarily inflate the base workload of benchmarks, while maintaining the continuity of log-term benchmark tracking.

For example, if a benchmark uses `for _ in N*10_000` in its run function, we could lower this to `for _ in N*1_000` and adding a `legacyFactor: 10` to its `BenchmarkInfo`.

Note that this doesn’t affect the real measurements gathered from the `--verbose` output. The `BenchmarkDoctor` has been slightly adjusted to work with these real samples, therefore `Benchmark_Driver check` will not flag these benchmarks for slow run time reported in the summary, if their real runtimes fall into the recommended range.

benchmark/scripts/test_Benchmark_Driver.py

@@ -423,7 +423,7 @@ class TestLoggingReportFormatter(unittest.TestCase):
 
 def _PTR(min=700, mem_pages=1000, setup=None):
     """Create PerformanceTestResult Stub."""
-    return Stub(min=min, mem_pages=mem_pages, setup=setup)
+    return Stub(samples=Stub(min=min), mem_pages=mem_pages, setup=setup)
 
 
 def _run(test, num_samples=None, num_iters=None, verbose=None,
@@ -483,7 +483,8 @@ class TestBenchmarkDoctor(unittest.TestCase):
         """
         driver = BenchmarkDriverMock(tests=['B1'], responses=([
             # calibration run, returns a stand-in for PerformanceTestResult
-            (_run('B1', num_samples=3, num_iters=1), _PTR(min=300))] +
+            (_run('B1', num_samples=3, num_iters=1,
+                  verbose=True), _PTR(min=300))] +
             # 5x i1 series, with 300 μs runtime its possible to take 4098
             # samples/s, but it should be capped at 2k
             ([(_run('B1', num_samples=2048, num_iters=1,