octoJon commented on code in PR #12284:
URL: https://github.com/apache/tvm/pull/12284#discussion_r936918746
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tests/python/topi/python/test_topi_prng.py:
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@@ -157,8 +185,27 @@ def test_uniform(target, dev):
assert np.max(rands) <= 10.0
+@tvm.testing.parametrize_targets
+def test_multinomial(target, dev):
+ def _verify_multinomial(size, num_samples):
Review Comment:
You could generate a "large" sample of at least 10,000 values and then use a
chi-squared test (scipy.stats.chisquare). You'd look at the p-value from that
chi-squared test and compare it to an acceptably low threshold for flakiness --
for example, have this unit test fail if the p-value is smaller than 1e-6,
which should only happen by chance in one run per million.
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