Fix MultiNodeWeightedSampler tests #1426
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/data/1426
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 029221d with merge base daafee4 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
ramanishsingh
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divyanshk
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divyanshk
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divyanshk
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divyanshk
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| @@ -86,13 +87,15 @@ def test_multi_node_weighted_batch_sampler_zero_weights( | |||
| weights={f"ds{i}": 10 * i for i in range(self._num_datasets)}, | |||
| ) | |||
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| def test_multi_node_weighted_sampler_first_exhausted(self) -> None: | |||
| @parameterized.expand(range(10)) | |||
| def test_multi_node_weighted_sampler_first_exhausted(self, seed) -> None: | |||
| """Test MultiNodeWeightedSampler with stop criteria FIRST_DATASET_EXHAUSTED""" | |||
| mixer = self._setup_multi_node_weighted_sampler( | |||
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one tiny nit: can you make this node = self._setup_multi_node_weighted_sampler( here as well as in other places we call _setup_multi_node_weighted_sampler, thanks!
divyanshk
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Due to the stochastic nature of the MultiNodeWeightedSampler and the way StopIteration is called when multiple datasets are involved, some test results are dependent on the OS/seed. Trying to fix seed and change testing conditions with this PR.