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Add input_size validation for RNN modules with clear error messages #166302
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/166302
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit e22e1db with merge base 6b25a63 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
test/test_nn.py
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| with self.assertRaisesRegex(ValueError, error_msg): | ||
| rnn = getattr(nn, mode)(30, 20, 2, proj_size=10) | ||
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| def test_rnn_invalid_input_size_and_hidden_size(self): |
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@pytorchbot rebase |
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@pytorchbot rebase |
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@pytorchbot rebase |
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@pytorchbot started a rebase job onto refs/remotes/origin/viable/strict. Check the current status here |
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@pytorchbot rebase -b main |
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mikaylagawarecki
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Thanks
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@pytorchbot merge |
Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
Merge failedReason: 1 jobs have failed, first few of them are: trunk / linux-jammy-cuda12.8-py3.10-gcc11-no-ops / build Details for Dev Infra teamRaised by workflow job |
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@pytorchbot merge -r |
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@pytorchbot started a rebase job onto refs/remotes/origin/viable/strict. Check the current status here |
Validates that input_size is an int > 0, providing clear TypeError/ValueError instead of cryptic torch.empty() errors. Applies to nn.RNN, nn.LSTM, nn.GRU. Tests added via ErrorModuleInput in module_error_inputs_torch_nn_RNN_GRU() in common_modules.py for comprehensive validation coverage. Fixes pytorch#136936
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Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
Merge failedReason: 3 mandatory check(s) failed. The first few are: Dig deeper by viewing the failures on hud |
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@pytorchbot merge |
Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
Validates that input_size is an int > 0, providing clear TypeError/ValueError instead of cryptic torch.empty() errors. Applies to nn.RNN, nn.LSTM, nn.GRU.
Fixes #136936