Record the lazy tracing time(C++) in metrics #5757
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wonjoolee95
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Nov 2, 2023
|
hmm, not sure I can rerun the CI once upstream thing merged |
alanwaketan
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Nov 14, 2023
| t1 = torch.tensor(156, device=xla_device) | ||
| t2 = t1 + 100 | ||
| self.assertIn('LazyTracing', met.metric_names()) | ||
| self.assertGreater(met.metric_data('LazyTracing')[0], 1) |
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So the op counter will still be int? But adding another LazyTracing metrics?
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* Record the lazy tracing time(C++) in metrics * Delete torch_patches/.torch_pin
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* Record the lazy tracing time(C++) in metrics * Delete torch_patches/.torch_pin
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* Record the lazy tracing time(C++) in metrics * Delete torch_patches/.torch_pin
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* Record the lazy tracing time(C++) in metrics * Delete torch_patches/.torch_pin
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* Record the lazy tracing time(C++) in metrics * Delete torch_patches/.torch_pin
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* Record the lazy tracing time(C++) in metrics * Delete torch_patches/.torch_pin
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This way we at least know how long it takes to trace the op in C++ PyTorch/XLA land.
upstream pr pytorch/pytorch#112679 (comment)