log ViewAndMutationMeta to trace_structured#133784
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bdhirsh wants to merge 13 commits intogh/bdhirsh/609/basefrom
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log ViewAndMutationMeta to trace_structured#133784bdhirsh wants to merge 13 commits intogh/bdhirsh/609/basefrom
bdhirsh wants to merge 13 commits intogh/bdhirsh/609/basefrom
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/133784
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit c1b7c35 with merge base 4470339 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
ezyang
reviewed
Aug 19, 2024
| payload_fn=lambda: fw_module.print_readable( | ||
| print_output=False, include_stride=True, include_device=True | ||
| ), | ||
| payload_fn=lambda: fw_metadata_str, |
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This doesn't do what you want, payload_fn=fw_metadata_str
Have you inspected the output tlparse yet?
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Oh it looks like you didn't exercise this one
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whoops... thank you
ezyang
reviewed
Aug 19, 2024
| print_output=False, include_stride=True, include_device=True | ||
| ), | ||
| ] | ||
| ) |
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Why put these together? Just output them as separate log entries. If you don't want to have to modify tlparse cli, dump the fw metadata as "artifact"
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you're completely right - I didn't realize that dumping using "artifact" allows us to add new artifacts without needing to change the tlparse cli. updated
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nit: I think the dumped structures would be substantially easier to understand if they were indented. There are two ways you could do this: dump as JSON, or use torchgen's dump dataclass with indentation utility |
I ended up bundling it into the existing tlparse logs for the AOT forward graph, since it looked like registering it as a separate artifact requires changes to tlparse itself (maybe that is wrong though?) Example new fw AOT graph tlparse output for the below code: https://interncache-all.fbcdn.net/manifold/tlparse_reports/tree/logs/.tmp70zKiO/0_0_0/aot_forward_graph_2.txt ``` import torch torch.compile def f(x): out1 = torch.view_as_complex(x) out2 = torch.view_as_complex(x) return out1, out2, x * 2 x_ = torch.randn(4, 2, requires_grad=True, dtype=torch.float64) out = f(x_) ``` [ghstack-poisoned]
I ended up bundling it into the existing tlparse logs for the AOT forward graph, since it looked like registering it as a separate artifact requires changes to tlparse itself (maybe that is wrong though?) Example new fw AOT graph tlparse output for the below code: https://interncache-all.fbcdn.net/manifold/tlparse_reports/tree/logs/.tmp70zKiO/0_0_0/aot_forward_graph_2.txt ``` import torch torch.compile def f(x): out1 = torch.view_as_complex(x) out2 = torch.view_as_complex(x) return out1, out2, x * 2 x_ = torch.randn(4, 2, requires_grad=True, dtype=torch.float64) out = f(x_) ``` [ghstack-poisoned]
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Just updated to use (I also locally exercised all four paths of inference/training, subclasses/no_subclasses) |
ezyang
approved these changes
Aug 22, 2024
I ended up bundling it into the existing tlparse logs for the AOT forward graph, since it looked like registering it as a separate artifact requires changes to tlparse itself (maybe that is wrong though?) Example new fw AOT graph tlparse output for the below code: https://interncache-all.fbcdn.net/manifold/tlparse_reports/tree/logs/.tmp70zKiO/0_0_0/aot_forward_graph_2.txt ``` import torch torch.compile def f(x): out1 = torch.view_as_complex(x) out2 = torch.view_as_complex(x) return out1, out2, x * 2 x_ = torch.randn(4, 2, requires_grad=True, dtype=torch.float64) out = f(x_) ``` [ghstack-poisoned]
I ended up bundling it into the existing tlparse logs for the AOT forward graph, since it looked like registering it as a separate artifact requires changes to tlparse itself (maybe that is wrong though?) Example new fw AOT graph tlparse output for the below code: https://interncache-all.fbcdn.net/manifold/tlparse_reports/tree/logs/.tmp70zKiO/0_0_0/aot_forward_graph_2.txt ``` import torch torch.compile def f(x): out1 = torch.view_as_complex(x) out2 = torch.view_as_complex(x) return out1, out2, x * 2 x_ = torch.randn(4, 2, requires_grad=True, dtype=torch.float64) out = f(x_) ``` [ghstack-poisoned]
I ended up bundling it into the existing tlparse logs for the AOT forward graph, since it looked like registering it as a separate artifact requires changes to tlparse itself (maybe that is wrong though?) Example new fw AOT graph tlparse output for the below code: https://interncache-all.fbcdn.net/manifold/tlparse_reports/tree/logs/.tmp70zKiO/0_0_0/aot_forward_graph_2.txt ``` import torch torch.compile def f(x): out1 = torch.view_as_complex(x) out2 = torch.view_as_complex(x) return out1, out2, x * 2 x_ = torch.randn(4, 2, requires_grad=True, dtype=torch.float64) out = f(x_) ``` [ghstack-poisoned]
I ended up bundling it into the existing tlparse logs for the AOT forward graph, since it looked like registering it as a separate artifact requires changes to tlparse itself (maybe that is wrong though?) Example new fw AOT graph tlparse output for the below code: https://interncache-all.fbcdn.net/manifold/tlparse_reports/tree/logs/.tmp70zKiO/0_0_0/aot_forward_graph_2.txt ``` import torch torch.compile def f(x): out1 = torch.view_as_complex(x) out2 = torch.view_as_complex(x) return out1, out2, x * 2 x_ = torch.randn(4, 2, requires_grad=True, dtype=torch.float64) out = f(x_) ``` cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv jiayisunx chenyang78 kadeng chauhang amjames rec [ghstack-poisoned]
I ended up bundling it into the existing tlparse logs for the AOT forward graph, since it looked like registering it as a separate artifact requires changes to tlparse itself (maybe that is wrong though?) Example new fw AOT graph tlparse output for the below code: https://interncache-all.fbcdn.net/manifold/tlparse_reports/tree/logs/.tmp70zKiO/0_0_0/aot_forward_graph_2.txt ``` import torch torch.compile def f(x): out1 = torch.view_as_complex(x) out2 = torch.view_as_complex(x) return out1, out2, x * 2 x_ = torch.randn(4, 2, requires_grad=True, dtype=torch.float64) out = f(x_) ``` cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv jiayisunx chenyang78 kadeng chauhang amjames rec [ghstack-poisoned]
I ended up bundling it into the existing tlparse logs for the AOT forward graph, since it looked like registering it as a separate artifact requires changes to tlparse itself (maybe that is wrong though?) Example new fw AOT graph tlparse output for the below code: https://interncache-all.fbcdn.net/manifold/tlparse_reports/tree/logs/.tmp70zKiO/0_0_0/aot_forward_graph_2.txt ``` import torch torch.compile def f(x): out1 = torch.view_as_complex(x) out2 = torch.view_as_complex(x) return out1, out2, x * 2 x_ = torch.randn(4, 2, requires_grad=True, dtype=torch.float64) out = f(x_) ``` cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv jiayisunx chenyang78 kadeng chauhang amjames rec [ghstack-poisoned]
I ended up bundling it into the existing tlparse logs for the AOT forward graph, since it looked like registering it as a separate artifact requires changes to tlparse itself (maybe that is wrong though?) Example new fw AOT graph tlparse output for the below code: https://interncache-all.fbcdn.net/manifold/tlparse_reports/tree/logs/.tmp70zKiO/0_0_0/aot_forward_graph_2.txt ``` import torch torch.compile def f(x): out1 = torch.view_as_complex(x) out2 = torch.view_as_complex(x) return out1, out2, x * 2 x_ = torch.randn(4, 2, requires_grad=True, dtype=torch.float64) out = f(x_) ``` cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv jiayisunx chenyang78 kadeng chauhang amjames rec [ghstack-poisoned]
I ended up bundling it into the existing tlparse logs for the AOT forward graph, since it looked like registering it as a separate artifact requires changes to tlparse itself (maybe that is wrong though?) Example new fw AOT graph tlparse output for the below code: https://interncache-all.fbcdn.net/manifold/tlparse_reports/tree/logs/.tmp70zKiO/0_0_0/aot_forward_graph_2.txt ``` import torch torch.compile def f(x): out1 = torch.view_as_complex(x) out2 = torch.view_as_complex(x) return out1, out2, x * 2 x_ = torch.randn(4, 2, requires_grad=True, dtype=torch.float64) out = f(x_) ``` cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv jiayisunx chenyang78 kadeng chauhang amjames rec [ghstack-poisoned]
I ended up bundling it into the existing tlparse logs for the AOT forward graph, since it looked like registering it as a separate artifact requires changes to tlparse itself (maybe that is wrong though?) Example new fw AOT graph tlparse output for the below code: https://interncache-all.fbcdn.net/manifold/tlparse_reports/tree/logs/.tmp70zKiO/0_0_0/aot_forward_graph_2.txt ``` import torch torch.compile def f(x): out1 = torch.view_as_complex(x) out2 = torch.view_as_complex(x) return out1, out2, x * 2 x_ = torch.randn(4, 2, requires_grad=True, dtype=torch.float64) out = f(x_) ``` cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv jiayisunx chenyang78 kadeng chauhang amjames rec [ghstack-poisoned]
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@pytorchbot merge |
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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 |
I ended up bundling it into the existing tlparse logs for the AOT forward graph, since it looked like registering it as a separate artifact requires changes to tlparse itself (maybe that is wrong though?) Example new fw AOT graph tlparse output for the below code: https://interncache-all.fbcdn.net/manifold/tlparse_reports/tree/logs/.tmp70zKiO/0_0_0/aot_forward_graph_2.txt ``` import torch torch.compile def f(x): out1 = torch.view_as_complex(x) out2 = torch.view_as_complex(x) return out1, out2, x * 2 x_ = torch.randn(4, 2, requires_grad=True, dtype=torch.float64) out = f(x_) ``` cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv jiayisunx chenyang78 kadeng chauhang amjames rec [ghstack-poisoned]
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Merge failedReason: New commits were pushed while merging. Please rerun the merge command. Details for Dev Infra teamRaised by workflow job |
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@pytorchbot merge |
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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 |
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The merge job was canceled or timed out. This most often happen if two merge requests were issued for the same PR, or if merge job was waiting for more than 6 hours for tests to finish. In later case, please do not hesitate to reissue the merge command |
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@pytorchbot merge |
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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 |
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I ended up bundling it into the existing tlparse logs for the AOT forward graph, since it looked like registering it as a separate artifact requires changes to tlparse itself (maybe that is wrong though?)
Example new fw AOT graph tlparse output for the below code: https://interncache-all.fbcdn.net/manifold/tlparse_reports/tree/logs/.tmp70zKiO/0_0_0/aot_forward_graph_2.txt
Stack from ghstack (oldest at bottom):
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng @chauhang @amjames @rec