[export] ignore mark_dynamic() in export #135536

pianpwk · 2024-09-09T21:28:03Z

Previously we were accomodating torch._dynamo.mark_dynamic() for export's dynamic shapes. Here we clean things up and ignore it, requiring users to specify an export input for dynamic_shapes.

Note: there's 4 decorators relevant to export, mark_dynamic, maybe_mark_dynamic, mark_static, mark_unbacked. User calls that involve export have only been mark_dynamic(), and we use maybe_mark_dynamic under the hood for Dim.AUTO, but we could start using others. One reason I decided to not warn and just silently ignore is these decorators cause the tensors to carry dynamic info, and it'll be hard to tell whether the markers are from export or user calls when re-exporting with the same inputs.

cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang @rec

pytorch-bot · 2024-09-09T21:28:06Z

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facebook-github-bot · 2024-09-09T21:28:43Z

@pianpwk has imported this pull request. If you are a Meta employee, you can view this diff on Phabricator.

Summary: Fixes #ISSUE_NUMBER Differential Revision: D62404528 Pulled By: pianpwk

facebook-github-bot · 2024-09-10T00:19:10Z

This pull request was exported from Phabricator. Differential Revision: D62404528

Summary: Fixes #ISSUE_NUMBER Differential Revision: D62404528 Pulled By: pianpwk

facebook-github-bot · 2024-09-10T01:27:07Z

This pull request was exported from Phabricator. Differential Revision: D62404528

pianpwk · 2024-09-10T18:08:52Z

benchmarks/dynamo/common.py

                # see https://github.com/pytorch/pytorch/issues/113029
                example_outputs = copy.deepcopy(model)(*example_args, **example_kwargs)

+            def _produce_dynamic_shapes(path, x):


@desertfire tagging you for the AOTInductor changes in benchmarking

facebook-github-bot · 2024-09-10T18:09:26Z

@pianpwk has imported this pull request. If you are a Meta employee, you can view this diff on Phabricator.

avikchaudhuri · 2024-09-10T23:24:03Z

benchmarks/dynamo/common.py

+                # use this to produce dynamic_shapes spec instead.
+                if not isinstance(x, torch.Tensor):
+                    return None
+                return {


You sure you don't have to handle other markers?

In these tests I'm pretty sure it's only mark_dynamic that's used..

avikchaudhuri · 2024-09-10T23:25:45Z

benchmarks/dynamo/common.py

            else:
                _register_dataclass_output_as_pytree(example_outputs)

+            combined_args = tuple(example_args) + tuple(example_kwargs.values())


curious, no need to look at the model signature here?

That could be better if the kwargs are out of order, but I don't think that's happening here, so it's fine to just feed the shapes spec as a tuple. Will check with tests though..

avikchaudhuri · 2024-09-10T23:27:19Z

torch/export/dynamic_shapes.py

            for i, val in enumerate(tensor.shape):
                dim = shape.get(i, _DimHint.STATIC)
-                if _marked_dynamic(tensor, i) or dim == _DimHint.AUTO:
+                if dim == _DimHint.AUTO:


lol get rid of the dupe if

Summary: Previously we were accomodating `torch._dynamo.mark_dynamic()` for export's dynamic shapes. Here we clean things up and ignore it, requiring users to specify an export input for `dynamic_shapes`. Note: there's 4 decorators relevant to export, `mark_dynamic, maybe_mark_dynamic, mark_static, mark_unbacked`. User calls that involve export have only been `mark_dynamic()`, and we use `maybe_mark_dynamic` under the hood for `Dim.AUTO`, but we could start using others. One reason I decided to not warn and just silently ignore is these decorators cause the tensors to carry dynamic info, and it'll be hard to tell whether the markers are from export or user calls when re-exporting with the same inputs. cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv jiayisunx ipiszy yf225 chenyang78 kadeng muchulee8 ColinPeppler amjames desertfire chauhang rec Reviewed By: avikchaudhuri Differential Revision: D62404528 Pulled By: pianpwk

facebook-github-bot · 2024-09-11T02:40:35Z

This pull request was exported from Phabricator. Differential Revision: D62404528

Summary: Previously we were accomodating `torch._dynamo.mark_dynamic()` for export's dynamic shapes. Here we clean things up and ignore it, requiring users to specify an export input for `dynamic_shapes`. Note: there's 4 decorators relevant to export, `mark_dynamic, maybe_mark_dynamic, mark_static, mark_unbacked`. User calls that involve export have only been `mark_dynamic()`, and we use `maybe_mark_dynamic` under the hood for `Dim.AUTO`, but we could start using others. One reason I decided to not warn and just silently ignore is these decorators cause the tensors to carry dynamic info, and it'll be hard to tell whether the markers are from export or user calls when re-exporting with the same inputs. cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv jiayisunx ipiszy yf225 chenyang78 kadeng muchulee8 ColinPeppler amjames desertfire chauhang rec X-link: pytorch/pytorch#135536 Reviewed By: avikchaudhuri Differential Revision: D62404528 Pulled By: pianpwk

Summary: X-link: pytorch/benchmark#2451 Previously we were accomodating `torch._dynamo.mark_dynamic()` for export's dynamic shapes. Here we clean things up and ignore it, requiring users to specify an export input for `dynamic_shapes`. Note: there's 4 decorators relevant to export, `mark_dynamic, maybe_mark_dynamic, mark_static, mark_unbacked`. User calls that involve export have only been `mark_dynamic()`, and we use `maybe_mark_dynamic` under the hood for `Dim.AUTO`, but we could start using others. One reason I decided to not warn and just silently ignore is these decorators cause the tensors to carry dynamic info, and it'll be hard to tell whether the markers are from export or user calls when re-exporting with the same inputs. cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv jiayisunx ipiszy yf225 chenyang78 kadeng muchulee8 ColinPeppler amjames desertfire chauhang rec Reviewed By: avikchaudhuri Differential Revision: D62404528 Pulled By: pianpwk

facebook-github-bot · 2024-09-11T03:04:31Z

This pull request was exported from Phabricator. Differential Revision: D62404528

Summary: Pull Request resolved: #2451 Previously we were accomodating `torch._dynamo.mark_dynamic()` for export's dynamic shapes. Here we clean things up and ignore it, requiring users to specify an export input for `dynamic_shapes`. Note: there's 4 decorators relevant to export, `mark_dynamic, maybe_mark_dynamic, mark_static, mark_unbacked`. User calls that involve export have only been `mark_dynamic()`, and we use `maybe_mark_dynamic` under the hood for `Dim.AUTO`, but we could start using others. One reason I decided to not warn and just silently ignore is these decorators cause the tensors to carry dynamic info, and it'll be hard to tell whether the markers are from export or user calls when re-exporting with the same inputs. cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv jiayisunx ipiszy yf225 chenyang78 kadeng muchulee8 ColinPeppler amjames desertfire chauhang rec X-link: pytorch/pytorch#135536 Reviewed By: avikchaudhuri Differential Revision: D62404528 Pulled By: pianpwk

Summary: X-link: pytorch/benchmark#2451 Previously we were accomodating `torch._dynamo.mark_dynamic()` for export's dynamic shapes. Here we clean things up and ignore it, requiring users to specify an export input for `dynamic_shapes`. Note: there's 4 decorators relevant to export, `mark_dynamic, maybe_mark_dynamic, mark_static, mark_unbacked`. User calls that involve export have only been `mark_dynamic()`, and we use `maybe_mark_dynamic` under the hood for `Dim.AUTO`, but we could start using others. One reason I decided to not warn and just silently ignore is these decorators cause the tensors to carry dynamic info, and it'll be hard to tell whether the markers are from export or user calls when re-exporting with the same inputs. cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv jiayisunx ipiszy yf225 chenyang78 kadeng muchulee8 ColinPeppler amjames desertfire chauhang rec Reviewed By: avikchaudhuri Differential Revision: D62404528 Pulled By: pianpwk

facebook-github-bot · 2024-09-11T17:52:32Z

This pull request was exported from Phabricator. Differential Revision: D62404528

Summary: Pull Request resolved: #2451 Previously we were accomodating `torch._dynamo.mark_dynamic()` for export's dynamic shapes. Here we clean things up and ignore it, requiring users to specify an export input for `dynamic_shapes`. Note: there's 4 decorators relevant to export, `mark_dynamic, maybe_mark_dynamic, mark_static, mark_unbacked`. User calls that involve export have only been `mark_dynamic()`, and we use `maybe_mark_dynamic` under the hood for `Dim.AUTO`, but we could start using others. One reason I decided to not warn and just silently ignore is these decorators cause the tensors to carry dynamic info, and it'll be hard to tell whether the markers are from export or user calls when re-exporting with the same inputs. cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv jiayisunx ipiszy yf225 chenyang78 kadeng muchulee8 ColinPeppler amjames desertfire chauhang rec X-link: pytorch/pytorch#135536 Reviewed By: avikchaudhuri Differential Revision: D62404528 Pulled By: pianpwk

Summary: Pull Request resolved: #2451 Previously we were accomodating `torch._dynamo.mark_dynamic()` for export's dynamic shapes. Here we clean things up and ignore it, requiring users to specify an export input for `dynamic_shapes`. Note: there's 4 decorators relevant to export, `mark_dynamic, maybe_mark_dynamic, mark_static, mark_unbacked`. User calls that involve export have only been `mark_dynamic()`, and we use `maybe_mark_dynamic` under the hood for `Dim.AUTO`, but we could start using others. One reason I decided to not warn and just silently ignore is these decorators cause the tensors to carry dynamic info, and it'll be hard to tell whether the markers are from export or user calls when re-exporting with the same inputs. cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv jiayisunx ipiszy yf225 chenyang78 kadeng muchulee8 ColinPeppler amjames desertfire chauhang rec X-link: pytorch/pytorch#135536 Reviewed By: desertfire, avikchaudhuri Differential Revision: D62404528 Pulled By: pianpwk

Summary: X-link: pytorch/benchmark#2451 Previously we were accomodating `torch._dynamo.mark_dynamic()` for export's dynamic shapes. Here we clean things up and ignore it, requiring users to specify an export input for `dynamic_shapes`. Note: there's 4 decorators relevant to export, `mark_dynamic, maybe_mark_dynamic, mark_static, mark_unbacked`. User calls that involve export have only been `mark_dynamic()`, and we use `maybe_mark_dynamic` under the hood for `Dim.AUTO`, but we could start using others. One reason I decided to not warn and just silently ignore is these decorators cause the tensors to carry dynamic info, and it'll be hard to tell whether the markers are from export or user calls when re-exporting with the same inputs. cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv jiayisunx ipiszy yf225 chenyang78 kadeng muchulee8 ColinPeppler amjames desertfire chauhang rec Reviewed By: desertfire, avikchaudhuri Differential Revision: D62404528 Pulled By: pianpwk

facebook-github-bot · 2024-09-12T17:55:19Z

This pull request was exported from Phabricator. Differential Revision: D62404528

Summary: Pull Request resolved: #2451 Previously we were accomodating `torch._dynamo.mark_dynamic()` for export's dynamic shapes. Here we clean things up and ignore it, requiring users to specify an export input for `dynamic_shapes`. Note: there's 4 decorators relevant to export, `mark_dynamic, maybe_mark_dynamic, mark_static, mark_unbacked`. User calls that involve export have only been `mark_dynamic()`, and we use `maybe_mark_dynamic` under the hood for `Dim.AUTO`, but we could start using others. One reason I decided to not warn and just silently ignore is these decorators cause the tensors to carry dynamic info, and it'll be hard to tell whether the markers are from export or user calls when re-exporting with the same inputs. cc voznesenskym penguinwu EikanWang jgong5 Guobing-Chen XiaobingSuper zhuhaozhe blzheng wenzhe-nrv jiayisunx ipiszy yf225 chenyang78 kadeng muchulee8 ColinPeppler amjames desertfire chauhang rec X-link: pytorch/pytorch#135536 Reviewed By: desertfire, avikchaudhuri Differential Revision: D62404528 Pulled By: pianpwk fbshipit-source-id: 1da81cbc71c337b40cc336dfdb93292210ab66aa

facebook-github-bot · 2024-09-12T21:20:23Z

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Previously we were accomodating `torch._dynamo.mark_dynamic()` for export's dynamic shapes. Here we clean things up and ignore it, requiring users to specify an export input for `dynamic_shapes`. Note: there's 4 decorators relevant to export, `mark_dynamic, maybe_mark_dynamic, mark_static, mark_unbacked`. User calls that involve export have only been `mark_dynamic()`, and we use `maybe_mark_dynamic` under the hood for `Dim.AUTO`, but we could start using others. One reason I decided to not warn and just silently ignore is these decorators cause the tensors to carry dynamic info, and it'll be hard to tell whether the markers are from export or user calls when re-exporting with the same inputs. Pull Request resolved: pytorch#135536 Approved by: https://github.com/avikchaudhuri

Summary: Removing `_transform_shapes_for_default_dynamic` and `assume_static_by_default=False` as added in #133620. This reverts back to `assume_static_by_default=True` with the use of dynamo decorators (e.g. `maybe_mark_dynamic, mark_static`, instead) for handling Dim.AUTO & Dim.STATIC instead. This is easier to maintain, as it doesn't requiring reasoning about "inverting" the dynamic_shapes specs, and also opens up usage of other decorators (`mark_dynamic, mark_unbacked`). On the user side this change has no effect, but internally this means dynamic behavior is determined only by the `dynamic_shapes` specs (ignoring user-side input decorators following #135536), but transferring this information for _DimHints via decorators, for Dynamo/non-strict to create symbolic_contexts accordingly, e.g. https://github.com/pytorch/pytorch/blob/7c6d543a5b3d65d8f49420e60cda150faaa5b8a0/torch/_dynamo/variables/builder.py#L2646-L2666 One caveat is we don't raise errors for dynamic decorators on the user side, since we don't know if they're from user markings, or from re-exporting with inputs we've previously marked. Differential Revision: D63358628 Pulled By: pianpwk

Summary: Removing `_transform_shapes_for_default_dynamic` and `assume_static_by_default=False` as added in #133620. This reverts back to `assume_static_by_default=True` with the use of dynamo decorators (e.g. `maybe_mark_dynamic, mark_static`, instead) for handling Dim.AUTO & Dim.STATIC instead. This is easier to maintain, as it doesn't requiring reasoning about "inverting" the dynamic_shapes specs, and also opens up usage of other decorators (`mark_dynamic, mark_unbacked`). On the user side this change has no effect, but internally this means dynamic behavior is determined only by the `dynamic_shapes` specs (ignoring user-side input decorators following #135536), but transferring this information for _DimHints via decorators, for Dynamo/non-strict to create symbolic_contexts accordingly, e.g. https://github.com/pytorch/pytorch/blob/7c6d543a5b3d65d8f49420e60cda150faaa5b8a0/torch/_dynamo/variables/builder.py#L2646-L2666 One caveat is we don't raise errors for dynamic decorators on the user side, since we don't know if they're from user markings, or from re-exporting with inputs we've previously marked. Pull Request resolved: #136591 Differential Revision: D63358628 Pulled By: pianpwk

Summary: Removing `_transform_shapes_for_default_dynamic` and `assume_static_by_default=False` as added in #133620. This reverts back to `assume_static_by_default=True` with the use of dynamo decorators (e.g. `maybe_mark_dynamic, mark_static`, instead) for handling Dim.AUTO & Dim.STATIC instead. This is easier to maintain, as it doesn't requiring reasoning about "inverting" the dynamic_shapes specs, and also opens up usage of other decorators (`mark_dynamic, mark_unbacked`). On the user side this change has no effect, but internally this means dynamic behavior is determined only by the `dynamic_shapes` specs (ignoring user-side input decorators following #135536), but transferring this information for _DimHints via decorators, for Dynamo/non-strict to create symbolic_contexts accordingly, e.g. https://github.com/pytorch/pytorch/blob/7c6d543a5b3d65d8f49420e60cda150faaa5b8a0/torch/_dynamo/variables/builder.py#L2646-L2666 One caveat is we don't raise errors for dynamic decorators on the user side, since we don't know if they're from user markings, or from re-exporting with inputs we've previously marked. Differential Revision: D63358628 Pulled By: pianpwk

Removing `_transform_shapes_for_default_dynamic` and `assume_static_by_default=False` as added in #133620. This reverts back to `assume_static_by_default=True` with the use of dynamo decorators (e.g. `maybe_mark_dynamic, mark_static`, instead) for handling Dim.AUTO & Dim.STATIC instead. This is easier to maintain, as it doesn't requiring reasoning about "inverting" the dynamic_shapes specs, and also opens up usage of other decorators (`mark_dynamic, mark_unbacked`). On the user side this change has no effect, but internally this means dynamic behavior is determined only by the `dynamic_shapes` specs (ignoring user-side input decorators following #135536), but transferring this information for _DimHints via decorators, for Dynamo/non-strict to create symbolic_contexts accordingly, e.g. https://github.com/pytorch/pytorch/blob/7c6d543a5b3d65d8f49420e60cda150faaa5b8a0/torch/_dynamo/variables/builder.py#L2646-L2666 One caveat is we don't raise errors for dynamic decorators on the user side, since we don't know if they're from user markings, or from re-exporting with inputs we've previously marked. Differential Revision: D63358628 Pull Request resolved: #136591 Approved by: https://github.com/avikchaudhuri

pianpwk changed the title ~~dynamic shapes~~ ignore mark dynamic and see what fails Sep 9, 2024

facebook-github-bot pushed a commit that referenced this pull request Sep 10, 2024

ignore mark dynamic and see what fails (#135536)

1ea23d1

Summary: Fixes #ISSUE_NUMBER Differential Revision: D62404528 Pulled By: pianpwk

facebook-github-bot force-pushed the pianpwk/export_ignore_mark_dynamic branch from 9b747ca to 1ea23d1 Compare September 10, 2024 00:19

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ignore mark dynamic and see what fails (#135536)

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Summary: Fixes #ISSUE_NUMBER Differential Revision: D62404528 Pulled By: pianpwk

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pianpwk changed the title ~~ignore mark dynamic and see what fails~~ [export] ignore mark_dynamic() in export Sep 10, 2024

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pianpwk marked this pull request as ready for review September 10, 2024 18:08

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ignore mark_dynamic() in export pytorch/benchmark#2451

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[export] simplify automatic dynamic shapes processing #136591

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[export] ignore mark_dynamic() in export #135536

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