[dtensor][2/n] use op overload instead of function schema #107306
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Summary: Test Plan: Reviewers: Subscribers: Tasks: Tags: [ghstack-poisoned]
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/107306
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit af9af44 with merge base 6dc56d3 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
This was referenced Aug 16, 2023
Summary: Test Plan: Reviewers: Subscribers: Tasks: Tags: [ghstack-poisoned]
Summary: Test Plan: Reviewers: Subscribers: Tasks: Tags: [ghstack-poisoned]
Summary: Test Plan: Reviewers: Subscribers: Tasks: Tags: [ghstack-poisoned]
Summary: Test Plan: Reviewers: Subscribers: Tasks: Tags: [ghstack-poisoned]
Summary: Test Plan: Reviewers: Subscribers: Tasks: Tags: [ghstack-poisoned]
Summary: Test Plan: Reviewers: Subscribers: Tasks: Tags: [ghstack-poisoned]
This was referenced Aug 30, 2023
wanchaol
requested review from
mrshenli,
zhaojuanmao,
rohan-varma,
H-Huang,
awgu,
kwen2501,
fegin,
fduwjj,
wz337,
kiukchung and
d4l3k
as code owners
fduwjj
reviewed
Sep 7, 2023
Comment on lines
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| def __post_init__(self) -> None: | ||
| # simple analysis of function schema to determine | ||
| # if this is an inplace/out variant, it might not | ||
| # be entirely correct, but it's good enough for now. | ||
| self.is_inplace = self.func_schema.name[-1] == "_" | ||
| self.is_out_variant = "out" in self.func_schema.overload_name |
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Isn't this making the check being called every time in every DTensor Op dispatch? Or we cannot cache the value of these two, so using __post_init__ does not help that much?
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This post init just try to analyze the operator we are dispatching over is a inplace op or out variant, but we don't really need this information unless for some certain ops (i.e. when we are checking if the op is inplace or out in pointwise ops), so everytime we form a OpSchema we analyze this become redundant, that's why I am deleting it and put this logic inside the op rules directly.
The caching would cache the op_schema's hash only, and because we don't hash these two fields anyways, the cache behavior does not change.
fduwjj
approved these changes
Sep 7, 2023
function schema doesn't provide us anything as we can also get the schema from `op._schema`, include the op directly in op_schema makes easier for sharding prop to do fake execution, and in principle it should also make the hash comparison faster as we don't need to hash the function schema, instead we just hash the `id(op)` which is constant This PR is just a refactor to include op to OpSchema instead of func schema, no other logic changes [ghstack-poisoned]
This was referenced Sep 12, 2023
pytorchmergebot
pushed a commit
that referenced
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Sep 13, 2023
This PR switches the usage of fx's shape prop TensorMetadata to dtensor's own dedicated defined TensorMeta, this is because DTensor only cares three fields: shape/stride/dtype, all other fields are not necessary and can be inferred from local_tensor directly. This would help significantly simplify how we deal with the tensor metadata by not caring other fields. Pull Request resolved: #108261 Approved by: https://github.com/fduwjj ghstack dependencies: #107306
pytorchmergebot
pushed a commit
that referenced
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Sep 13, 2023
We were using make_fx for strategy based propagation so that we can get a graph and the shape related metadata, this becomes too much overkill for the sharding propagation purpose. This change refactors the strategy propagation to remove the graph based propagation, instead just use the op to index to the strategy functions. We also just use a fake shape prop instead of relying on fx tracing for the shape/stride propagation. for a future possible decomposed propagation, we will exercise different codepath to enable that NOTE that this would also greatly reduce the latency of: 1. first time dtensor operations when populating the cache, the first iter would become faster again! 2. greatly reduce the test_dtensor_ops.py time again, right now the whole test finished within 2-3 mins again. Pull Request resolved: #108262 Approved by: https://github.com/fduwjj ghstack dependencies: #107306, #108261
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Stack from ghstack (oldest at bottom):
function schema doesn't provide us anything as we can also get the schema from
op._schema, include the op directly in op_schema makes easier for sharding prop to do fake execution, and in principle it should also make the hash comparison faster as we don't need to hash the function schema, instead we just hash theid(op)which is constantThis PR is just a refactor to include op to OpSchema instead of func schema, no other logic changes