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[Core] Zero-copy asdict for InputMetadata #3475
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@@ -527,7 +526,7 @@ def prepare_input_tensors( | |||
"lora_requests": lora_requests, | |||
"lora_mapping": lora_mapping, | |||
} | |||
metadata_dict.update(dataclasses.asdict(input_metadata)) | |||
metadata_dict.update(input_metadata.asdict_zerocopy()) |
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can you just do input_metadata.__dict__
to avoid the new method at all?
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Perhaps, though that may lead to unexpected interactions if InputMetadata
has extra properties added and such.
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No, because the post init adds self.attn_bias = None
.
It seems the deepcopy of How about moving to from attrs import asdict, define
@define
class MyDataClass:
a: int
b: list
instance = MyDataClass(1, [2, 3])
data1 = asdict(instance, recurse=False)
assert data1['b'] is instance.b Its |
Here is the whole picture: import attrs
@attrs.define(slots=False)
class MyDataClass:
a: int
b: list
def __attrs_post_init__(self):
self.c = None
instance = MyDataClass(1, [2, 3])
data1 = asdict(instance, recurse=False)
assert data1['b'] is instance.b # make sure it is shallow copy
assert "c" not in data1 # make sure asdict only contains annotated fields |
I don't think it makes sense to add a third-party library just for this one specific usecase. We can always revisit this if we find ourselves implementing this pattern more times. |
Oh, One reason that e.g. when you want to use new features from I vote for Open to any feedback :) |
I think it's fine if your PR makes use of it, but I don't think it's necessary to couple |
Then please make sure to rename |
I think it should be |
Co-authored-by: Woosuk Kwon <woosuk.kwon@berkeley.edu>
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LGTM! Thanks for finding the performance bug. Didn't know the issue in dataclasses.asdict
. TIL 😄
@Yard1 It seems the CI failed. Could you please double check? |
yeah let me see |
Should be good now! |
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dataclasses.asdict
will deepcopy tensors insideInputMetadata
, leading to an avoidable overhead. This PR adds a new method toInputMetadata
which will return a dict of fields and their values without copy.Before:
After: