Factor out the specific configurations to helper functions #286
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/286
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Summary: int4wo, int8wo, int8dyn, 8da4w are specific configurations for quantize function, we factor that out in the PR so they are easy to use Test Plan: python test/quantization/test_quant_api.py Reviewers: Subscribers: Tasks: Tags:
andrewor14
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May 28, 2024
andrewor14
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May 28, 2024
| @@ -287,3 +297,103 @@ def filter_fn(module, fqn): | |||
| _is_linear if filter_fn is None else filter_fn, | |||
| ) | |||
| return model | |||
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| def get_apply_8da4w_quant(groupsize=32): | |||
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should we make these private for now? I'm not sure if we want users to call these directly
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it's fine I think, I'm planning to use this in an example as well. what's the concern of this being public?
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Summary: int4wo, int8wo, int8dyn, 8da4w are specific configurations for quantize function, we factor that out in the PR so they are easy to use Test Plan: python test/quantization/test_quant_api.py Reviewers: Subscribers: Tasks: Tags:
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Summary:
int4wo, int8wo, int8dyn, 8da4w are specific configurations for quantize function, we factor that out in the PR so they are easy to use
Test Plan:
python test/quantization/test_quant_api.py
Reviewers:
Subscribers:
Tasks:
Tags: