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[not yet for review] migrate pt2e from torch.ao to torchao #10294

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metascroy
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Most code related to PT2E quantization is migrating from torch.ao.quantization to torchao.quantization.pt2e.

torchao.quantization.pt2e contains an exact copy of PT2E code in torch.ao.quantization.

The torchao pin in ExecuTorch has already been bumped pick up these changes.

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pytorch-bot bot commented Apr 18, 2025 •
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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/10294

Note: Links to docs will display an error until the docs builds have been completed.

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@facebook-github-bot facebook-github-bot added the CLA Signed This label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed. label Apr 18, 2025
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This PR needs a release notes: label

If your changes are user facing and intended to be a part of release notes, please use a label starting with release notes:.

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@metascroy metascroy changed the title Migrate pt2e from torch.ao to torchao [not yet for review] migrate pt2e from torch.ao to torchao Apr 18, 2025
digantdesai
digantdesai reviewed Apr 21, 2025
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backends/arm/quantizer/arm_quantizer.py
@@ -34,25 +34,25 @@
is_ethosu,
) # usort: skip
from executorch.exir.backend.compile_spec_schema import CompileSpec
from torch.ao.quantization.fake_quantize import (
from torch.fx import GraphModule, Node
from torchao.quantization.pt2e import _ObserverOrFakeQuantizeConstructor
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Correct me if I am wrong but torchao isn't a mandetory dep today but now it is?

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How do we define mandatory dependencies? It is installed by the install_requirements script?

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Seems like we pull in source -

executorch/.gitmodules

Line 60 in 647e1f1

url = https://github.com/pytorch/ao.git

So this submodule is already updated since the tests are passing here.

check (1) if we run tests on et wheels with something quant, (2) if we do are they passing for this diff.

backends/xnnpack/quantizer/xnnpack_quantizer.py
@@ -16,25 +16,25 @@
propagate_annotation,
QuantizationConfig,
)
from torch.ao.quantization.fake_quantize import (
from torchao.quantization.pt2e.fake_quantize import (
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nit: there are some affine quantization stuff which assumes torchao isn't always available, can we fix that with this? here is one example.

cc @mcr229

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cccclai commented Apr 21, 2025

Adding partners for visibility

@cccclai cccclai requested a review from YifanShenSZ April 21, 2025 20:44
digantdesai
digantdesai reviewed Apr 22, 2025
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backends/nxp/quantizer/neutron_quantizer.py
from torch.ao.quantization.observer import HistogramObserver, MinMaxObserver
from torch.ao.quantization.quantizer import DerivedQuantizationSpec, Quantizer
from torch.ao.quantization.quantizer.composable_quantizer import ComposableQuantizer
from torchao.quantization.pt2e.observer import HistogramObserver, MinMaxObserver
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cc @robert-kalmar FYI

digantdesai
digantdesai reviewed Apr 22, 2025
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backends/cadence/aot/compiler.py

from torch.export import export
from torch.export.exported_program import ExportedProgram
from torchao.quantization.pt2e.quantize_pt2e import convert_pt2e, prepare_pt2e
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FYI @mcremon-meta

digantdesai
digantdesai reviewed Apr 22, 2025
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backends/arm/quantizer/arm_quantizer.py
@@ -34,25 +34,25 @@
is_ethosu,
) # usort: skip
from executorch.exir.backend.compile_spec_schema import CompileSpec
from torch.ao.quantization.fake_quantize import (
from torch.fx import GraphModule, Node
from torchao.quantization.pt2e import _ObserverOrFakeQuantizeConstructor
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FYI @freddan80 @per

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