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Merged
merged 8 commits into from
May 2, 2022
Merged

Fuse_modules in a qat-respecting way #12891

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67bc264
Fuse_modules in a qat-respecting way
ORippler Apr 26, 2022
923ae89
Add compatibility for PyTorch <1.11
ORippler Apr 27, 2022
7f16d6a
Add CHANGELOG for pull #12891
ORippler Apr 27, 2022
4ea51be
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Apr 27, 2022
c122790
Fix conditional import of fuse_modules_qat
ORippler Apr 27, 2022
3190723
Update CHANGELOG.md
akihironitta Apr 27, 2022
d87ad70
Merge branch 'master' into fix/12890
akihironitta Apr 29, 2022
78bb737
Merge branch 'master' into fix/12890
carmocca Apr 29, 2022
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3 changes: 3 additions & 0 deletions CHANGELOG.md
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Expand Up @@ -143,6 +143,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).

### Fixed

- Fixed `fuse_modules` to be qat-aware for `torch>=1.11` ([#12891](https://github.com/PyTorchLightning/pytorch-lightning/pull/12891))


- Use only a single instance of `rich.console.Console` throughout codebase ([#12886](https://github.com/PyTorchLightning/pytorch-lightning/pull/12886))


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9 changes: 7 additions & 2 deletions pytorch_lightning/callbacks/quantization.py
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Expand Up @@ -26,14 +26,19 @@

import pytorch_lightning as pl
from pytorch_lightning.callbacks.base import Callback
from pytorch_lightning.utilities import _TORCH_GREATER_EQUAL_1_10
from pytorch_lightning.utilities import _TORCH_GREATER_EQUAL_1_10, _TORCH_GREATER_EQUAL_1_11
from pytorch_lightning.utilities.exceptions import MisconfigurationException

if _TORCH_GREATER_EQUAL_1_10:
from torch.ao.quantization.qconfig import QConfig
else:
from torch.quantization import QConfig

if _TORCH_GREATER_EQUAL_1_11:
from torch.ao.quantization import fuse_modules_qat as fuse_modules
else:
from torch.quantization import fuse_modules


def wrap_qat_forward_context(
quant_cb, model: "pl.LightningModule", func: Callable, trigger_condition: Optional[Union[Callable, int]] = None
Expand Down Expand Up @@ -252,7 +257,7 @@ def _prepare_model(self, model: torch.nn.Module) -> None:
model.qconfig = self._qconfig

if self._check_feasible_fuse(model):
torch.quantization.fuse_modules(model, self._modules_to_fuse, inplace=True)
fuse_modules(model, self._modules_to_fuse, inplace=True)

# Prepare the model for QAT. This inserts observers and fake_quants in
# the model that will observe weight and activation tensors during calibration.
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1 change: 1 addition & 0 deletions pytorch_lightning/utilities/__init__.py
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Expand Up @@ -49,6 +49,7 @@
_RICH_AVAILABLE,
_TORCH_GREATER_EQUAL_1_9,
_TORCH_GREATER_EQUAL_1_10,
_TORCH_GREATER_EQUAL_1_11,
_TORCH_QUANTIZE_AVAILABLE,
_TORCHTEXT_AVAILABLE,
_TORCHVISION_AVAILABLE,
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