Summary: This commit renames fx/quantization_patterns.py
to fx/quantize_handler.py, and fx/fusion_patterns.py to
fx/fuse_handler.py. This is because these files contain
only QuantizeHandler and FuseHandler respectively, so the
new names are more descriptive. A future commit will
further break BC by removing all the empty *QuantizeHandler
classes.
BC-breaking notes:
The following classes under the
`torch.ao.quantization.fx.quantization_patterns` namespace
are migrated to the `torch.ao.quantization.fx.quantize_handler`
namespace:
```
QuantizeHandler
BinaryOpQuantizeHandler
CatQuantizeHandler
ConvReluQuantizeHandler
LinearReLUQuantizeHandler
BatchNormQuantizeHandler
EmbeddingQuantizeHandler
RNNDynamicQuantizeHandler
DefaultNodeQuantizeHandler
FixedQParamsOpQuantizeHandler
CopyNodeQuantizeHandler
GeneralTensorShapeOpQuantizeHandler
CustomModuleQuantizeHandler
StandaloneModuleQuantizeHandler
```
The following classes under the
`torch.ao.quantization.fx.fusion_patterns` namespace are
migrated to the `torch.ao.quantization.fx.fuse_handler`
namespace:
```
DefaultFuseHandler
FuseHandler
```
Test Plan:
python test/test_quantization.py TestQuantizeFx
python test/test_quantization.py TestQuantizeFxOps
Reviewers: jerryzh168, vkuzo
Subscribers: jerryzh168, vkuzo
Pull Request resolved: https://github.com/pytorch/pytorch/pull/89872
Approved by: https://github.com/jerryzh168
Summary: Previously under torch/ao/quantization we have
backend_config/utils.py and fx/backend_config_utils.py, which
was confusing. This commit deletes the latter and moves
everything there to more suitable util files.
BC-breaking note: The following public APIs under the
`torch.ao.quantization.fx.backend_config_utils` namespace
are removed in this commit.
```
get_quantize_handler_cls
get_fusion_pattern_to_fuse_handler_cls
get_native_quant_patterns
get_pattern_to_quantize_handlers
```
Test Plan:
python test/test_quantization.py TestQuantizeFx
python test/test_quantization.py TestQuantizeFxOps
Reviewers: jerryzh168, vkuzo
Subscribers: jerryzh168, vkuzo
Pull Request resolved: https://github.com/pytorch/pytorch/pull/89810
Approved by: https://github.com/jerryzh168
Summary:
Following https://github.com/pytorch/rfcs/blob/master/RFC-0019-Extending-PyTorch-Quantization-to-Custom-Backends.md we implemented
the backend configuration for fbgemm/qnnpack backend, currently it was under fx folder, but we'd like to use this for all different
workflows, including eager, fx graph and define by run quantization, this PR moves it to torch.ao.quantization namespace so that
it can be shared by different workflows
Also moves some utility functions specific to fx to fx/backend_config_utils.py and some files are kept in fx folder (quantize_handler.py and fuse_handler.py)
Test Plan:
python test/teset_quantization.py TestQuantizeFx
python test/teset_quantization.py TestQuantizeFxOps
python test/teset_quantization.py TestQuantizeFxModels
python test/test_quantization.py TestAOMigrationQuantization
python test/test_quantization.py TestAOMigrationQuantizationFx
Reviewers:
Subscribers:
Tasks:
Tags:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/75823
Approved by: https://github.com/vkuzo
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/75318
This PR moves the registrations for fusion patterns to backend_config_dict
Also fixed one issue in numeric suite graph matcher, since now (torch.nn.ReLU, torch.nn.BatchNorm3d)
would appear in quant patterns, (previously only in fusion pattern), and we need to match sure (torch.nn.ReLU, (torch.nn.BatchNorm3d, torch.nn.Conv3d))
can match before (torch.nn.ReLU, torch.nn.BatchNorm3d), but previously, it looks like (torch.nn.ReLU, (torch.nn.BatchNorm3d, torch.nn.Conv3d)) is not
really matched since `end_node_matches_reversed_fusion` is expecting a flattened pattern like (torch.nn.ReLU, torch.nn.BatchNorm3d, torch.nn.Conv3d),
for now we'll manually flatten this pattern, but in the future I think we might want to use the matching function `is_match` under torch.ao.quantization.fx.match_utils
to do this matching.
Test Plan:
python test/test_quantization.py TestQuantizeFx
python test/test_quantization.py TestQuantizeFxOps
python test/test_quantization.py TestFXNumericSuiteCoreAPIs
Imported from OSS
Reviewed By: vkuzo, andrewor14
Differential Revision: D35423788
fbshipit-source-id: a54093ccebae9c59aeee9399669ddb2c48bfb9aa
(cherry picked from commit 6a55ea8eb2740cedafb9972888fedf68e927586d)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/74636
This commit changes how quantization patterns for linear
and conv are set up in prepare. Previously, these were set up
through ConvReluQuantizeHandler and LinearReLUQuantizeHandler.
After this commit, however, these were set up through the
corresponding entries in the native backend_config_dict,
rendering the above quantize handlers no longer necessary.
In future commits, we will do the same for the remaining ops.
Test Plan:
python test/test_quantization.py TestQuantizeFx
python test/test_quantization.py TestQuantizeFxOps
Imported from OSS
Reviewed By: jerryzh168, ngimel
Differential Revision: D35225680
fbshipit-source-id: 4a79f63a11fce46701eb17aaf3619c1e827d72a4
(cherry picked from commit 475f599821cd32d3ba71ba086885ecdc4cbee755)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/74600
Following https://github.com/pytorch/pytorch/pull/74210, this PR adds the support for some ops
using the DefaultNodeQuantizeHandler in the backend_config_dict defintion for pytorch native backend
TODO: There is still a few ops we didn't handle with backend_config_dict path: gelu and softmax, need to discuss if we still need them, if so we can change the test
to use backend_config_dict and remove the DefaultNodeQuantizeHandler after that
Test Plan:
python test/test_quantization.py TestQuantizeFxOps
Imported from OSS
Reviewed By: andrewor14
Differential Revision: D35071437
fbshipit-source-id: 70351d2810ca1ac7dc09d4a9c239f6757ccb51ca
(cherry picked from commit 5e68f755a32ba7d90d6c73db9c2017f9c58d7fa5)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/69238
The NS for FX graph matcher was not properly taking into account
seen_nodes, this allowed a node to be matched twice.
Test Plan:
FB-only testing on real model passes.
Ideally we would have a test case to capture this, but hopefully we can land this soon to unblock production work.
Imported from OSS
Reviewed By: HDCharles
Differential Revision: D32765761
fbshipit-source-id: ed3dff8fd981e399a649fcd406883b4d56cc712a
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/66058
After the initial migration from `torch.quantization` to `torch.ao.quantization`, some of the files did not change.
This happened because the migration was done in parallel, and some of the files were landed while the others were still in the original location.
This is the last fix in the AO migration phase 1, which completely enables the ao.quantization namespace.
Test Plan: `python test/test_quantization.py`
Reviewed By: vkuzo
Differential Revision: D31366066
Pulled By: z-a-f
fbshipit-source-id: bf4a74885be89d098df2d87e685795a2a64026c5
