Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/26992
Run the same test for FBGEMM and QNNPACK backends.
Checks that QNNPACK or FBGEMM are supported before running it (using supported_qengines)
Test Plan:
python test/test_quantized.py TestQuantizedLinear
python test/test_quantized.py TestQuantizedConv
python test/test_quantized_models.py
python test/test_quantized_nn_mods.py
Imported from OSS
Differential Revision: D17689171
fbshipit-source-id: e11c0a5e41f5f4e6836a614a5b61e4db3c5e384b
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/26620
This change updates torch.backend.quantized.engine to accept string ("fbgemm"/"qnnpack"/"none" for now).
set_qengine and get_qengine return an int which represents the at::QEngine enum
Test Plan:
python test/test_torch.py
Imported from OSS
Differential Revision: D17533582
fbshipit-source-id: 5103263d0d59ff37d43dec27243cb76ba8ba633f
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/26135
This change adds the support to call QNNPACK using the refactored API for Linear operators (Fully Connected)
It also has certain cmake changes to enable builing and using pytorch_qnnpack inside aten
I have disabled USE_QNNPACK in CMakeLists.txt. Enabling it results in picking kernels from third_party/QNNPACK during runtime since the function names are the same.
Test Plan:
python test/test_quantized.py TestQNNPackOps.test_qlinear_qnnpack
Imported from OSS
Differential Revision: D17434885
fbshipit-source-id: 084698026938f4529f61d12e86dfe82534ec73dd
Summary:
As suggested in https://github.com/pytorch/pytorch/pull/22891, we will add an overload for torch.fbgemm_linear_int8_weight (dynamic quantized version of linear function) that takes PackedLinearWeight as input and is pretty much the same in signature as regular aten::linear.
The previous Diff D16381552 is reverted because `quantize_linear` expects the scale to be `float`, and the zero_point to be `int`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/23464
ghstack-source-id: 88257231
Differential Revision: D16527741
fbshipit-source-id: 66585f668c6e623c50514eb11633bb711d8767f2
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/23104
ghstack-source-id: 87247148
As suggested in https://github.com/pytorch/pytorch/pull/22891, we will add an overload for ```torch.fbgemm_linear_int8_weight``` (dynamic quantized version of linear function) that takes PackedLinearWeight as input and is pretty much the same in signature as regular aten::linear.
Differential Revision: D16381552
fbshipit-source-id: 1ccc4174fd02c546eee328940ac4b0da48fc85e8
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/22694
Move quantization and quantized utility functions for testing to common_quantized.py and common_quantization.py. Addditionally, add a quantized test case base class which contains common methods for checking the results of quantization on modules. As a consequence of the move, fixed the import at the top of test_quantized.py, and test_quantization to use the new utility
Reviewed By: jerryzh168
Differential Revision: D16172012
fbshipit-source-id: 329166af5555fc829f26bf1383d682c25c01a7d9
