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Commits on Aug 26, 2019

• Adding Scalar add/mul. (pytorch#24447)

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• Adding return for the observer in the functional_modules.py

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• fix to loggin in AA

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• Implement name inference for mm, addmm (pytorch#24306)

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• Fix binary op name inference between unnamed and named tensors. (pytorch#24921)

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• Move test QAT tests to double precision to ensure numerics match (pytorch#25189)

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• Serialization for nn.quantized.functional modules (pytorch#24924)

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• Support observer without any data calibration (pytorch#24923)

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• Update mapping dictionary to support functionalmodules and pooling operations (pytorch#24804)

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• Handle empty qconfig for functional Modules (pytorch#24803)

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• Work around for bias quantization for conv and linear operators (pytorch#24789)

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• bind autograd.backward and tensor.backward in TorchScript (pytorch#23913)

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• quant_fusion jit pass (pytorch#24427)

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• insert_quant_dequant jit pass (pytorch#24426)

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• per channel quantization support (pytorch#25134)

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• hyperparameter plugin (pytorch#23134)

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• Add Python/C++ torch.nn API parity test harness (pytorch#23852)

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• prevent generating caffe2::mkl for multiple times (pytorch#25167)

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• Ensure tests get passed on Windows (pytorch#25145)

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• torch.from_numpy fix for np.int (pytorch#25139)

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Commits on Aug 25, 2019

• Support focal loss in MTML

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• Fix ios_crash:backtrace=FBCameraFramework:caffe2::getClockTimeMilliseconds() (perf_observer.cc (pytorch#24813)

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• Add logging to JIT CSE pass.

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Commits on Aug 24, 2019

• Switch hub to use requests because of SSL (pytorch#25083)

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• SubgraphMatcher: matching modules support. (pytorch#25075)

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• SubgraphMatcher: add logging.

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• SubgraphMatcher: Factor out matchAttributes.

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• use avx2 for Add without broadcast and when inputs are uint8_t (pytorch#25098)

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• Use the EmbeddingLookup API which takes the offsets instead of lengths (pytorch#24945)

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Commits on Aug 23, 2019

• print padding_mode for Conv modules if not zeros (pytorch#23996)

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• Support lowering of fp16 weights

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• Revert "per channel quantization support (pytorch#24936)" (pytorch#25131)

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• move some methods into function.cpp (pytorch#25119)

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• Add a skip_override option to should_run_job.py (pytorch#25118)

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• add some sparse tensor ops support in TorchScript (pytorch#24967)

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