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Summary: Bugs: 1) would introduce -I* in compile commands 2) wouldn't hipify source code directly in build_dir, only one level down or more Pull Request resolved: #50703 Reviewed By: mrshenli Differential Revision: D25949070 Pulled By: ngimel fbshipit-source-id: 018c2a056b68019a922e20e5db2eb8435ad147fe
Summary: This is an automated pull request to update the first-party submodule for [pytorch/tensorpipe](https://github.com/pytorch/tensorpipe). New submodule commit: pytorch/tensorpipe@6c8ed2e Pull Request resolved: #50765 Test Plan: Ensure that CI jobs succeed on GitHub before landing. Reviewed By: mrshenli Differential Revision: D25960813 fbshipit-source-id: 80b4e48ef04f22f750a2eb049f5f7114715c0a1e
Summary: Pull Request resolved: #50639 Test Plan: Imported from OSS Reviewed By: ansley Differential Revision: D25934142 Pulled By: jamesr66a fbshipit-source-id: de9053d4f92a7a2f4f573378837ff5ae78e539b1
Summary:
Fixes #{issue number}
Pull Request resolved: #50088
Reviewed By: mrshenli
Differential Revision: D25894003
Pulled By: ezyang
fbshipit-source-id: 93688c33b2f9a355c331d6edb3e402935223f75b
Summary: Fixes regression introduced by #50400 `cmake_dependent_option` semantic is following (see https://cmake.org/cmake/help/v3.19/module/CMakeDependentOption.html); `cmake_dependent_option(<option> "<help_text>" <value> <depends> <force>)` I.e. depends should be true for CPU_INTEL or CPU_AARCH64 but default value should be ON only if CPU_INTEL is true Pull Request resolved: #50782 Reviewed By: xuzhao9 Differential Revision: D25966509 Pulled By: malfet fbshipit-source-id: c891cd9234311875762403f7125d0c3803bb0e65
Summary: Pull Request resolved: #50767 The native signature for optional tensor arguments wrongly produced "Tensor" instead of "optional<Tensor>". We didn't notice this because all internal ops currently use hacky_wrapper, and for hacky_wrapper, "Tensor" is correct. This PR fixes that and ports one op (batch_norm) to not use hacky_wrapper anymore as a proof of fix. ghstack-source-id: 120017543 Test Plan: waitforsandcastle Reviewed By: bhosmer Differential Revision: D25960941 fbshipit-source-id: ca6fe133109b5d85cff52390792cf552f12d9590
#50778) Summary: Pull Request resolved: #50778 - use tensor shapes from ctr_mobilefeed merge net - use pt cat out-variant for a fairer comparison otherwise benchmark includes time to construct result tensor Test Plan: turbo off, devbig machine ``` MKL_NUM_THREADS=1 OMP_NUM_THREADS=1 buck-out/gen/caffe2/benchmarks/operator_benchmark/c2/concat_test.par --tag_filter=static_runtime ``` ``` # ---------------------------------------- # PyTorch/Caffe2 Operator Micro-benchmarks # ---------------------------------------- # Tag : static_runtime # Benchmarking Caffe2: concat # Name: concat_sizes(1,40)_N5_axis1_add_axis0_devicecpu_dtypefloat # Input: sizes: (1, 40), N: 5, axis: 1, add_axis: 0, device: cpu, dtype: float Forward Execution Time (us) : 0.619 # Benchmarking Caffe2: concat # Name: concat_sizes[(1,160),(1,14)]_N-1_axis1_add_axis0_devicecpu_dtypefloat # Input: sizes: [(1, 160), (1, 14)], N: -1, axis: 1, add_axis: 0, device: cpu, dtype: float Forward Execution Time (us) : 0.369 # Benchmarking Caffe2: concat # Name: concat_sizes[(1,20,40),(1,4,40),(1,5,40)]_N-1_axis1_add_axis0_devicecpu_dtypefloat # Input: sizes: [(1, 20, 40), (1, 4, 40), (1, 5, 40)], N: -1, axis: 1, add_axis: 0, device: cpu, dtype: float Forward Execution Time (us) : 0.590 # Benchmarking Caffe2: concat # Name: concat_sizes[(1,580),(1,174)]_N-1_axis1_add_axis0_devicecpu_dtypefloat # Input: sizes: [(1, 580), (1, 174)], N: -1, axis: 1, add_axis: 0, device: cpu, dtype: float Forward Execution Time (us) : 0.412 # Benchmarking Caffe2: concat # Name: concat_sizes(20,40)_N5_axis1_add_axis0_devicecpu_dtypefloat # Input: sizes: (20, 40), N: 5, axis: 1, add_axis: 0, device: cpu, dtype: float Forward Execution Time (us) : 2.464 # Benchmarking Caffe2: concat # Name: concat_sizes[(20,160),(20,14)]_N-1_axis1_add_axis0_devicecpu_dtypefloat # Input: sizes: [(20, 160), (20, 14)], N: -1, axis: 1, add_axis: 0, device: cpu, dtype: float Forward Execution Time (us) : 1.652 # Benchmarking Caffe2: concat # Name: concat_sizes[(20,20,40),(20,4,40),(20,5,40)]_N-1_axis1_add_axis0_devicecpu_dtypefloat # Input: sizes: [(20, 20, 40), (20, 4, 40), (20, 5, 40)], N: -1, axis: 1, add_axis: 0, device: cpu, dtype: float Forward Execution Time (us) : 9.312 # Benchmarking Caffe2: concat # Name: concat_sizes[(20,580),(20,174)]_N-1_axis1_add_axis0_devicecpu_dtypefloat # Input: sizes: [(20, 580), (20, 174)], N: -1, axis: 1, add_axis: 0, device: cpu, dtype: float Forward Execution Time (us) : 6.532 ``` ``` MKL_NUM_THREADS=1 OMP_NUM_THREADS=1 buck-out/gen/caffe2/benchmarks/operator_benchmark/pt/cat_test.par --tag_filter=static_runtime ``` ``` # ---------------------------------------- # PyTorch/Caffe2 Operator Micro-benchmarks # ---------------------------------------- # Tag : static_runtime # Benchmarking PyTorch: cat # Mode: Eager # Name: cat_sizes[(1,160),(1,14)]_N-1_dim1_cpu # Input: sizes: [(1, 160), (1, 14)], N: -1, dim: 1, device: cpu Forward Execution Time (us) : 3.313 # Benchmarking PyTorch: cat # Mode: Eager # Name: cat_sizes[(1,20,40),(1,4,40),(1,5,40)]_N-1_dim1_cpu # Input: sizes: [(1, 20, 40), (1, 4, 40), (1, 5, 40)], N: -1, dim: 1, device: cpu Forward Execution Time (us) : 3.680 # Benchmarking PyTorch: cat # Mode: Eager # Name: cat_sizes[(1,580),(1,174)]_N-1_dim1_cpu # Input: sizes: [(1, 580), (1, 174)], N: -1, dim: 1, device: cpu Forward Execution Time (us) : 3.452 # Benchmarking PyTorch: cat # Mode: Eager # Name: cat_sizes[(20,160),(20,14)]_N-1_dim1_cpu # Input: sizes: [(20, 160), (20, 14)], N: -1, dim: 1, device: cpu Forward Execution Time (us) : 4.653 # Benchmarking PyTorch: cat # Mode: Eager # Name: cat_sizes[(20,20,40),(20,4,40),(20,5,40)]_N-1_dim1_cpu # Input: sizes: [(20, 20, 40), (20, 4, 40), (20, 5, 40)], N: -1, dim: 1, device: cpu Forward Execution Time (us) : 7.364 # Benchmarking PyTorch: cat # Mode: Eager # Name: cat_sizes[(20,580),(20,174)]_N-1_dim1_cpu # Input: sizes: [(20, 580), (20, 174)], N: -1, dim: 1, device: cpu Forward Execution Time (us) : 7.055 ``` Reviewed By: hlu1 Differential Revision: D25839036 fbshipit-source-id: 7a6a234f41dfcc56246a80141fe0c84f769a5a85
Summary: Pull Request resolved: #50194 **Summary** `ClassType::repr_str()` prints out only the name of a `ClassType`, which is not always enough to disambiguate it. In some situations, two `ClassTypes` are compared and do not match despite having identical names because they are in separate compilation units. In such cases, the error message can seem nonsensical (e.g. `expected type T but found type T`). This commit modifies `ClassType::repr_str()` so that it prints out the address of the type's compilation unit to make these messages less puzzling (e.g. `expected type T (0x239023) but found type T (0x230223)`). **Test Plan** This commit adds a unit test, `ClassTypeTest.IdenticalTypesDifferentCus` that reproduces this situation. **Fixes** This commit fixes #46212. Test Plan: Imported from OSS Reviewed By: tugsbayasgalan Differential Revision: D25933082 Pulled By: SplitInfinity fbshipit-source-id: ec71b6728be816edd6a9c2b2d5075ead98d8bc88
Summary: Pull Request resolved: #50777 Test Plan: Imported from OSS Reviewed By: Chillee Differential Revision: D25966026 Pulled By: jamesr66a fbshipit-source-id: 8e36521eee03eade7e1b602e801229c085b03488
…ps (#50706) Summary: Pull Request resolved: #50706 Add a default CPU implementation for quantized embedding lookup operators. This should enable the ops to execute on mobile as well where we don't have fbgemm. Test Plan: python test/test_quantization.py and CI tests Imported from OSS Reviewed By: vkuzo Differential Revision: D25956842 fbshipit-source-id: 07694888e5e1423b496af1a51494a49558e82152
Summary: Pull Request resolved: #50649 **Summary** Tutorials, documentation and comments are not consistent with the file extension they use for JIT archives. This commit modifies certain instances of `*.pth` in `torch.jit.save` calls with `*.pt`. **Test Plan** Continuous integration. **Fixes** This commit fixes #49660. Test Plan: Imported from OSS Reviewed By: ZolotukhinM Differential Revision: D25961628 Pulled By: SplitInfinity fbshipit-source-id: a40c97954adc7c255569fcec1f389aa78f026d47
Summary: Pull Request resolved: #50676 Test Plan: Imported from OSS Reviewed By: beauby Differential Revision: D25941962 Pulled By: mrshenli fbshipit-source-id: 7d4fd3b4fbd5ae5a0c50ad65605ced9db10ede4a
…49786) Summary: Add a new device type 'XPU' ('xpu' for lower case) to PyTorch. Changes are needed for code related to device model and kernel dispatch, e.g. DeviceType, Backend and DispatchKey etc. #48246 Pull Request resolved: #49786 Reviewed By: mrshenli Differential Revision: D25893962 Pulled By: ezyang fbshipit-source-id: 7ff0a316ee34cf0ed6fc7ead08ecdeb7df4b0052
Test Plan: revert-hammer Differential Revision: D25958987 (2ace4fc) Original commit changeset: aadc065c489b fbshipit-source-id: efd8b7c3cbe03d5ab0afa0d7c695182623285a3a
…or hook running/compilation (#49544) Summary: Pull Request resolved: #49544 Implementation of design laid out in: https://fb.quip.com/MY9gAqlroo0Z Test Plan: Imported from OSS Reviewed By: heitorschueroff Differential Revision: D25771122 Pulled By: Lilyjjo fbshipit-source-id: dc4a8461f71c58ae75144ca1477cd1c0e9f0f325
Summary: Pull Request resolved: #49975 Test Plan: Imported from OSS Reviewed By: heitorschueroff Differential Revision: D25771120 Pulled By: Lilyjjo fbshipit-source-id: 262892cec45b6894bd8c0c20b9cfee43065abc7c
Summary: Pull Request resolved: #49545 Test Plan: Imported from OSS Reviewed By: heitorschueroff Differential Revision: D25771121 Pulled By: Lilyjjo fbshipit-source-id: fe08936d601618010b9c64e2bb769e0b67cb7187
Summary: Pull Request resolved: #49546 Test Plan: Imported from OSS Reviewed By: heitorschueroff Differential Revision: D25771119 Pulled By: Lilyjjo fbshipit-source-id: bf8a8e20f790691d3ff58fa9c8d0d9ab3e8322c4
Summary: Pull Request resolved: #49547 Test Plan: Imported from OSS Reviewed By: heitorschueroff Differential Revision: D25771118 Pulled By: Lilyjjo fbshipit-source-id: cd8a58ff008a1c5d65ccbfbcbcb0214781ece16f
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Fixes #{issue number}