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usr
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local
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lib64
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python3.6
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site-packages
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torch
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include
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ATen
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/usr/local/lib64/python3.6/site-packages/torch/include/ATen
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core/
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cpu/
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detail/
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AccumulateType.h
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ArrayRef.h
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ATen.h
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autocast_mode.h
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Backend.h
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Backtrace.h
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BatchedFallback.h
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BatchedTensorImpl.h
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CompositeExplicitAutogradFunctions.h
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CompositeExplicitAutogradFunctions_inl.h
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Config.h
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Context.h
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cpp_custom_type_hack.h
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CPUApplyUtils.h
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CPUFixedAllocator.h
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CPUFunctions.h
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CPUFunctions_inl.h
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CPUGeneratorImpl.h
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CUDAFunctions.h
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CUDAFunctions_inl.h
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CUDAGeneratorImpl.h
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Device.h
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DeviceGuard.h
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Dimname.h
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DimVector.h
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Dispatch.h
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div_rtn.h
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DLConvertor.h
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DynamicLibrary.h
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ExpandUtils.h
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Formatting.h
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Functions.h
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Generator.h
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InferSize.h
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InitialTensorOptions.h
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Layout.h
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MapAllocator.h
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MatrixRef.h
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MemoryOverlap.h
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MetaFunctions.h
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MetaFunctions_inl.h
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NamedTensor.h
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NamedTensorUtils.h
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NativeFunctions.h
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NativeMetaFunctions.h
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NumericUtils.h
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OpaqueTensorImpl.h
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Operators.h
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OpMathType.h
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Parallel.h
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ParallelNative.h
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ParallelNativeTBB.h
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ParallelOpenMP.h
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PTThreadPool.h
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record_function.h
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RedispatchFunctions.h
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RegistrationDeclarations.h
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SavedTensorHooks.h
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Scalar.h
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ScalarOps.h
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ScalarType.h
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SequenceNumber.h
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SmallVector.h
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SparseCsrTensorImpl.h
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SparseCsrTensorUtils.h
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SparseTensorImpl.h
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SparseTensorUtils.h
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Storage.h
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Tensor.h
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TensorAccessor.h
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TensorGeometry.h
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TensorIndexing.h
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TensorIterator.h
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TensorIteratorInternal.h
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TensorMeta.h
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TensorNames.h
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TensorOperators.h
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TensorOptions.h
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TensorUtils.h
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ThreadLocalState.h
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TracerMode.h
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TypeDefault.h
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Utils.h
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Version.h
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VmapMode.h
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VmapTransforms.h
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WrapDimUtils.h
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WrapDimUtilsMulti.h
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Edit:
/usr/local/lib64/python3.6/site-packages/torch/include/ATen/TensorMeta.h
(2917B)
#pragma once #include <ATen/DimVector.h> #include <c10/core/TensorOptions.h> #include <ATen/core/Dimname.h> namespace at { class Tensor; namespace impl { // Use this to define the prototype for a meta function. There are two // versions; one that takes one argument (just the operator name), or FUNC2 // variant that takes two arguments (operator name and overload name). // // Example usage: // // TORCH_META_FUNC2(add, Tensor) ( // const Tensor& self, const Tensor& other // ) { // ... compute sizes and options ... // set_output(sizes, options); // } // #define TORCH_META_FUNC(name) void structured_##name::meta #define TORCH_META_FUNC2(name, overload) void structured_##name##_##overload::meta // These are versions of TORCH_META_FUNC(2) that include a precompute_out struct as a return value. // They should be used when the kernel in question has precomputed values declared in native_functions.yaml and // the corresponding implementation should return an instance of the aforementioned struct. #define TORCH_PRECOMPUTE_META_FUNC(name) structured_##name::meta_return_ty structured_##name::meta #define TORCH_PRECOMPUTE_META_FUNC2(name, overload) structured_##name##_##overload::meta_return_ty structured_##name##_##overload::meta // Use this to create a precompute struct in a meta function. #define TORCH_PRECOMPUTE_STRUCT(name) structured_##name::precompute_out<> #define TORCH_PRECOMPUTE_STRUCT2(name, overload) structured_##name##_##overload::precompute_out<> // Use this to define the prototype for an implementation. This takes only // one argument, which is the name of the dispatch key entry you're // implementing. // // Example usage: // // TORCH_IMPL_FUNC(add_cpu) ( // Tensor& result, const Tensor& self, const Tensor& other // ) { // ... do the actual implementation ... // } // #define TORCH_IMPL_FUNC(name) void structured_##name::impl // Base class for all structured kernel classes. The set_output virtual // method is varied depending whether or not the operator is // functional/out/inplace, and could also be specialized for CPU/CUDA/etc // (although presently it isn't). // // A notable subclass of this interface is TensorIteratorBase. struct TORCH_API MetaBase { virtual void set_output(int64_t output_idx, IntArrayRef sizes, IntArrayRef strides, TensorOptions options, DimnameList names) = 0; virtual const Tensor& maybe_get_output(int64_t output_idx) = 0; void set_output(IntArrayRef sizes, TensorOptions options) { set_output(0, sizes, {}, options, {}); } void set_output(int64_t output_idx, IntArrayRef sizes, TensorOptions options) { set_output(output_idx, sizes, {}, options, {}); } // Returns a reference to an undefined tensor if there is no presupplied // output const Tensor& maybe_get_output() { return maybe_get_output(0); } virtual ~MetaBase() {} }; } // namespace impl } // namespace at
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