From 37d080f2f11cfd734104b76512e1fb191486216e Mon Sep 17 00:00:00 2001 From: Georgios Pinitas Date: Fri, 21 Jun 2019 18:43:12 +0100 Subject: COMPMID-2378: Sanitize GEMM configuration for NEON Change-Id: I7859b82b2059e14685f8792424648ac5eacd67f1 Signed-off-by: Georgios Pinitas Reviewed-on: https://review.mlplatform.org/c/1418 Comments-Addressed: Arm Jenkins Reviewed-by: Michele Di Giorgio Reviewed-by: Michalis Spyrou Tested-by: Arm Jenkins --- .../NEON/kernels/assembly/INEGEMMWrapperKernel.h | 18 +++---- .../NEGEMMInterleavedMatrixMultiplyWrapper.h | 55 +++++++++++++--------- .../assembly/NEGEMMInterleavedTransformAWrapper.h | 38 ++++++++------- 3 files changed, 62 insertions(+), 49 deletions(-) (limited to 'arm_compute/core/NEON') diff --git a/arm_compute/core/NEON/kernels/assembly/INEGEMMWrapperKernel.h b/arm_compute/core/NEON/kernels/assembly/INEGEMMWrapperKernel.h index 63178a738a..352f73d7f1 100644 --- a/arm_compute/core/NEON/kernels/assembly/INEGEMMWrapperKernel.h +++ b/arm_compute/core/NEON/kernels/assembly/INEGEMMWrapperKernel.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018 ARM Limited. + * Copyright (c) 2018-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -45,7 +45,7 @@ public: unsigned int multis{ 0 }; /**< Number of "multi" GEMMs (unique A, B and C). */ }; - static Params extract_parameters(const ITensor *a, const ITensor *b, const ITensor *c); + static Params extract_parameters(const ITensor *a, const ITensor *b, const ITensor *c, const GEMMInfo &gemm_info); /** Constructor */ INEGEMMWrapperKernel(); @@ -61,13 +61,14 @@ public: * * @note The input and output tensor must have the same dimensions * - * @param[in] a Input tensor (Matrix A) - * @param[in] b Input tensor (Matrix B) - * @param[out] c Output tensor to store the result of matrix multiplication. Data type supported: same as @p input0. - * @param[in] alpha Scalar multiplier to apply to AB matrix product. - * @param[in] beta Scalar multiplier to apply to input C matrix before adding product. + * @param[in] a Input tensor (Matrix A) + * @param[in] b Input tensor (Matrix B) + * @param[out] c Output tensor to store the result of matrix multiplication. Data type supported: same as @p input0. + * @param[in] alpha Scalar multiplier to apply to AB matrix product. + * @param[in] beta Scalar multiplier to apply to input C matrix before adding product. + * @param[in] gemm_info GEMM meta-data */ - void configure(const ITensor *a, const ITensor *b, ITensor *c, float alpha, float beta); + void configure(const ITensor *a, const ITensor *b, ITensor *c, float alpha, float beta, const GEMMInfo &gemm_info); // Inherited methods overridden: void run(const Window &window, const ThreadInfo &info) override; @@ -95,6 +96,7 @@ protected: const ITensor *_b; ITensor *_c; Params _params; + GEMMInfo _gemm_info; private: Window _window3d; diff --git a/arm_compute/core/NEON/kernels/assembly/NEGEMMInterleavedMatrixMultiplyWrapper.h b/arm_compute/core/NEON/kernels/assembly/NEGEMMInterleavedMatrixMultiplyWrapper.h index e2b849aa3d..40b6f5da39 100644 --- a/arm_compute/core/NEON/kernels/assembly/NEGEMMInterleavedMatrixMultiplyWrapper.h +++ b/arm_compute/core/NEON/kernels/assembly/NEGEMMInterleavedMatrixMultiplyWrapper.h @@ -95,31 +95,32 @@ class NEGEMMInterleavedMatrixMultiplyWrapperTemplate : public NEGEMMInterleavedM public: /** Configure the matrix multiplication: C = alpha * A * B + beta * C * - * @param[in] prepared_a Already reshaped matrix A. - * @param[in] transformed_b Already reshaped matrix B. - * @param[out] tmp_c Temporary buffer to be used to store intermediate results. - * @param[in,out] c Result matrix C. - * @param[in] block_walker Window containing iteration information for the M and batch dimensions. - * @param[in] block_sizes Block sizes to use for the matrix multiplication (A & B must have been reshaped using these same block sizes). - * @param[in] params M, N, K sizes. - * @param[in] is_pretransposed Is B also pretransposed ? - * @param[in] alpha Alpha value - * @param[in] beta Beta value - * @param[in] max_num_threads Maximum number of threads that might be used for the calculations. + * @param[in] prepared_a Already reshaped matrix A. + * @param[in] transformed_b Already reshaped matrix B. + * @param[out] tmp_c Temporary buffer to be used to store intermediate results. + * @param[in,out] c Result matrix C. + * @param[in] block_walker Window containing iteration information for the M and batch dimensions. + * @param[in] block_sizes Block sizes to use for the matrix multiplication (A & B must have been reshaped using these same block sizes). + * @param[in] params M, N, K sizes. + * @param[in] gemm_info GEMM meta-data + * @param[in] alpha Alpha value + * @param[in] beta Beta value + * @param[in] max_num_threads Maximum number of threads that might be used for the calculations. */ void configure(const ITensor *prepared_a, const ITensor *transformed_b, ITensor *tmp_c, ITensor *c, const Window &block_walker, const BlockSizes &block_sizes, - const INEGEMMWrapperKernel::Params ¶ms, bool b_is_pretransposed, float alpha, float beta, unsigned int max_num_threads) + const INEGEMMWrapperKernel::Params ¶ms, const GEMMInfo &gemm_info, float alpha, float beta, unsigned int max_num_threads) { - _prepared_a = prepared_a; - _transformed_b = transformed_b; - _tmp_c = tmp_c; - _c = c; - _block_walker = block_walker; - _block_sizes = block_sizes; - _params = params; - _b_is_pretransposed = b_is_pretransposed; - _alpha = alpha; - _beta = beta; + _prepared_a = prepared_a; + _transformed_b = transformed_b; + _tmp_c = tmp_c; + _c = c; + _block_walker = block_walker; + _block_sizes = block_sizes; + _params = params; + _b_is_pretransposed = gemm_info.pretranpose_B(); + _reinterpret_c_as_3d = gemm_info.depth_output_gemm3d() != 0; + _alpha = alpha; + _beta = beta; auto_init_if_empty(*_tmp_c->info(), c->info()->clone()->set_tensor_shape(TensorShape{ _block_sizes.x_block * strategy::out_height(), max_num_threads })); } @@ -133,6 +134,14 @@ public: TensorAccessor c(*_c); TensorAccessor tmp_c(*_tmp_c); + // Handle 3d output re-interpretation + if(_reinterpret_c_as_3d) + { + Strides c_strides_as_3d = _c->info()->strides_in_bytes(); + c_strides_as_3d.remove(Window::DimZ); + c.set_strides(c_strides_as_3d); + } + int prev_batch = -1; typename strategy::operand_type *a_ptr = nullptr; auto window_iterator = arm_compute::create_window_iterator(batch_window, start_offset, end_offset, [&](const Coordinates & id) @@ -216,9 +225,9 @@ private: INEGEMMWrapperKernel::Params _params{}; Window _block_walker{}; bool _b_is_pretransposed{ false }; + bool _reinterpret_c_as_3d{ false }; typename strategy::result_type _alpha{}; typename strategy::result_type _beta{}; }; - } // namespace arm_compute #endif /* __ARM_COMPUTE_NEGEMMINTERLEAVEDMATRIXMULTIPLYWRAPPER_H__ */ diff --git a/arm_compute/core/NEON/kernels/assembly/NEGEMMInterleavedTransformAWrapper.h b/arm_compute/core/NEON/kernels/assembly/NEGEMMInterleavedTransformAWrapper.h index 5d6cd02398..b18d327339 100644 --- a/arm_compute/core/NEON/kernels/assembly/NEGEMMInterleavedTransformAWrapper.h +++ b/arm_compute/core/NEON/kernels/assembly/NEGEMMInterleavedTransformAWrapper.h @@ -87,20 +87,22 @@ class NEGEMMInterleavedTransformAWrapperTemplate : public NEGEMMInterleavedTrans public: /** Configure the reshape A routine. * - * @param[in] a Input matrix A. - * @param[out] transformed_a Reshaped matrix A. - * @param[in] transpose_a Also transpose A ? - * @param[in] block_walker Window representing the layout of the matrix's blocks - * @param[in] params M, N, K sizes. + * @param[in] a Input matrix A. + * @param[out] transformed_a Reshaped matrix A. + * @param[in] transpose_a Also transpose A ? + * @param[in] reinterpret_a_as_3d Re-interpret as 3D ? + * @param[in] block_walker Window representing the layout of the matrix's blocks + * @param[in] params M, N, K sizes. */ - void configure(const ITensor *a, ITensor *transformed_a, bool transpose_a, const Window &block_walker, const INEGEMMWrapperKernel::Params ¶ms) + void configure(const ITensor *a, ITensor *transformed_a, bool transpose_a, bool reinterpret_a_as_3d, const Window &block_walker, const INEGEMMWrapperKernel::Params ¶ms) { - _a = a; - _transformed_a = transformed_a; - _transpose_a = transpose_a; - _Ksize = params.K; - _Msize = params.M; - _k_multi_window = block_walker.shift_dimensions(1); // block_walker contains (M,K,Multi) --> shift by 1 to get rid of the "M" dimension + _a = a; + _transformed_a = transformed_a; + _transpose_a = transpose_a; + _reinterpret_a_as_3d = reinterpret_a_as_3d; + _Ksize = params.K; + _Msize = params.M; + _k_multi_window = block_walker.shift_dimensions(1); // block_walker contains (M,K,Multi) --> shift by 1 to get rid of the "M" dimension } // Inherited methods overridden: @@ -110,12 +112,12 @@ public: TensorAccessor a(*_a); TensorAccessor transformed_a(*_transformed_a); - if(_a->info()->data_layout() == DataLayout::NHWC) + // Handle 3d input re-interpretation + if(_reinterpret_a_as_3d) { - // In the case of NHWC we want to interpret the output shape as 3D. Thus, the batch stride for A is - // the relevant multiple of the row stride. - const size_t nhwc_batch_stride = _a->info()->strides_in_bytes().y() * _Msize; - a.set_stride(2, nhwc_batch_stride); + Strides a_strides_as_3d = _a->info()->strides_in_bytes(); + a_strides_as_3d.remove(Window::DimZ); + a.set_strides(a_strides_as_3d); } unsigned int last_m = 0; @@ -164,8 +166,8 @@ private: unsigned int _Msize{ 0 }; unsigned int _Ksize{ 0 }; bool _transpose_a{ false }; + bool _reinterpret_a_as_3d{ false }; Window _k_multi_window{}; }; - } // namespace arm_compute #endif /* __ARM_COMPUTE_NEGEMMINTERLEAVEDTRANSFORMAWRAPPER_H__ */ -- cgit v1.2.1