From bb54e4e40b7b08c509e234cd91ebd3087af66c23 Mon Sep 17 00:00:00 2001 From: Giorgio Arena Date: Thu, 5 Apr 2018 17:20:34 +0100 Subject: COMPMID-797 Integrate Mobilenet QASYMM8 with new graph. Change-Id: I4df63ec2f4eb27a8a6eec2bea27741bf8dec6910 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/126966 Tested-by: Jenkins Reviewed-by: Anthony Barbier --- .../CL/functions/CLGEMMLowpMatrixMultiplyCore.cpp | 10 ++++++++-- src/runtime/NEON/functions/NEGEMM.cpp | 5 ++++- .../NEON/functions/NEGEMMConvolutionLayer.cpp | 16 +++++----------- .../NEON/functions/NEGEMMLowpMatrixMultiplyCore.cpp | 20 ++++++++++++++------ 4 files changed, 31 insertions(+), 20 deletions(-) (limited to 'src/runtime') diff --git a/src/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.cpp b/src/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.cpp index 5f747bc477..711b006ede 100644 --- a/src/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.cpp +++ b/src/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.cpp @@ -102,7 +102,10 @@ void CLGEMMLowpMatrixMultiplyCore::configure(const ICLTensor *a, const ICLTensor matrix_b = &_tmp_b; _memory_group.manage(&_tmp_a); - _memory_group.manage(&_tmp_b); + if(!_reshape_b_only_on_first_run) + { + _memory_group.manage(&_tmp_b); + } // Configure interleave kernel _mtx_a_reshape_kernel.configure(a, &_tmp_a, mult_interleave4x4_height); @@ -119,7 +122,10 @@ void CLGEMMLowpMatrixMultiplyCore::configure(const ICLTensor *a, const ICLTensor { TensorInfo info_vector_sum_col(compute_reductionA_shape(*b->info()), 1, DataType::S32); _vector_sum_col.allocator()->init(info_vector_sum_col); - _memory_group.manage(&_vector_sum_col); + if(!_reshape_b_only_on_first_run) + { + _memory_group.manage(&_vector_sum_col); + } // Configure Matrix B reduction kernel _mtx_b_reduction_kernel.configure(b, &_vector_sum_col); diff --git a/src/runtime/NEON/functions/NEGEMM.cpp b/src/runtime/NEON/functions/NEGEMM.cpp index 18e6e919c3..e0859be93e 100644 --- a/src/runtime/NEON/functions/NEGEMM.cpp +++ b/src/runtime/NEON/functions/NEGEMM.cpp @@ -107,7 +107,10 @@ void NEGEMM::configure(const ITensor *a, const ITensor *b, const ITensor *c, ITe // Manage intermediate buffers _memory_group.manage(&_tmp_a); - _memory_group.manage(&_tmp_b); + if(!_reshape_b_only_on_first_run) + { + _memory_group.manage(&_tmp_b); + } int m = a->info()->dimension(1); int n = b->info()->dimension(0); diff --git a/src/runtime/NEON/functions/NEGEMMConvolutionLayer.cpp b/src/runtime/NEON/functions/NEGEMMConvolutionLayer.cpp index 7f25c2e717..3c48d691ed 100644 --- a/src/runtime/NEON/functions/NEGEMMConvolutionLayer.cpp +++ b/src/runtime/NEON/functions/NEGEMMConvolutionLayer.cpp @@ -109,14 +109,6 @@ Status NEConvolutionLayerReshapeWeights::validate(const ITensorInfo *weights, co ARM_COMPUTE_RETURN_ERROR_ON(biases->num_dimensions() > 1); } - // Checks performed when biases are present - if(append_bias) - { - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(weights, biases); - ARM_COMPUTE_RETURN_ERROR_ON(biases->dimension(0) != weights->dimension(3)); - ARM_COMPUTE_RETURN_ERROR_ON(biases->num_dimensions() > 1); - } - if(transpose1xW) { TensorInfo weights_reshaped = weights->clone()->set_tensor_shape(get_reshaped_weights_shape(weights, append_bias)); @@ -344,7 +336,7 @@ void NEGEMMConvolutionLayer::configure(const ITensor *input, const ITensor *weig _memory_group.manage(&_input_im2col_reshaped); // Create tensor (interleave) to prepare input tensor for GEMM - if(!_is_fully_connected_convolution && !run_optimised) + if(!_is_fully_connected_convolution && !run_optimised && _is_interleaved) { TensorShape shape_interleaved(shape_im2col); shape_interleaved.set(0, shape_interleaved.x() * 4); @@ -362,7 +354,9 @@ void NEGEMMConvolutionLayer::configure(const ITensor *input, const ITensor *weig TensorInfo info_gemm(shape_gemm, 1, gemm_data_type, input->info()->fixed_point_position()); info_gemm.set_quantization_info(output->info()->quantization_info()); _gemm_output.allocator()->init(info_gemm); - _memory_group.manage(&_gemm_output); + + // FIXME: enabling memory manager for _gemm_output gives incorrect results (maybe bound to the assembly kernel in GEMMLowp?) + // _memory_group.manage(&_gemm_output); // Configure kernels // Configure im2col @@ -491,7 +485,7 @@ Status NEGEMMConvolutionLayer::validate(const ITensorInfo *input, const ITensorI reshaped_weights->set_tensor_shape(get_reshaped_weights_shape_conv(weights, append_bias, is_fully_connected_convolution)); ARM_COMPUTE_RETURN_ON_ERROR(NEConvolutionLayerReshapeWeights::validate(weights, biases, reshaped_weights.get(), !is_fully_connected_convolution /* 1xW transpose */)); } - else + else if(!is_quantized) { TensorShape reshaped_weights_shape; diff --git a/src/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.cpp b/src/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.cpp index 7372c6ca57..cbec73fc31 100644 --- a/src/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.cpp +++ b/src/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.cpp @@ -43,19 +43,19 @@ using namespace arm_compute::misc::shape_calculator; NEGEMMLowpMatrixMultiplyCore::NEGEMMLowpMatrixMultiplyCore(std::shared_ptr memory_manager) : _memory_group(std::move(memory_manager)), _asm_glue_unsigned(), _asm_glue_signed(), _mm_kernel(nullptr), _mtx_a_reshape_kernel(nullptr), _mtx_b_reshape_kernel(nullptr), _mtx_a_reduction_kernel(), _mtx_b_reduction_kernel(), _offset_contribution_kernel(), _vector_sum_col(), _vector_sum_row(), _tmp_a(), _tmp_b(), _workspace(), _a_offset(0), _b_offset(0), _run_vector_matrix_multiplication(false), - _dot_product_path(false) + _dot_product_path(false), _is_first_run(true), _reshape_b_only_on_first_run(false) { } void NEGEMMLowpMatrixMultiplyCore::configure(const ITensor *a, const ITensor *b, ITensor *output, const GEMMInfo &gemm_info) { ARM_COMPUTE_ERROR_ON_NULLPTR(a, b, output); - ARM_COMPUTE_UNUSED(gemm_info); ARM_COMPUTE_ERROR_THROW_ON(NEGEMMLowpMatrixMultiplyCore::validate(a->info(), b->info(), output->info(), gemm_info)); _a_offset = a->info()->quantization_info().offset; _b_offset = b->info()->quantization_info().offset; _run_vector_matrix_multiplication = a->info()->dimension(1) < 2; + _reshape_b_only_on_first_run = gemm_info.reshape_b_only_on_first_run(); #ifdef __aarch64__ switch(a->info()->data_type()) @@ -98,7 +98,10 @@ void NEGEMMLowpMatrixMultiplyCore::configure(const ITensor *a, const ITensor *b, _tmp_a.allocator()->init(info_a); _tmp_b.allocator()->init(info_b); _memory_group.manage(&_tmp_a); - _memory_group.manage(&_tmp_b); + if(!_reshape_b_only_on_first_run) + { + _memory_group.manage(&_tmp_b); + } // Configure interleave kernel { @@ -129,7 +132,10 @@ void NEGEMMLowpMatrixMultiplyCore::configure(const ITensor *a, const ITensor *b, TensorInfo info_vector_sum_col(compute_reductionA_shape(*b->info()), 1, DataType::S32); _vector_sum_col.allocator()->init(info_vector_sum_col); - _memory_group.manage(&_vector_sum_col); + if(!_reshape_b_only_on_first_run) + { + _memory_group.manage(&_vector_sum_col); + } // Configure Matrix B reduction kernel _mtx_b_reduction_kernel.configure(b, &_vector_sum_col, a->info()->dimension(0), false); @@ -252,7 +258,7 @@ void NEGEMMLowpMatrixMultiplyCore::run() NEScheduler::get().schedule(_mtx_a_reshape_kernel.get(), Window::DimY); } - if(_mtx_b_reshape_kernel) + if(_mtx_b_reshape_kernel && (_is_first_run || !_reshape_b_only_on_first_run)) { NEScheduler::get().schedule(_mtx_b_reshape_kernel.get(), Window::DimY); } @@ -278,7 +284,7 @@ void NEGEMMLowpMatrixMultiplyCore::run() } // Run matrix B reduction kernel only if _a_offset is not equal to 0 - if(_a_offset != 0) + if(_a_offset != 0 && (_is_first_run || !_reshape_b_only_on_first_run)) { NEScheduler::get().schedule(&_mtx_b_reduction_kernel, Window::DimX); } @@ -287,4 +293,6 @@ void NEGEMMLowpMatrixMultiplyCore::run() NEScheduler::get().schedule(&_offset_contribution_kernel, Window::DimY); _memory_group.release(); + + _is_first_run = false; } -- cgit v1.2.1