From 70ad61972d4e7b5ff69e9f3b2924de0df462e6ee Mon Sep 17 00:00:00 2001 From: Michele Di Giorgio Date: Fri, 6 Sep 2019 17:51:37 +0100 Subject: COMPMID-2635: Add support for QASYMM8 in CPPBoxWithNonMaximaSuppressionLimit Change-Id: Ife35cf865e6573ff7f921eb0b39af89dbf0f5dda Signed-off-by: Michele Di Giorgio Reviewed-on: https://review.mlplatform.org/c/1873 Tested-by: Arm Jenkins Reviewed-by: Pablo Marquez Comments-Addressed: Arm Jenkins --- .../CPPBoxWithNonMaximaSuppressionLimitKernel.cpp | 1 + .../CPPBoxWithNonMaximaSuppressionLimit.cpp | 226 ++++++++++++++++++++- 2 files changed, 220 insertions(+), 7 deletions(-) (limited to 'src') diff --git a/src/core/CPP/kernels/CPPBoxWithNonMaximaSuppressionLimitKernel.cpp b/src/core/CPP/kernels/CPPBoxWithNonMaximaSuppressionLimitKernel.cpp index 02150ff275..62568b4b45 100644 --- a/src/core/CPP/kernels/CPPBoxWithNonMaximaSuppressionLimitKernel.cpp +++ b/src/core/CPP/kernels/CPPBoxWithNonMaximaSuppressionLimitKernel.cpp @@ -351,6 +351,7 @@ void CPPBoxWithNonMaximaSuppressionLimitKernel::configure(const ITensor *scores_ { ARM_COMPUTE_ERROR_ON_NULLPTR(scores_in, boxes_in, scores_out, boxes_out, classes); ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(scores_in, 1, DataType::F16, DataType::F32); + ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(scores_in, boxes_in, scores_out); const unsigned int num_classes = scores_in->info()->dimension(0); ARM_COMPUTE_UNUSED(num_classes); diff --git a/src/runtime/CPP/functions/CPPBoxWithNonMaximaSuppressionLimit.cpp b/src/runtime/CPP/functions/CPPBoxWithNonMaximaSuppressionLimit.cpp index 2e10152793..158f45a320 100644 --- a/src/runtime/CPP/functions/CPPBoxWithNonMaximaSuppressionLimit.cpp +++ b/src/runtime/CPP/functions/CPPBoxWithNonMaximaSuppressionLimit.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018 ARM Limited. + * Copyright (c) 2018-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -24,14 +24,226 @@ #include "arm_compute/runtime/CPP/functions/CPPBoxWithNonMaximaSuppressionLimit.h" #include "arm_compute/core/CPP/kernels/CPPBoxWithNonMaximaSuppressionLimitKernel.h" -#include "support/ToolchainSupport.h" +#include "arm_compute/runtime/Scheduler.h" -using namespace arm_compute; +namespace arm_compute +{ +namespace +{ +void dequantize_tensor(const ITensor *input, ITensor *output, DataType data_type) +{ + const UniformQuantizationInfo qinfo = input->info()->quantization_info().uniform(); + + Window window; + window.use_tensor_dimensions(input->info()->tensor_shape()); + Iterator input_it(input, window); + Iterator output_it(output, window); + + switch(data_type) + { + case DataType::QASYMM8: + execute_window_loop(window, [&](const Coordinates &) + { + *reinterpret_cast(output_it.ptr()) = dequantize(*reinterpret_cast(input_it.ptr()), qinfo.scale, qinfo.offset); + }, + input_it, output_it); + break; + case DataType::QASYMM16: + execute_window_loop(window, [&](const Coordinates &) + { + *reinterpret_cast(output_it.ptr()) = dequantize(*reinterpret_cast(input_it.ptr()), qinfo.scale, qinfo.offset); + }, + input_it, output_it); + break; + default: + ARM_COMPUTE_ERROR("Unsupported data type"); + } +} + +void quantize_tensor(const ITensor *input, ITensor *output, DataType data_type) +{ + const UniformQuantizationInfo qinfo = input->info()->quantization_info().uniform(); + + Window window; + window.use_tensor_dimensions(input->info()->tensor_shape()); + Iterator input_it(input, window); + Iterator output_it(output, window); + + switch(data_type) + { + case DataType::QASYMM8: + execute_window_loop(window, [&](const Coordinates &) + { + *reinterpret_cast(output_it.ptr()) = quantize_qasymm8(*reinterpret_cast(input_it.ptr()), qinfo); + }, + input_it, output_it); + break; + case DataType::QASYMM16: + execute_window_loop(window, [&](const Coordinates &) + { + *reinterpret_cast(output_it.ptr()) = quantize_qasymm16(*reinterpret_cast(input_it.ptr()), qinfo); + }, + input_it, output_it); + break; + default: + ARM_COMPUTE_ERROR("Unsupported data type"); + } +} +} // namespace + +CPPBoxWithNonMaximaSuppressionLimit::CPPBoxWithNonMaximaSuppressionLimit(std::shared_ptr memory_manager) + : _memory_group(std::move(memory_manager)), + _box_with_nms_limit_kernel(), + _scores_in(), + _boxes_in(), + _batch_splits_in(), + _scores_out(), + _boxes_out(), + _classes(), + _batch_splits_out(), + _keeps(), + _keeps_size(), + _scores_in_f32(), + _boxes_in_f32(), + _batch_splits_in_f32(), + _scores_out_f32(), + _boxes_out_f32(), + _classes_f32(), + _batch_splits_out_f32(), + _keeps_f32(), + _keeps_size_f32(), + _is_qasymm8(false) +{ +} void CPPBoxWithNonMaximaSuppressionLimit::configure(const ITensor *scores_in, const ITensor *boxes_in, const ITensor *batch_splits_in, ITensor *scores_out, ITensor *boxes_out, ITensor *classes, ITensor *batch_splits_out, ITensor *keeps, ITensor *keeps_size, const BoxNMSLimitInfo info) { - auto k = arm_compute::support::cpp14::make_unique(); - k->configure(scores_in, boxes_in, batch_splits_in, scores_out, boxes_out, classes, batch_splits_out, keeps, keeps_size, info); - _kernel = std::move(k); -} \ No newline at end of file + ARM_COMPUTE_ERROR_ON_NULLPTR(scores_in, boxes_in, batch_splits_in, scores_out, boxes_out, classes); + + _is_qasymm8 = scores_in->info()->data_type() == DataType::QASYMM8; + + _scores_in = scores_in; + _boxes_in = boxes_in; + _batch_splits_in = batch_splits_in; + _scores_out = scores_out; + _boxes_out = boxes_out; + _classes = classes; + _batch_splits_out = batch_splits_out; + _keeps = keeps; + _keeps_size = keeps_size; + + if(_is_qasymm8) + { + // Manage intermediate buffers + _memory_group.manage(&_scores_in_f32); + _memory_group.manage(&_boxes_in_f32); + _memory_group.manage(&_batch_splits_in_f32); + _memory_group.manage(&_scores_out_f32); + _memory_group.manage(&_boxes_out_f32); + _memory_group.manage(&_classes_f32); + _scores_in_f32.allocator()->init(scores_in->info()->clone()->set_data_type(DataType::F32)); + _boxes_in_f32.allocator()->init(boxes_in->info()->clone()->set_data_type(DataType::F32)); + _batch_splits_in_f32.allocator()->init(batch_splits_in->info()->clone()->set_data_type(DataType::F32)); + _scores_out_f32.allocator()->init(scores_out->info()->clone()->set_data_type(DataType::F32)); + _boxes_out_f32.allocator()->init(boxes_out->info()->clone()->set_data_type(DataType::F32)); + _classes_f32.allocator()->init(classes->info()->clone()->set_data_type(DataType::F32)); + if(batch_splits_out != nullptr) + { + _memory_group.manage(&_batch_splits_out_f32); + _batch_splits_out_f32.allocator()->init(batch_splits_out->info()->clone()->set_data_type(DataType::F32)); + } + if(keeps != nullptr) + { + _memory_group.manage(&_keeps_f32); + _keeps_f32.allocator()->init(keeps->info()->clone()->set_data_type(DataType::F32)); + } + if(keeps_size != nullptr) + { + _memory_group.manage(&_keeps_size_f32); + _keeps_size_f32.allocator()->init(keeps_size->info()->clone()->set_data_type(DataType::F32)); + } + + _box_with_nms_limit_kernel.configure(&_scores_in_f32, &_boxes_in_f32, &_batch_splits_in_f32, &_scores_out_f32, &_boxes_out_f32, &_classes_f32, + (batch_splits_out != nullptr) ? &_batch_splits_out_f32 : nullptr, (keeps != nullptr) ? &_keeps_f32 : nullptr, + (keeps_size != nullptr) ? &_keeps_size_f32 : nullptr, info); + } + else + { + _box_with_nms_limit_kernel.configure(scores_in, boxes_in, batch_splits_in, scores_out, boxes_out, classes, batch_splits_out, keeps, keeps_size, info); + } + + if(_is_qasymm8) + { + _scores_in_f32.allocator()->allocate(); + _boxes_in_f32.allocator()->allocate(); + _batch_splits_in_f32.allocator()->allocate(); + _scores_out_f32.allocator()->allocate(); + _boxes_out_f32.allocator()->allocate(); + _classes_f32.allocator()->allocate(); + if(batch_splits_out != nullptr) + { + _batch_splits_out_f32.allocator()->allocate(); + } + if(keeps != nullptr) + { + _keeps_f32.allocator()->allocate(); + } + if(keeps_size != nullptr) + { + _keeps_size_f32.allocator()->allocate(); + } + } +} + +Status validate(const ITensorInfo *scores_in, const ITensorInfo *boxes_in, const ITensorInfo *batch_splits_in, const ITensorInfo *scores_out, const ITensorInfo *boxes_out, const ITensorInfo *classes, + const ITensorInfo *batch_splits_out, const ITensorInfo *keeps, const ITensorInfo *keeps_size, const BoxNMSLimitInfo info) +{ + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(scores_in, boxes_in, batch_splits_in, scores_out, boxes_out, classes); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(scores_in, 1, DataType::QASYMM8, DataType::F16, DataType::F32); + + const bool is_qasymm8 = scores_in->data_type() == DataType::QASYMM8; + if(is_qasymm8) + { + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(boxes_in, 1, DataType::QASYMM16); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(boxes_in, boxes_out); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(boxes_in, boxes_out); + const UniformQuantizationInfo boxes_qinfo = boxes_in->quantization_info().uniform(); + ARM_COMPUTE_RETURN_ERROR_ON(boxes_qinfo.scale != 0.125f); + ARM_COMPUTE_RETURN_ERROR_ON(boxes_qinfo.offset != 0); + } + + return Status{}; +} + +void CPPBoxWithNonMaximaSuppressionLimit::run() +{ + if(_is_qasymm8) + { + dequantize_tensor(_scores_in, &_scores_in_f32, _scores_in->info()->data_type()); + dequantize_tensor(_boxes_in, &_boxes_in_f32, _boxes_in->info()->data_type()); + dequantize_tensor(_batch_splits_in, &_batch_splits_in_f32, _batch_splits_in->info()->data_type()); + } + + Scheduler::get().schedule(&_box_with_nms_limit_kernel, Window::DimY); + + if(_is_qasymm8) + { + quantize_tensor(&_scores_out_f32, _scores_out, _scores_out->info()->data_type()); + quantize_tensor(&_boxes_out_f32, _boxes_out, _boxes_out->info()->data_type()); + quantize_tensor(&_classes_f32, _classes, _classes->info()->data_type()); + if(_batch_splits_out != nullptr) + { + quantize_tensor(&_batch_splits_out_f32, _batch_splits_out, _batch_splits_out->info()->data_type()); + } + if(_keeps != nullptr) + { + quantize_tensor(&_keeps_f32, _keeps, _keeps->info()->data_type()); + } + if(_keeps_size != nullptr) + { + quantize_tensor(&_keeps_size_f32, _keeps_size, _keeps_size->info()->data_type()); + } + } +} +} // namespace arm_compute -- cgit v1.2.1