From b412fab0e3c8ec10e104f4d85760898a5b26179c Mon Sep 17 00:00:00 2001 From: Manuel Bottini Date: Mon, 10 Dec 2018 17:40:23 +0000 Subject: COMPMID-1724: CL Implement Prod Change-Id: I17e51f25064b53a8f7e13d6fcbecc14a192de103 Reviewed-on: https://review.mlplatform.org/387 Reviewed-by: Georgios Pinitas Tested-by: Arm Jenkins --- src/runtime/CL/functions/CLReductionOperation.cpp | 100 +++++++++++++--------- 1 file changed, 60 insertions(+), 40 deletions(-) (limited to 'src/runtime/CL') diff --git a/src/runtime/CL/functions/CLReductionOperation.cpp b/src/runtime/CL/functions/CLReductionOperation.cpp index c5447ffd6b..e2dec6b375 100644 --- a/src/runtime/CL/functions/CLReductionOperation.cpp +++ b/src/runtime/CL/functions/CLReductionOperation.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2018 ARM Limited. + * Copyright (c) 2017-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -56,15 +56,19 @@ unsigned int calculate_number_of_stages(const ITensorInfo *input, unsigned int a } // namespace CLReductionOperation::CLReductionOperation(std::shared_ptr memory_manager) - : _memory_group(std::move(memory_manager)), _sums_vector(), _reduction_kernels_vector(), _border_handlers_vector(), _num_of_stages(), _reduction_axis(), _is_quantized() + : _memory_group(std::move(memory_manager)), _results_vector(), _reduction_kernels_vector(), _border_handlers_vector(), _num_of_stages(), _reduction_axis(), _is_serial() { } Status CLReductionOperation::validate(const ITensorInfo *input, const ITensorInfo *output, unsigned int axis, ReductionOperation op) { const unsigned int num_of_stages = calculate_number_of_stages(input, axis); - - if(axis == 0 && !is_data_type_quantized(input->data_type())) + bool is_serial = is_data_type_quantized(input->data_type()) || axis != 0; + if(is_serial) + { + ARM_COMPUTE_RETURN_ON_ERROR(CLReductionOperationKernel::validate(input, output, axis, op)); + } + else { // Create temporary tensor infos auto sums_vector = arm_compute::support::cpp14::make_unique(num_of_stages - 1); @@ -81,17 +85,25 @@ Status CLReductionOperation::validate(const ITensorInfo *input, const ITensorInf } ReductionOperation first_kernel_op; + ReductionOperation intermediate_kernel_op; ReductionOperation last_kernel_op; switch(op) { case ReductionOperation::SUM: case ReductionOperation::MEAN_SUM: - first_kernel_op = ReductionOperation::SUM; - last_kernel_op = op; + first_kernel_op = ReductionOperation::SUM; + intermediate_kernel_op = ReductionOperation::SUM; + last_kernel_op = op; break; case ReductionOperation::SUM_SQUARE: - first_kernel_op = ReductionOperation::SUM_SQUARE; - last_kernel_op = ReductionOperation::SUM; + first_kernel_op = ReductionOperation::SUM_SQUARE; + intermediate_kernel_op = ReductionOperation::SUM; + last_kernel_op = ReductionOperation::SUM; + break; + case ReductionOperation::PROD: + first_kernel_op = ReductionOperation::PROD; + intermediate_kernel_op = ReductionOperation::PROD; + last_kernel_op = ReductionOperation::PROD; break; default: ARM_COMPUTE_ERROR("Not supported"); @@ -103,17 +115,13 @@ Status CLReductionOperation::validate(const ITensorInfo *input, const ITensorInf // Validate ReductionOperation on intermediate stages for(unsigned int i = 1; i < num_of_stages - 1; ++i) { - ARM_COMPUTE_RETURN_ON_ERROR(CLReductionOperationKernel::validate(sums_vector.get() + i - 1, sums_vector.get() + i, axis, ReductionOperation::SUM)); + ARM_COMPUTE_RETURN_ON_ERROR(CLReductionOperationKernel::validate(sums_vector.get() + i - 1, sums_vector.get() + i, axis, intermediate_kernel_op)); } // Validate ReductionOperation on the last stage const unsigned int last_stage = num_of_stages - 1; ARM_COMPUTE_RETURN_ON_ERROR(CLReductionOperationKernel::validate(sums_vector.get() + last_stage - 1, output, axis, last_kernel_op, input->dimension(0))); } - else - { - ARM_COMPUTE_RETURN_ON_ERROR(CLReductionOperationKernel::validate(input, output, axis, op)); - } return Status{}; } @@ -122,65 +130,77 @@ void CLReductionOperation::configure(ICLTensor *input, ICLTensor *output, unsign { _num_of_stages = calculate_number_of_stages(input->info(), axis); _reduction_axis = axis; - _is_quantized = is_data_type_quantized(input->info()->data_type()); + _is_serial = is_data_type_quantized(input->info()->data_type()) || axis != 0; // Configure reduction operation kernels _reduction_kernels_vector = arm_compute::support::cpp14::make_unique(_num_of_stages); // Create temporary tensors - if(axis == 0 && !_is_quantized) + if(_is_serial) + { + _reduction_kernels_vector[0].configure(input, output, axis, op, 0); + } + else { _border_handlers_vector = arm_compute::support::cpp14::make_unique(_num_of_stages); - _sums_vector = arm_compute::support::cpp14::make_unique(_num_of_stages - 1); + _results_vector = arm_compute::support::cpp14::make_unique(_num_of_stages - 1); TensorShape shape{ input->info()->tensor_shape() }; for(unsigned int i = 0; i < _num_of_stages - 1; i++) { shape.set(0, ceil(shape.x() / 128.f)); - _sums_vector[i].allocator()->init(input->info()->clone()->set_tensor_shape(shape)); + _results_vector[i].allocator()->init(input->info()->clone()->set_tensor_shape(shape)); } // Apply ReductionOperation only on first kernel - _memory_group.manage(_sums_vector.get()); + _memory_group.manage(_results_vector.get()); ReductionOperation first_kernel_op; + ReductionOperation intermediate_kernel_op; ReductionOperation last_kernel_op; + PixelValue pixelValue; switch(op) { case ReductionOperation::SUM: case ReductionOperation::MEAN_SUM: - first_kernel_op = ReductionOperation::SUM; - last_kernel_op = op; + first_kernel_op = ReductionOperation::SUM; + intermediate_kernel_op = ReductionOperation::SUM; + last_kernel_op = op; + pixelValue = PixelValue(0); break; case ReductionOperation::SUM_SQUARE: - first_kernel_op = ReductionOperation::SUM_SQUARE; - last_kernel_op = ReductionOperation::SUM; + first_kernel_op = ReductionOperation::SUM_SQUARE; + intermediate_kernel_op = ReductionOperation::SUM; + last_kernel_op = ReductionOperation::SUM; + pixelValue = PixelValue(0); + break; + case ReductionOperation::PROD: + first_kernel_op = ReductionOperation::PROD; + intermediate_kernel_op = ReductionOperation::PROD; + last_kernel_op = ReductionOperation::PROD; + pixelValue = PixelValue(1, input->info()->data_type()); break; default: ARM_COMPUTE_ERROR("Not supported"); } - _reduction_kernels_vector[0].configure(input, _sums_vector.get(), axis, first_kernel_op); - _border_handlers_vector[0].configure(input, _reduction_kernels_vector[0].border_size(), BorderMode::CONSTANT, PixelValue(0)); + _reduction_kernels_vector[0].configure(input, _results_vector.get(), axis, first_kernel_op); + _border_handlers_vector[0].configure(input, _reduction_kernels_vector[0].border_size(), BorderMode::CONSTANT, pixelValue); // Apply ReductionOperation on intermediate stages for(unsigned int i = 1; i < _num_of_stages - 1; ++i) { - _memory_group.manage(_sums_vector.get() + i); - _reduction_kernels_vector[i].configure(_sums_vector.get() + i - 1, _sums_vector.get() + i, axis, ReductionOperation::SUM); - _border_handlers_vector[i].configure(_sums_vector.get() + i - 1, _reduction_kernels_vector[i].border_size(), BorderMode::CONSTANT, PixelValue(0)); - _sums_vector[i - 1].allocator()->allocate(); + _memory_group.manage(_results_vector.get() + i); + _reduction_kernels_vector[i].configure(_results_vector.get() + i - 1, _results_vector.get() + i, axis, intermediate_kernel_op); + _border_handlers_vector[i].configure(_results_vector.get() + i - 1, _reduction_kernels_vector[i].border_size(), BorderMode::CONSTANT, pixelValue); + _results_vector[i - 1].allocator()->allocate(); } // Apply ReductionOperation on the last stage const unsigned int last_stage = _num_of_stages - 1; const unsigned int input_width = input->info()->dimension(0); - _reduction_kernels_vector[last_stage].configure(_sums_vector.get() + last_stage - 1, output, axis, last_kernel_op, input_width); - _border_handlers_vector[last_stage].configure(_sums_vector.get() + last_stage - 1, _reduction_kernels_vector[last_stage].border_size(), BorderMode::CONSTANT, PixelValue(0)); - _sums_vector[last_stage - 1].allocator()->allocate(); - } - else - { - _reduction_kernels_vector[0].configure(input, output, axis, op, 0); + _reduction_kernels_vector[last_stage].configure(_results_vector.get() + last_stage - 1, output, axis, last_kernel_op, input_width); + _border_handlers_vector[last_stage].configure(_results_vector.get() + last_stage - 1, _reduction_kernels_vector[last_stage].border_size(), BorderMode::CONSTANT, pixelValue); + _results_vector[last_stage - 1].allocator()->allocate(); } } @@ -188,7 +208,11 @@ void CLReductionOperation::run() { _memory_group.acquire(); - if(_reduction_axis == 0 && !_is_quantized) + if(_is_serial) + { + CLScheduler::get().enqueue(_reduction_kernels_vector[0], false); + } + else { for(unsigned int i = 0; i < _num_of_stages; ++i) { @@ -196,10 +220,6 @@ void CLReductionOperation::run() CLScheduler::get().enqueue(_reduction_kernels_vector[i], false); } } - else - { - CLScheduler::get().enqueue(_reduction_kernels_vector[0], false); - } _memory_group.release(); } -- cgit v1.2.1