diff options
Diffstat (limited to 'src/runtime/CL/functions/CLArgMinMaxLayer.cpp')
-rw-r--r-- | src/runtime/CL/functions/CLArgMinMaxLayer.cpp | 149 |
1 files changed, 54 insertions, 95 deletions
diff --git a/src/runtime/CL/functions/CLArgMinMaxLayer.cpp b/src/runtime/CL/functions/CLArgMinMaxLayer.cpp index 8c32563abb..f9bbd31e8a 100644 --- a/src/runtime/CL/functions/CLArgMinMaxLayer.cpp +++ b/src/runtime/CL/functions/CLArgMinMaxLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018-2020 Arm Limited. + * Copyright (c) 2018-2021, 2023 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -27,8 +27,10 @@ #include "arm_compute/core/Error.h" #include "arm_compute/core/TensorInfo.h" #include "arm_compute/core/Types.h" -#include "arm_compute/core/Validate.h" #include "arm_compute/core/utils/misc/ShapeCalculator.h" +#include "arm_compute/core/Validate.h" + +#include "src/common/utils/Log.h" #include "src/core/CL/CLValidate.h" #include "src/core/CL/kernels/CLArgMinMaxLayerKernel.h" #include "src/core/helpers/AutoConfiguration.h" @@ -37,76 +39,52 @@ namespace arm_compute { CLArgMinMaxLayer::CLArgMinMaxLayer(std::shared_ptr<IMemoryManager> memory_manager) - : _memory_group(std::move(memory_manager)), _results_vector(), _not_reshaped_output(), _reduction_kernels_vector(), _reshape(), _num_of_stages(), _reduction_axis() + : _memory_group(std::move(memory_manager)), + _not_reshaped_output(), + _arg_min_max_kernel(), + _reshape(), + _reduction_axis() { } CLArgMinMaxLayer::~CLArgMinMaxLayer() = default; -Status CLArgMinMaxLayer::validate(const ITensorInfo *input, int axis, const ITensorInfo *output, const ReductionOperation &op) +Status +CLArgMinMaxLayer::validate(const ITensorInfo *input, int axis, const ITensorInfo *output, const ReductionOperation &op) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::S32, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(op != ReductionOperation::ARG_IDX_MAX && op != ReductionOperation::ARG_IDX_MIN, "Invalid reduction operation"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(axis >= static_cast<int>(TensorShape::num_max_dimensions), "Reduction axis greater than max number of dimensions"); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, + DataType::S32, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(op != ReductionOperation::ARG_IDX_MAX && op != ReductionOperation::ARG_IDX_MIN, + "Invalid reduction operation"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(axis >= static_cast<int>(TensorShape::num_max_dimensions), + "Reduction axis greater than max number of dimensions"); ARM_COMPUTE_RETURN_ERROR_ON_MSG(axis > 3, "Unsupported reduction axis"); - const unsigned int num_of_stages = utils::calculate_number_of_stages_only_x_axis(input->dimension(0), axis); DataType output_data_type = DataType::S32; TensorInfo not_reshaped_output; const auto input_num_channles = input->num_channels(); const auto input_qinfo = input->quantization_info(); - if(output->total_size() != 0) + if (output->total_size() != 0) { output_data_type = output->data_type(); - const TensorInfo expected_output_shape = output->clone()->set_tensor_shape(arm_compute::misc::shape_calculator::compute_reduced_shape(input->tensor_shape(), axis, false)); + const TensorInfo expected_output_shape = output->clone()->set_tensor_shape( + arm_compute::misc::shape_calculator::compute_reduced_shape(input->tensor_shape(), axis, false)); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(&expected_output_shape, output); } auto shape_before_reshape = input->tensor_shape(); shape_before_reshape.set(axis, 1); - auto initialize_tensorinfo = [](TensorInfo & ti, TensorShape shape, DataType data_type, int num_channels, QuantizationInfo qinfo) - { + auto initialize_tensorinfo = [](TensorInfo &ti, TensorShape shape, DataType data_type, int num_channels, + QuantizationInfo qinfo) { ti.set_data_type(data_type).set_tensor_shape(shape).set_num_channels(num_channels).set_quantization_info(qinfo); }; initialize_tensorinfo(not_reshaped_output, shape_before_reshape, output_data_type, input_num_channles, input_qinfo); - if(num_of_stages == 1) - { - ARM_COMPUTE_RETURN_ON_ERROR(CLArgMinMaxLayerKernel::validate(input, nullptr, ¬_reshaped_output, axis, op)); - } - else - { - // Create temporary tensor infos - std::vector<TensorInfo> sums_vector(num_of_stages - 1); - - // Create intermediate tensor info - TensorShape shape{ input->tensor_shape() }; - - for(unsigned int i = 0; i < num_of_stages - 1; i++) - { - shape.set(0, ceil(shape.x() / 128.f)); - sums_vector[i].set_data_type(input->data_type()); - sums_vector[i].set_tensor_shape(shape); - sums_vector[i].set_num_channels(input->num_channels()); - } - - // Validate ReductionOperation only on first kernel - ARM_COMPUTE_RETURN_ON_ERROR(CLArgMinMaxLayerKernel::validate(input, nullptr, &sums_vector[0], axis, op)); - - // Validate ReductionOperation on intermediate stages - for(unsigned int i = 1; i < num_of_stages - 1; ++i) - { - ARM_COMPUTE_RETURN_ON_ERROR(CLArgMinMaxLayerKernel::validate(input, &sums_vector[i - 1], &sums_vector[i], axis, op)); - } - - // Validate ReductionOperation on the last stage - const unsigned int last_stage = num_of_stages - 1; - ARM_COMPUTE_RETURN_ON_ERROR(CLArgMinMaxLayerKernel::validate(input, &sums_vector[last_stage - 1], ¬_reshaped_output, axis, op)); - } + ARM_COMPUTE_RETURN_ON_ERROR(CLArgMinMaxLayerKernel::validate(input, ¬_reshaped_output, axis, op)); ARM_COMPUTE_RETURN_ON_ERROR(CLReshapeLayer::validate(¬_reshaped_output, output)); return Status{}; } @@ -116,58 +94,42 @@ void CLArgMinMaxLayer::configure(const ICLTensor *input, int axis, ICLTensor *ou configure(CLKernelLibrary::get().get_compile_context(), input, axis, output, op); } -void CLArgMinMaxLayer::configure(const CLCompileContext &compile_context, const ICLTensor *input, int axis, ICLTensor *output, const ReductionOperation &op) +void CLArgMinMaxLayer::configure(const CLCompileContext &compile_context, + const ICLTensor *input, + int axis, + ICLTensor *output, + const ReductionOperation &op) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); - _num_of_stages = utils::calculate_number_of_stages_only_x_axis(input->info()->dimension(0), axis); - _reduction_axis = axis; - - const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_reduced_shape(input->info()->tensor_shape(), axis, false); - DataType output_data_type = (output->info()->data_type() == DataType::UNKNOWN) ? DataType::S32 : output->info()->data_type(); - auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape).set_data_type(output_data_type).reset_padding().set_is_resizable(true)); + ARM_COMPUTE_LOG_PARAMS(input, axis, output, op); - // Configure reduction operation kernels - _reduction_kernels_vector.reserve(_num_of_stages); + _reduction_axis = axis; - auto add_reduction_kernel = [this, &compile_context, axis, op](const ICLTensor * input, const ICLTensor * prev_output, ICLTensor * output) - { - _reduction_kernels_vector.emplace_back(std::make_unique<CLArgMinMaxLayerKernel>()); - _reduction_kernels_vector.back()->configure(compile_context, input, prev_output, output, axis, op); - }; + const TensorShape output_shape = + arm_compute::misc::shape_calculator::compute_reduced_shape(input->info()->tensor_shape(), axis, false); + DataType output_data_type = + (output->info()->data_type() == DataType::UNKNOWN) ? DataType::S32 : output->info()->data_type(); + auto_init_if_empty(*output->info(), input->info() + ->clone() + ->set_tensor_shape(output_shape) + .set_data_type(output_data_type) + .reset_padding() + .set_is_resizable(true)); + + TensorShape not_reshaped_output_shape{input->info()->tensor_shape()}; + not_reshaped_output_shape.set(axis, 1); + auto_init_if_empty(*_not_reshaped_output.info(), input->info() + ->clone() + ->set_tensor_shape(not_reshaped_output_shape) + .set_data_type(output_data_type) + .reset_padding() + .set_is_resizable(true)); + + _arg_min_max_kernel = std::make_unique<CLArgMinMaxLayerKernel>(); + _arg_min_max_kernel->configure(compile_context, input, &_not_reshaped_output, axis, op); _memory_group.manage(&_not_reshaped_output); - // Create temporary tensors - if(_num_of_stages == 1) - { - add_reduction_kernel(input, nullptr, &_not_reshaped_output); - } - else - { - _results_vector.resize(_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)); - _results_vector[i].allocator()->init(input->info()->clone()->set_tensor_shape(shape).set_data_type(output_data_type)); - } - - // Apply ReductionOperation only on first kernel - _memory_group.manage(&_results_vector[0]); - add_reduction_kernel(input, nullptr, &_results_vector[0]); - - // Apply ReductionOperation on intermediate stages - for(unsigned int i = 1; i < _num_of_stages - 1; ++i) - { - _memory_group.manage(&_results_vector[i]); - add_reduction_kernel(input, &_results_vector[i - 1], &_results_vector[i]); - _results_vector[i - 1].allocator()->allocate(); - } - - // Apply ReductionOperation on the last stage - const unsigned int last_stage = _num_of_stages - 1; - add_reduction_kernel(input, &_results_vector[last_stage - 1], &_not_reshaped_output); - _results_vector[last_stage - 1].allocator()->allocate(); - } + _reshape.configure(compile_context, &_not_reshaped_output, output); _not_reshaped_output.allocator()->allocate(); } @@ -176,10 +138,7 @@ void CLArgMinMaxLayer::run() { MemoryGroupResourceScope scope_mg(_memory_group); - for(unsigned int i = 0; i < _num_of_stages; ++i) - { - CLScheduler::get().enqueue(*_reduction_kernels_vector[i], false); - } + CLScheduler::get().enqueue(*_arg_min_max_kernel, false); _reshape.run(); } } // namespace arm_compute |