diff options
Diffstat (limited to 'src/runtime')
-rw-r--r-- | src/runtime/NEON/functions/NEConcatenateLayer.cpp | 174 |
1 files changed, 82 insertions, 92 deletions
diff --git a/src/runtime/NEON/functions/NEConcatenateLayer.cpp b/src/runtime/NEON/functions/NEConcatenateLayer.cpp index 1897915d33..fa7b91c3ca 100644 --- a/src/runtime/NEON/functions/NEConcatenateLayer.cpp +++ b/src/runtime/NEON/functions/NEConcatenateLayer.cpp @@ -38,36 +38,16 @@ namespace arm_compute { NEConcatenateLayer::NEConcatenateLayer() - : _concat_function(nullptr), - _hconcat_kernels(), + : _concat_kernels(), _num_inputs(0), _axis(Window::DimX) { } -Status NEConcatenateLayer::validate_h_concatenate(const std::vector<ITensorInfo *> &inputs_vector, const ITensorInfo *output) -{ - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output); - ARM_COMPUTE_RETURN_ERROR_ON(inputs_vector.size() < 2); - - // Output auto inizialitation if not yet initialized - TensorInfo tmp_output_info = *output->clone(); - TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, Window::DimY); - auto_init_if_empty(tmp_output_info, output_shape, 1, inputs_vector[0]->data_type()); - - unsigned int offset = 0; - for(const auto &input : inputs_vector) - { - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input); - ARM_COMPUTE_RETURN_ON_ERROR(NEHeightConcatenateLayerKernel::validate(input, offset, &tmp_output_info)); - offset += input->dimension(Window::DimY); - } - - return Status{}; -} - -void NEConcatenateLayer::configure_h_concatenate(std::vector<ITensor *> inputs_vector, ITensor *output) +void NEConcatenateLayer::configure(const std::vector<ITensor *> &inputs_vector, ITensor *output, DataLayoutDimension axis) { + ARM_COMPUTE_ERROR_ON(output == nullptr); + _axis = get_data_layout_dimension_index(output->info()->data_layout(), axis); _num_inputs = inputs_vector.size(); std::vector<ITensorInfo *> inputs_vector_info; @@ -76,98 +56,108 @@ void NEConcatenateLayer::configure_h_concatenate(std::vector<ITensor *> inputs_v ARM_COMPUTE_ERROR_ON_NULLPTR(inputs_vector.at(i)); inputs_vector_info.emplace_back(inputs_vector.at(i)->info()); } - TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, Window::DimY); + TensorShape output_shape{}; + if(_axis == Window::DimZ) + { + output_shape = arm_compute::misc::shape_calculator::calculate_depth_concatenate_shape(inputs_vector); + } + else + { + output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, _axis); + } // Output auto inizialitation if not yet initialized auto_init_if_empty(*output->info(), output_shape, 1, inputs_vector[0]->info()->data_type()); - ARM_COMPUTE_ERROR_THROW_ON(validate_h_concatenate(inputs_vector_info, output->info())); + ARM_COMPUTE_ERROR_THROW_ON(NEConcatenateLayer::validate(inputs_vector_info, output->info(), axis)); unsigned int offset = 0; - _hconcat_kernels = arm_compute::support::cpp14::make_unique<NEHeightConcatenateLayerKernel[]>(_num_inputs); - for(unsigned int i = 0; i < _num_inputs; ++i) { - _hconcat_kernels[i].configure(inputs_vector.at(i), offset, output); - offset += inputs_vector.at(i)->info()->dimension(Window::DimY); - } -} - -void NEConcatenateLayer::configure(const std::vector<ITensor *> &inputs_vector, ITensor *output, DataLayoutDimension axis) -{ - ARM_COMPUTE_ERROR_ON(output == nullptr); - _axis = get_data_layout_dimension_index(output->info()->data_layout(), axis); - switch(_axis) - { - case 0: + switch(_axis) { - auto func = support::cpp14::make_unique<NEWidthConcatenateLayer>(); - func->configure(inputs_vector, output); - _concat_function = std::move(func); - break; - } - case 1: - { - configure_h_concatenate(inputs_vector, output); - break; - } - case 2: - { - auto func = support::cpp14::make_unique<NEDepthConcatenateLayer>(); - func->configure(inputs_vector, output); - _concat_function = std::move(func); - break; + case Window::DimX: + { + auto kernel = support::cpp14::make_unique<NEWidthConcatenateLayerKernel>(); + kernel->configure(inputs_vector.at(i), offset, output); + _concat_kernels.emplace_back(std::move(kernel)); + break; + } + case Window::DimY: + { + auto kernel = support::cpp14::make_unique<NEHeightConcatenateLayerKernel>(); + kernel->configure(inputs_vector.at(i), offset, output); + _concat_kernels.emplace_back(std::move(kernel)); + break; + } + case Window::DimZ: + { + auto kernel = support::cpp14::make_unique<NEDepthConcatenateLayerKernel>(); + kernel->configure(inputs_vector.at(i), offset, output); + _concat_kernels.emplace_back(std::move(kernel)); + break; + } + default: + ARM_COMPUTE_ERROR("Axis not supported"); } - default: - ARM_COMPUTE_ERROR("Concatenation is supported across width, height and depth only!"); + offset += inputs_vector.at(i)->info()->dimension(_axis); } } Status NEConcatenateLayer::validate(const std::vector<ITensorInfo *> &inputs_vector, const ITensorInfo *output, DataLayoutDimension axis) { - ARM_COMPUTE_RETURN_ERROR_ON(output == nullptr); + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output); + ARM_COMPUTE_RETURN_ERROR_ON(inputs_vector.size() < 2); + const unsigned int _axis = get_data_layout_dimension_index(inputs_vector[0]->data_layout(), axis); - switch(get_data_layout_dimension_index(output->data_layout(), axis)) + // Output auto inizialitation if not yet initialized + TensorInfo tmp_output_info = *output->clone(); + TensorShape output_shape{}; + if(_axis == Window::DimZ) { - case 0: - ARM_COMPUTE_RETURN_ON_ERROR(NEWidthConcatenateLayer::validate(inputs_vector, output)); - break; - case 1: - ARM_COMPUTE_RETURN_ON_ERROR(NEConcatenateLayer::validate_h_concatenate(inputs_vector, output)); - break; - case 2: - ARM_COMPUTE_RETURN_ON_ERROR(NEDepthConcatenateLayer::validate(inputs_vector, output)); - break; - default: - ARM_COMPUTE_RETURN_ERROR_MSG("Concatenation is supported across width and depth only!"); + output_shape = arm_compute::misc::shape_calculator::calculate_depth_concatenate_shape(inputs_vector); } - return Status{}; -} + else + { + output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, _axis); + } + auto_init_if_empty(tmp_output_info, output_shape, 1, inputs_vector[0]->data_type()); -void NEConcatenateLayer::run() -{ - switch(_axis) + unsigned int offset = 0; + for(const auto &input : inputs_vector) { - case 0: - case 2: - { - ARM_COMPUTE_ERROR_ON(_concat_function == nullptr); - _concat_function->run(); - break; - } - case 1: + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input); + switch(_axis) { - for(unsigned i = 0; i < _num_inputs; ++i) + case Window::DimX: { - NEScheduler::get().schedule(_hconcat_kernels.get() + i, Window::DimY); + ARM_COMPUTE_RETURN_ON_ERROR(NEWidthConcatenateLayerKernel::validate(input, offset, &tmp_output_info)); + break; } - break; - } - default: - { - ARM_COMPUTE_ERROR("Axis not supported."); - break; + case Window::DimY: + { + ARM_COMPUTE_RETURN_ON_ERROR(NEHeightConcatenateLayerKernel::validate(input, offset, &tmp_output_info)); + break; + } + case Window::DimZ: + { + ARM_COMPUTE_RETURN_ON_ERROR(NEDepthConcatenateLayerKernel::validate(input, offset, &tmp_output_info)); + break; + } + default: + ARM_COMPUTE_ERROR("Axis not supported"); } + offset += input->dimension(_axis); + } + + return Status{}; +} + +void NEConcatenateLayer::run() +{ + for(auto &kernel : _concat_kernels) + { + NEScheduler::get().schedule(kernel.get(), _axis); } } } // namespace arm_compute |