diff options
Diffstat (limited to 'src/graph/nodes/L2NormalizeLayer.cpp')
-rw-r--r-- | src/graph/nodes/L2NormalizeLayer.cpp | 70 |
1 files changed, 16 insertions, 54 deletions
diff --git a/src/graph/nodes/L2NormalizeLayer.cpp b/src/graph/nodes/L2NormalizeLayer.cpp index c5689e159a..bcc3b94178 100644 --- a/src/graph/nodes/L2NormalizeLayer.cpp +++ b/src/graph/nodes/L2NormalizeLayer.cpp @@ -23,72 +23,34 @@ */ #include "arm_compute/graph/nodes/L2NormalizeLayer.h" -#include "arm_compute/runtime/CL/CLTensor.h" -#include "arm_compute/runtime/CL/functions/CLL2Normalize.h" -#include "arm_compute/runtime/NEON/functions/NEL2Normalize.h" -#include "arm_compute/runtime/Tensor.h" +#include "arm_compute/graph/NodeContext.h" +#include "arm_compute/graph/OperationRegistry.h" #include "support/ToolchainSupport.h" -#include "utils/TypePrinter.h" using namespace arm_compute::graph; -namespace +L2NormalizeLayer::L2NormalizeLayer(unsigned int axis, float epsilon) + : _axis(axis), _epsilon(epsilon) { -template <typename L2NormalizeType, typename TensorType, TargetHint hint> -std::unique_ptr<arm_compute::IFunction> instantiate_function(arm_compute::ITensor *input, arm_compute::ITensor *output, unsigned int axis, float epsilon) -{ - auto l2norm = arm_compute::support::cpp14::make_unique<L2NormalizeType>(); - l2norm->configure( - dynamic_cast<TensorType *>(input), - dynamic_cast<TensorType *>(output), - axis, - epsilon); - - return std::move(l2norm); } -template <TargetHint target_hint> -std::unique_ptr<arm_compute::IFunction> instantiate(arm_compute::ITensor *input, arm_compute::ITensor *output, unsigned int axis, float epsilon); - -template <> -std::unique_ptr<arm_compute::IFunction> instantiate<TargetHint::OPENCL>(arm_compute::ITensor *input, arm_compute::ITensor *output, unsigned int axis, float epsilon) -{ - return instantiate_function<arm_compute::CLL2Normalize, arm_compute::ICLTensor, TargetHint::OPENCL>(input, output, axis, epsilon); -} - -template <> -std::unique_ptr<arm_compute::IFunction> instantiate<TargetHint::NEON>(arm_compute::ITensor *input, arm_compute::ITensor *output, unsigned int axis, float epsilon) -{ - return instantiate_function<arm_compute::NEL2Normalize, arm_compute::ITensor, TargetHint::NEON>(input, output, axis, epsilon); -} -} // namespace - std::unique_ptr<arm_compute::IFunction> L2NormalizeLayer::instantiate_node(GraphContext &ctx, ITensorObject *input, ITensorObject *output) { ARM_COMPUTE_ERROR_ON(input == nullptr || input->tensor() == nullptr); ARM_COMPUTE_ERROR_ON(output == nullptr || output->tensor() == nullptr); - std::unique_ptr<arm_compute::IFunction> func; - _target_hint = ctx.hints().target_hint(); - arm_compute::ITensor *in = input->tensor(); arm_compute::ITensor *out = output->tensor(); - - if(_target_hint == TargetHint::OPENCL) - { - func = instantiate<TargetHint::OPENCL>(in, out, _axis, _epsilon); - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiating CLL2NormalizeLayer"); - } - else - { - func = instantiate<TargetHint::NEON>(in, out, _axis, _epsilon); - ARM_COMPUTE_LOG_GRAPH_INFO("Instantiating NEL2NormalizeLayer"); - } - - ARM_COMPUTE_LOG_GRAPH_INFO(" Data Type: " << in->info()->data_type() - << " Input shape: " << in->info()->tensor_shape() - << " Output shape: " << out->info()->tensor_shape() - << std::endl); - - return func; + _target_hint = ctx.hints().target_hint(); + + // Create node context + NodeContext node_ctx(OperationType::L2NormalizeLayer); + node_ctx.set_target(_target_hint); + node_ctx.add_input(in); + node_ctx.add_output(out); + node_ctx.add_parameter<unsigned int>("axis", _axis); + node_ctx.add_parameter<float>("epsilon", _epsilon); + + // Get function + return OperationRegistry::get().find_operation(OperationType::L2NormalizeLayer, _target_hint)->configure(node_ctx); } |