1 files changed, 113 insertions, 0 deletions
diff --git a/onert-micro/luci-interpreter/src/kernels/AddN.cpp b/onert-micro/luci-interpreter/src/kernels/AddN.cpp
new file mode 100644
index 000000000..0df3c448b
--- /dev/null
+++ b/onert-micro/luci-interpreter/src/kernels/AddN.cpp
@@ -0,0 +1,113 @@
+/*
+ * Copyright (c) 2020 Samsung Electronics Co., Ltd. All Rights Reserved
+ * Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "Builders.h"
+#include "kernels/Utils.h"
+
+#include "PALAddN.h"
+
+namespace luci_interpreter
+{
+
+namespace
+{
+
+template <typename T>
+void evalGeneric(const circle::Operator *cur_op, BaseRuntimeGraph *runtime_graph)
+{
+  const auto output_index = cur_op->outputs()->operator[](0);
+  assert(output_index != -1);
+  const auto output = runtime_graph->getCircleTensorByIndex(output_index);
+
+  const auto input_sizes = cur_op->inputs()->size();
+
+  auto input1_index = cur_op->inputs()->operator[](0);
+  const auto *tensor1 = runtime_graph->getCircleTensorByIndex(input1_index);
+
+  const int flat_size = Tensor::num_elements(tensor1);
+
+  std::vector<const T *> all_input_data;
+  for (int32_t i = 0; i < input_sizes; ++i)
+  {
+    auto input_index = cur_op->inputs()->operator[](i);
+    const auto *tensor = runtime_graph->getCircleTensorByIndex(input_index);
+
+    const auto *tensor_data = runtime_graph->getDataByTensor(tensor);
+    if (tensor_data == nullptr)
+      tensor_data = runtime_graph->getConstDataByTensor(tensor);
+
+    auto *data = reinterpret_cast<const T *>(tensor_data);
+    all_input_data.push_back(data);
+  }
+
+  auto *output_data = reinterpret_cast<T *>(runtime_graph->getDataByTensor(output));
+
+  luci_interpreter_pal::AddN(flat_size, input_sizes, all_input_data.data(), output_data);
+}
+
+} // namespace
+
+void configure_kernel_CircleAddN(const circle::Operator *cur_op, BaseRuntimeGraph *runtime_graph)
+{
+  const int num_inputs = cur_op->inputs()->size();
+
+  LUCI_INTERPRETER_CHECK(num_inputs >= 2);
+  LUCI_INTERPRETER_CHECK(cur_op->outputs()->size() == 1);
+
+  const auto input1_index = cur_op->inputs()->operator[](0);
+  assert(input1_index != -1);
+
+  const auto input1_tensor = runtime_graph->getCircleTensorByIndex(input1_index);
+  assert(input1_tensor != nullptr);
+
+  for (int i = 1; i < num_inputs; ++i)
+  {
+    const auto input_index = cur_op->inputs()->operator[](i);
+    assert(input_index != -1);
+
+    const auto input_tensor = runtime_graph->getCircleTensorByIndex(input_index);
+    assert(input_tensor != nullptr);
+
+    LUCI_INTERPRETER_CHECK(Tensor::element_type(input1_tensor) ==
+                           Tensor::element_type(input_tensor));
+    LUCI_INTERPRETER_CHECK(Tensor::num_dims(input1_tensor) == Tensor::num_dims(input_tensor));
+    LUCI_INTERPRETER_CHECK(Tensor::num_elements(input1_tensor) ==
+                           Tensor::num_elements(input_tensor));
+  }
+}
+
+void execute_kernel_CircleAddN(const circle::Operator *cur_op, BaseRuntimeGraph *runtime_graph)
+{
+  const auto output_index = cur_op->outputs()->operator[](0);
+  assert(output_index != -1);
+  const auto output = runtime_graph->getCircleTensorByIndex(output_index);
+
+  switch (Tensor::element_type(output))
+  {
+#ifndef DIS_FLOAT
+    case DataType::FLOAT32:
+    {
+      evalGeneric<float>(cur_op, runtime_graph);
+    }
+    break;
+#endif // DIS_FLOAT
+    default:
+      assert(false && "Unsupported type.");
+  }
+}
+
+} // namespace luci_interpreter