1 files changed, 141 insertions, 0 deletions
diff --git a/runtime/neurun/core/src/exec/interp/operations/Gather.cc b/runtime/neurun/core/src/exec/interp/operations/Gather.cc
new file mode 100644
index 000000000..8b64d1937
--- /dev/null
+++ b/runtime/neurun/core/src/exec/interp/operations/Gather.cc
@@ -0,0 +1,141 @@
+/*
+ * Copyright (c) 2019 Samsung Electronics Co., Ltd. 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 <cker/operation/Gather.h>
+
+#include "OperationUtil.h"
+
+#include "exec/interp/Registration.h"
+#include "ir/operation/Gather.h"
+#include "misc/polymorphic_downcast.h"
+
+namespace neurun
+{
+namespace exec
+{
+namespace interp
+{
+namespace
+{
+
+void prepareGather(ExecEnv *env, const ir::Operation &node)
+{
+  const auto input_index = node.getInputs().at(ir::operation::Gather::INPUT);
+  const auto indices_index = node.getInputs().at(ir::operation::Gather::INDICES);
+  const auto output_index = node.getOutputs().at(0);
+
+  const auto input_tensor = env->tensorAt(input_index);
+  const auto indices_tensor = env->tensorAt(indices_index);
+
+  // TODO handle unspecified output shape:
+  //      calculate output shape using ifm shape, kernel shape, padding, stride
+  const auto output_info = env->graph().operands().at(output_index).info();
+  if (output_info.total_size() == 0)
+  {
+    throw std::runtime_error{"Interp(Gather): NYI for unspecified output shape"};
+  }
+  else
+  {
+    env->allocateIfNeeded(output_index, output_info);
+  }
+
+  if (indices_tensor->data_type() != ir::DataType::INT32)
+  {
+    throw std::runtime_error{"Interp(Gather): Invalid indices data type"};
+  }
+
+  auto output_tensor = env->tensorAt(output_index);
+  auto output_rank = input_tensor->num_dimensions() + indices_tensor->num_dimensions() - 1;
+
+  if (output_rank != output_tensor->num_dimensions())
+  {
+    throw std::runtime_error{"Interp(Gather): Invalid output rank"};
+  }
+  if (output_tensor->data_type() != input_tensor->data_type())
+  {
+    throw std::runtime_error{"Interp(Gather): Invalid output data type"};
+  }
+
+  if (input_tensor->data_type() == ir::DataType::QUANT8_ASYMM &&
+      input_tensor->tensorInfo().typeInfo() != output_tensor->tensorInfo().typeInfo())
+  {
+    throw std::runtime_error{
+        "Interp(Gather): Cannot handle different I/O QUANT8_ASYMM scale/offset"};
+  }
+}
+
+template <typename raw_type>
+void invoke(const ITensor *input_tensors, const ITensor *indices_tensors,
+            const ITensor *output_tensor, uint32_t axis)
+{
+  // Calculate
+  nnfw::cker::GatherParams cker_param;
+  cker_param.axis = (int8_t)axis;
+
+  const auto cker_input_shapes = convertShape(input_tensors->tensorInfo().shape());
+  const auto cker_indices_shape = convertShape(indices_tensors->tensorInfo().shape());
+  const auto cker_output_shape = convertShape(output_tensor->tensorInfo().shape());
+  const raw_type *input_ptr = reinterpret_cast<const raw_type *>(input_tensors->bufferRO());
+  const int32_t *indices_ptr = reinterpret_cast<const int32_t *>(indices_tensors->bufferRO());
+  raw_type *output_ptr = reinterpret_cast<raw_type *>(output_tensor->buffer());
+
+  nnfw::cker::Gather<raw_type>(cker_param, cker_input_shapes, input_ptr, cker_indices_shape,
+                               indices_ptr, cker_output_shape, output_ptr);
+}
+
+void invokeGather(const ExecEnv *env, const ir::Operation &node)
+{
+  const auto &gather_node = nnfw::misc::polymorphic_downcast<const ir::operation::Gather &>(node);
+  const int32_t axis_raw = gather_node.param().axis;
+
+  const auto input_index = node.getInputs().at(ir::operation::Gather::INPUT);
+  const auto indices_index = node.getInputs().at(ir::operation::Gather::INDICES);
+  const auto output_index = node.getOutputs().at(0);
+
+  const auto input_tensor = env->tensorAt(input_index);
+  const auto indices_tensor = env->tensorAt(indices_index);
+  const auto output_tensor = env->tensorAt(output_index);
+  const uint32_t axis = (axis_raw < 0) ? (axis_raw + input_tensor->num_dimensions()) : axis_raw;
+
+  const auto data_type = input_tensor->data_type();
+
+  switch (data_type)
+  {
+    case ir::DataType::FLOAT32:
+      invoke<float>(input_tensor, indices_tensor, output_tensor, axis);
+      break;
+    case ir::DataType::INT32:
+      invoke<int32_t>(input_tensor, indices_tensor, output_tensor, axis);
+      break;
+    case ir::DataType::QUANT8_ASYMM:
+      invoke<uint8_t>(input_tensor, indices_tensor, output_tensor, axis);
+      break;
+    default:
+      throw std::runtime_error{"Interp(Gather): NYI - Not supported type"};
+  }
+}
+
+} // namespace concat
+
+OpKernel *getGather()
+{
+  static OpKernel kernel = {prepareGather, invokeGather};
+  return &kernel;
+}
+
+} // namespace interp
+} // namespace exec
+} // namespace neurun