1 files changed, 0 insertions, 141 deletions
diff --git a/runtime/neurun/core/src/exec/interp/operations/Gather.cc b/runtime/neurun/core/src/exec/interp/operations/Gather.cc
deleted file mode 100644
index 8b64d1937..000000000
--- a/runtime/neurun/core/src/exec/interp/operations/Gather.cc
+++ /dev/null
@@ -1,141 +0,0 @@
-/*
- * 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