1 files changed, 0 insertions, 140 deletions
diff --git a/runtime/onert/core/src/interp/operations/Pool2D.cc b/runtime/onert/core/src/interp/operations/Pool2D.cc
deleted file mode 100644
index 92f9d70b2..000000000
--- a/runtime/onert/core/src/interp/operations/Pool2D.cc
+++ /dev/null
@@ -1,140 +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/AveragePool.h>
-#include <cker/operation/MaxPool.h>
-
-#include "OperationUtil.h"
-
-#include "interp/Registration.h"
-#include "ir/operation/Pool2D.h"
-#include "util/Utils.h"
-#include "util/ShapeInference.h"
-#include "misc/polymorphic_downcast.h"
-
-namespace onert
-{
-namespace interp
-{
-namespace pool2d
-{
-
-void preparePool2D(ExecEnv *env, const ir::Operation &node)
-{
-  const auto &pool_node = nnfw::misc::polymorphic_downcast<const ir::operation::Pool2D &>(node);
-  const auto in_index = node.getInputs().at(pool_node.INPUT);
-  const auto out_index = node.getOutputs().at(0);
-
-  const auto in_tensor = env->tensorAt(in_index);
-  UNUSED_RELEASE(in_tensor);
-
-  assert(in_tensor->num_dimensions() == 4);
-
-  const auto output_info = env->graph().operands().at(out_index).info();
-  if (output_info.total_size() == 0)
-  {
-    // Handle unspecified output shape
-    const auto infered_output_shape =
-        shape_inference::inferPoolShape(in_tensor->tensorInfo().shape(), pool_node.param());
-    env->allocateIfNeeded(
-        out_index, ir::OperandInfo::createStaticInfo(infered_output_shape, output_info.typeInfo()));
-  }
-  else
-  {
-    env->allocateIfNeeded(out_index, output_info);
-  }
-
-  auto out_tensor = env->tensorAt(out_index);
-  UNUSED_RELEASE(out_tensor);
-
-  // Handle same ifm & ofm data type only
-  assert(in_tensor->data_type() == out_tensor->data_type());
-  assert(out_tensor->num_dimensions() == 4);
-}
-
-template <typename T>
-void invoke(const nnfw::cker::PoolParams &params, const nnfw::cker::Shape &in_shape,
-            const T *in_ptr, const nnfw::cker::Shape &out_shape, T *out_ptr,
-            ir::operation::Pool2D::PoolType op_type)
-{
-  switch (op_type)
-  {
-    case ir::operation::Pool2D::PoolType::AVG:
-      nnfw::cker::AveragePool<T>(params, in_shape, in_ptr, out_shape, out_ptr);
-      break;
-    case ir::operation::Pool2D::PoolType::MAX:
-      nnfw::cker::MaxPool<T>(params, in_shape, in_ptr, out_shape, out_ptr);
-      break;
-    default:
-      throw std::runtime_error{"Interp(Pool2D): NYI unsupported operation"};
-      break;
-  }
-}
-
-void invokePool2DOps(const ExecEnv *env, const ir::Operation &node)
-{
-  const auto &pool_node = nnfw::misc::polymorphic_downcast<const ir::operation::Pool2D &>(node);
-
-  const auto in_index = node.getInputs().at(0);
-  const auto out_index = node.getOutputs().at(0);
-
-  // Check lhs shape is same with rhs (with broadcast)
-  const auto in_tensor = env->tensorAt(in_index);
-  const auto out_tensor = env->tensorAt(out_index);
-
-  // TODO support NCHW frontend
-  const auto ifm_shape = in_tensor->tensorInfo().shape().asFeature(ir::Layout::NHWC);
-  const auto ofm_shape = out_tensor->tensorInfo().shape().asFeature(ir::Layout::NHWC);
-  const auto param = pool_node.param();
-  const auto padding =
-      ir::calculatePadding(param.padding, ifm_shape, ofm_shape, param.stride, param.kw, param.kh);
-  // Calculate
-  nnfw::cker::PoolParams cker_param;
-  cker_param.filter_width = param.kw;
-  cker_param.filter_height = param.kh;
-  cker_param.padding_values.width = padding.left;
-  cker_param.padding_values.height = padding.top;
-  cker_param.stride_width = param.stride.horizontal;
-  cker_param.stride_height = param.stride.vertical;
-
-  const auto data_type = in_tensor->data_type();
-  if (data_type == ir::DataType::FLOAT32)
-  {
-    calculateActivationRange(param.activation, &cker_param.float_activation_min,
-                             &cker_param.float_activation_max);
-
-    const auto in_shape = convertShape(in_tensor->tensorInfo().shape());
-    const auto out_shape = convertShape(out_tensor->tensorInfo().shape());
-    const float *in_ptr = reinterpret_cast<const float *>(in_tensor->bufferRO());
-    float *out_ptr = reinterpret_cast<float *>(out_tensor->buffer());
-    // Now, invoke() supports only Pool2D in float
-    invoke<float>(cker_param, in_shape, in_ptr, out_shape, out_ptr, param.op_type);
-  }
-  else
-  {
-    throw std::runtime_error{"NYI: Support float only"};
-  }
-}
-} // namespace pool2d
-
-OpKernel *getPool2D()
-{
-  static OpKernel kernel = {pool2d::preparePool2D, pool2d::invokePool2DOps};
-  return &kernel;
-}
-
-} // namespace interp
-} // namespace onert