1 files changed, 0 insertions, 159 deletions
diff --git a/runtimes/neurun/src/kernel/acl_cl/ConcatLayer.cc b/runtimes/neurun/src/kernel/acl_cl/ConcatLayer.cc
deleted file mode 100644
index 3844317ab..000000000
--- a/runtimes/neurun/src/kernel/acl_cl/ConcatLayer.cc
+++ /dev/null
@@ -1,159 +0,0 @@
-/*
- * Copyright (c) 2018 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 "ConcatLayer.h"
-
-#include <arm_compute/runtime/CL/CLScheduler.h>
-
-#include "util/feature/nchw/View.h"
-#include "util/logging.h"
-
-namespace
-{
-
-bool matchSizeExceptAxis(const ::neurun::backend::acl_cl::operand::ICLTensor *t1,
-                         const ::neurun::backend::acl_cl::operand::ICLTensor *t2, uint32_t axis)
-{
-  assert(t1->num_dimensions() <= 4);
-  assert(t2->num_dimensions() <= 4);
-
-  for (uint32_t i = 0; i < 4; i++)
-  {
-    if (axis == i)
-      continue;
-    if (t1->dimension(i) != t2->dimension(i))
-      return false;
-  }
-  return true;
-}
-
-} // namespace {anonymous}
-
-namespace neurun
-{
-namespace kernel
-{
-namespace acl_cl
-{
-
-ConcatLayer::ConcatLayer()
-    : _input_allocs(), _output_alloc(nullptr), _axis(0), _input_type(OperandType::SCALAR_FLOAT32)
-{
-  // DO NOTHING
-}
-
-bool ConcatLayer::concatenationFloat32()
-{
-  // Input and output size check
-  {
-    // NOTE Support only tensor with dimension 4 or less
-
-    uint32_t axis_sum = 0;
-
-    for (auto input : _input_allocs)
-    {
-      assert(matchSizeExceptAxis(_output_alloc, input, _axis));
-      axis_sum += input->dimension(_axis);
-    }
-
-    assert(_output_alloc->dimension(_axis) == axis_sum);
-  }
-
-  VERBOSE(Concat_RUN) << "START Concat" << std::endl;
-
-  // Perform operation
-  {
-    uint32_t axis_offset = 0;
-
-    auto &queue = ::arm_compute::CLScheduler::get().queue();
-
-    _output_alloc->map(queue);
-    util::feature::nchw::View<float> output_view{_output_alloc};
-
-    for (auto input : _input_allocs)
-    {
-      input->map(queue);
-      const util::feature::nchw::View<float> input_reader{input};
-
-      for (uint32_t n = 0; n < input_reader.shape().N; n++)
-      {
-        for (uint32_t c = 0; c < input_reader.shape().C; c++)
-        {
-          for (uint32_t h = 0; h < input_reader.shape().H; h++)
-          {
-            for (uint32_t w = 0; w < input_reader.shape().W; w++)
-            {
-              uint32_t no = (_axis == 3) ? axis_offset : 0;
-              uint32_t co = (_axis == 2) ? axis_offset : 0;
-              uint32_t ho = (_axis == 1) ? axis_offset : 0;
-              uint32_t wo = (_axis == 0) ? axis_offset : 0;
-              output_view.at(n + no, c + co, h + ho, w + wo) = input_reader.at(n, c, h, w);
-            }
-          }
-        }
-      }
-      if (_axis == 3)
-        axis_offset += input_reader.shape().N;
-      if (_axis == 2)
-        axis_offset += input_reader.shape().C;
-      if (_axis == 1)
-        axis_offset += input_reader.shape().H;
-      if (_axis == 0)
-        axis_offset += input_reader.shape().W;
-
-      input->unmap(queue);
-    }
-    _output_alloc->unmap(queue);
-  }
-
-  VERBOSE(Concat_RUN) << "End   Concat" << std::endl;
-
-  return true;
-}
-
-void ConcatLayer::configure(
-    const std::vector<::neurun::backend::acl_cl::operand::ICLTensor *> &input_allocs, int32_t axis,
-    ::neurun::backend::acl_cl::operand::ICLTensor *output_alloc)
-{
-  _input_allocs = input_allocs;
-  _output_alloc = output_alloc;
-
-  assert(axis < 4);
-
-  // This map converts NHWC to NCHW(reversed)
-  // NHWC -> WHCN
-  static const uint32_t axis_map[] = {3, 1, 0, 2};
-  _axis = axis_map[axis];
-
-  // TODO Support Quant8
-  _input_type = OperandType::TENSOR_FLOAT32;
-}
-
-void ConcatLayer::run()
-{
-  if (_input_type == OperandType::TENSOR_FLOAT32)
-  {
-    concatenationFloat32();
-  }
-  else if (_input_type == OperandType::TENSOR_QUANT8_ASYMM)
-  {
-    throw std::runtime_error("NYI - concatenationQuant8()");
-  }
-}
-
-} // namespace acl_cl
-} // namespace kernel
-} // namespace neurun