1 files changed, 0 insertions, 104 deletions
diff --git a/libs/kernel/acl/src/cl/Concatenation.cpp b/libs/kernel/acl/src/cl/Concatenation.cpp
deleted file mode 100644
index 9376006ca..000000000
--- a/libs/kernel/acl/src/cl/Concatenation.cpp
+++ /dev/null
@@ -1,104 +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 <OperationsUtils.h>
-#include <arm_compute/core/TensorShape.h>
-#include <arm_compute/core/TensorInfo.h>
-
-#include <cassert>
-
-// TODO: fix include path in CMakeFiles
-#include "../IO_accessor.h"
-#include "../shape.h"
-
-namespace nnfw {
-namespace kernel {
-namespace acl {
-
-bool concatenationFloat32(const std::vector<const float*>& inputDataPtrs,
-                          const std::vector<nnfw::rt::Shape>& inputShapes, int32_t axis,
-                          float* outputData, const nnfw::rt::Shape& outputShape)
-{
-  if (axis != 3)
-  {
-    assert("Only support axis=3 for ACL" && 0);
-    return false;
-  }
-  assert(inputDataPtrs.size() == inputShapes.size());
-
-  std::vector<arm_compute::CLTensor*> inputPtrs;
-  std::vector<arm_compute::ICLTensor*> inputIptrs;
-  arm_compute::CLTensor output;
-
-  // init Tensors
-  std::vector<nnfw::rt::Shape>::const_iterator it_inputShape = inputShapes.begin();
-  for (auto inputData : inputDataPtrs)
-  {
-    const nnfw::rt::Shape& inputShape = *it_inputShape;
-    arm_compute::TensorShape input_shape = util::fromNNShape(inputShape);
-    arm_compute::CLTensor* inputPtr = new arm_compute::CLTensor();
-
-    inputPtr->allocator()->init(arm_compute::TensorInfo(input_shape, arm_compute::Format::F32));
-    inputPtrs.push_back(inputPtr);
-    inputIptrs.push_back(inputPtr);
-
-    it_inputShape++;
-  }
-  arm_compute::TensorShape output_shape = util::fromNNShape(outputShape);
-  output.allocator()->init(arm_compute::TensorInfo(output_shape, arm_compute::Format::F32));
-
-  // prepare ACL Concatenate and configure tensors
-  auto concat = std::make_shared<arm_compute::CLDepthConcatenateLayer>();
-  concat->configure(inputIptrs, &output);
-
-  // allocate Tensors
-  it_inputShape = inputShapes.begin();
-  std::vector<const float*>::const_iterator it_inputData = inputDataPtrs.begin();
-  for (auto inputPtr : inputPtrs)
-  {
-    inputPtr->allocator()->allocate();
-
-    const float* inputData = *it_inputData;
-    const nnfw::rt::Shape& inputShape = *it_inputShape;
-
-    TensorAccess<InputAccessor>(*inputPtr, inputData, inputShape);
-
-    it_inputShape++;
-    it_inputData++;
-  }
-  output.allocator()->allocate();
-
-  // run
-  concat->run();
-  arm_compute::CLScheduler::get().sync();
-
-  // get output
-  TensorAccess<OutputAccessor>(output, outputData, outputShape);
-
-  // cleanup
-  for (auto inputPtr : inputPtrs)
-  {
-    inputPtr->allocator()->free();
-    delete inputPtr;
-  }
-  output.allocator()->free();
-
-  return true;
-}
-
-} // namespace acl
-} // namespace kernel
-} // namespace nnfw