1 files changed, 0 insertions, 121 deletions
diff --git a/libs/ARMComputeEx/src/runtime/CL/functions/CLReduceMax.cpp b/libs/ARMComputeEx/src/runtime/CL/functions/CLReduceMax.cpp
deleted file mode 100644
index 3382058db..000000000
--- a/libs/ARMComputeEx/src/runtime/CL/functions/CLReduceMax.cpp
+++ /dev/null
@@ -1,121 +0,0 @@
-/*
- * Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved
- * Copyright (c) 2017 ARM Limited.
- *
- * 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 "arm_compute/runtime/CL/functions/CLReduceMax.h"
-
-#include "arm_compute/core/CL/ICLTensor.h"
-#include "support/ToolchainSupport.h"
-#include "arm_compute/core/CL/CLHelpers.h"
-#include "arm_compute/core/CL/kernels/CLReduceMaxKernel.h"
-
-#include <vector>
-#include <algorithm>
-
-#include <utility>
-
-#define REDUCE_MAX_RUN_ON_CPU 1
-
-namespace arm_compute
-{
-
-CLReduceMax::CLReduceMax() : _axis(0), _input(nullptr), _output(nullptr), _kernel(nullptr) {}
-
-void CLReduceMax::configure(ICLTensor *input, int axis, ICLTensor *output)
-{
-  _axis = axis;
-
-  _input = input;
-  _output = output;
-
-  auto k = arm_compute::support::cpp14::make_unique<CLReduceMaxKernel>();
-  k->configure(input, axis, output);
-  _kernel = std::move(k);
-
-  // We can handle for simple case only
-  // Output rank: 1
-  // Axis: one axis value, restrict to 1
-  ARM_COMPUTE_ERROR_ON(input->info()->tensor_shape().num_dimensions() != 2);
-  ARM_COMPUTE_ERROR_ON(output->info()->tensor_shape().num_dimensions() != 1);
-  ARM_COMPUTE_ERROR_ON(axis != 1);
-}
-
-Status CLReduceMax::validate(const ITensorInfo *input, int32_t axis, const ITensorInfo *output)
-{
-  return CLReduceMaxKernel::validate(input, axis, output);
-}
-
-void CLReduceMax::run()
-{
-#if REDUCE_MAX_RUN_ON_CPU
-  run_on_cpu();
-
-  arm_compute::CLScheduler::get().sync();
-#else
-  arm_compute::CLScheduler::get().enqueue(*_kernel);
-#endif
-}
-
-void CLReduceMax::run_on_cpu()
-{
-  cl::CommandQueue q = CLScheduler::get().queue();
-
-  _input->map(q);
-  _output->map(q);
-
-  // Compute by CPU for simple case
-  // Input rank: 2
-  // Output rank: 1
-  // Axis: one axis value, restrict to 1
-
-  float *input_data = (float *)_input->buffer();
-  float *output_data = (float *)_output->buffer();
-
-  std::vector<float> container_max;
-  int cols = _input->info()->tensor_shape()[0];
-  int rows = _input->info()->tensor_shape()[1];
-  container_max.resize(rows);
-
-  // Initialize as 1st element in row
-  float *input_pointer = input_data;
-  for (int i = 0; i < rows; i++)
-  {
-    container_max[i] = *input_pointer;
-    input_pointer += cols;
-  }
-
-  // Update max value in row
-  for (int i = 0; i < rows; i++)
-  {
-    float max_in_row = container_max[i];
-    for (int j = 1; j < cols; j++)
-    {
-      if (max_in_row < input_data[i * cols + j])
-      {
-        max_in_row = input_data[i * cols + j];
-      }
-    }
-    container_max[i] = max_in_row;
-  }
-
-  for (int i = 0; i < rows; i++)
-  {
-    output_data[i] = container_max[i];
-  }
-
-  _input->unmap(q);
-  _output->unmap(q);
-}
-} // namespace arm_compute