1 files changed, 0 insertions, 142 deletions
diff --git a/runtimes/pure_arm_compute/src/internal/layers/SimpleSpaceToBatchND.cc b/runtimes/pure_arm_compute/src/internal/layers/SimpleSpaceToBatchND.cc
deleted file mode 100644
index f53675b99..000000000
--- a/runtimes/pure_arm_compute/src/internal/layers/SimpleSpaceToBatchND.cc
+++ /dev/null
@@ -1,142 +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 "internal/layers/SimpleSpaceToBatchND.h"
-
-#include <arm_compute/runtime/CL/CLScheduler.h>
-
-void SimpleSpaceToBatchND::configure(::arm_compute::ITensor *input,
-                                     ::arm_compute::ITensor *block_size,
-                                     ::arm_compute::ITensor *padding_size,
-                                     ::arm_compute::ITensor *output)
-{
-  const auto rank = input->info()->num_dimensions();
-  assert(rank == 4);
-
-  _input = input;
-  _block_size = block_size;
-  _padding_size = padding_size;
-  _output = output;
-}
-
-template <typename T>
-inline void
-SpaceToBatchND(const ::arm_compute::ITensor *input, const ::arm_compute::TensorShape &input_shape,
-               const ::arm_compute::ITensor *block_size, const ::arm_compute::ITensor *padding_size,
-               const ::arm_compute::ITensor *output, const ::arm_compute::TensorShape &output_shape,
-               T zero_value)
-{
-  const int input_batch = input_shape[3];
-  const int input_height = input_shape[1];
-  const int input_width = input_shape[0];
-
-  const int depth = output_shape[2];
-
-  const int padding_height_left = *reinterpret_cast<int *>(padding_size->ptr_to_element({0, 1}));
-  const int padding_height_right = *reinterpret_cast<int *>(padding_size->ptr_to_element({1, 1}));
-  const int padding_width_left = *reinterpret_cast<int *>(padding_size->ptr_to_element({0, 0}));
-  const int padding_width_right = *reinterpret_cast<int *>(padding_size->ptr_to_element({1, 0}));
-  const int padded_height = input_height + padding_height_left + padding_height_right;
-  const int padded_width = input_width + padding_width_left + padding_width_right;
-
-  const int block_size_height = *reinterpret_cast<int *>(block_size->ptr_to_element({1}));
-  const int block_size_width = *reinterpret_cast<int *>(block_size->ptr_to_element({0}));
-
-  assert(padding_height_left >= 0);
-  assert(padding_height_right >= 0);
-  assert(padding_width_left >= 0);
-  assert(padding_width_right >= 0);
-  assert(block_size_height >= 1);
-  assert(block_size_width >= 1);
-  assert(padded_height % block_size_height == 0);
-  assert(padded_width % block_size_width == 0);
-  assert(output->info()->dimension(3) ==
-         input->info()->dimension(3) * (block_size_height * block_size_width));
-
-  for (int in_b = 0; in_b < input_batch; ++in_b)
-  {
-    for (int in_d = 0; in_d < depth; ++in_d)
-    {
-      for (int in_h = 0; in_h < padded_height; ++in_h)
-      {
-        for (int in_w = 0; in_w < padded_width; ++in_w)
-        {
-          const int out_d = in_d;
-          const int out_h = in_h / block_size_height;
-          const int out_w = in_w / block_size_width;
-          const int out_b =
-              in_b +
-              ((in_h % block_size_height) * block_size_width + in_w % block_size_width) *
-                  input_batch;
-
-          const ::arm_compute::Coordinates output_id{out_w, out_h, out_d, out_b};
-
-          if (in_h < padding_height_left || in_h >= (input_height + padding_height_left) ||
-              in_w < padding_width_left || in_w >= (input_width + padding_width_left))
-          {
-            *reinterpret_cast<T *>(output->ptr_to_element(output_id)) = zero_value;
-          }
-          else
-          {
-            const ::arm_compute::Coordinates input_id{in_w - padding_width_left,
-                                                      in_h - padding_height_left, in_d, in_b};
-            *reinterpret_cast<T *>(output->ptr_to_element(output_id)) =
-                *reinterpret_cast<T *>(input->ptr_to_element(input_id));
-          }
-        }
-      }
-    }
-  }
-}
-void SimpleSpaceToBatchND::run()
-{
-  if (::internal::arm_compute::isGpuMode())
-  {
-    auto &q = ::arm_compute::CLScheduler::get().queue();
-
-    CAST_CL(_input)->map(q);
-    CAST_CL(_block_size)->map(q);
-    CAST_CL(_padding_size)->map(q);
-    CAST_CL(_output)->map(q);
-  }
-
-  switch (_input->info()->data_type())
-  {
-    case ::arm_compute::DataType::U8:
-    case ::arm_compute::DataType::QASYMM8:
-      SpaceToBatchND<uint8_t>(_input, _input->info()->tensor_shape(), _block_size, _padding_size,
-                              _output, _output->info()->tensor_shape(),
-                              _input->info()->quantization_info().offset);
-      break;
-    case ::arm_compute::DataType::F32:
-      SpaceToBatchND<float>(_input, _input->info()->tensor_shape(), _block_size, _padding_size,
-                            _output, _output->info()->tensor_shape(), 0.0f);
-      break;
-    default:
-      ARM_COMPUTE_ERROR("DataType not supported");
-      break;
-  }
-
-  if (::internal::arm_compute::isGpuMode())
-  {
-    auto &q = ::arm_compute::CLScheduler::get().queue();
-
-    CAST_CL(_input)->unmap(q);
-    CAST_CL(_block_size)->unmap(q);
-    CAST_CL(_padding_size)->unmap(q);
-    CAST_CL(_output)->unmap(q);
-  }
-}