1 files changed, 0 insertions, 143 deletions
diff --git a/runtime/neurun/backend/cpu/kernel/DepthwiseConvolutionLayer.cc b/runtime/neurun/backend/cpu/kernel/DepthwiseConvolutionLayer.cc
deleted file mode 100644
index e33e3465e..000000000
--- a/runtime/neurun/backend/cpu/kernel/DepthwiseConvolutionLayer.cc
+++ /dev/null
@@ -1,143 +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 "DepthwiseConvolutionLayer.h"
-
-#include <cker/operation/DepthwiseConv.h>
-
-namespace neurun
-{
-namespace backend
-{
-namespace cpu
-{
-namespace kernel
-{
-
-DepthwiseConvolutionLayer::DepthwiseConvolutionLayer()
-    : _inputData(), _kernelData(), _outputData(), _biasData(), _inputDescr(), _kernelDescr(),
-      _outputDescr(), _biasDescr(), _paddingLeft(0), _paddingTop(0), _paddingRight(0),
-      _paddingBottom(0), _strideWidth(0), _strideHeight(0), _multiplier(0),
-      _activation(ir::Activation::NONE), _inputType(OperandType::FLOAT32)
-{
-  // DO NOTHING
-}
-
-void DepthwiseConvolutionLayer::convFloat32()
-{
-  float output_activation_min, output_activation_max;
-  CalculateActivationRangeFloat(_activation, &output_activation_min, &output_activation_max);
-
-  nnfw::cker::DepthwiseConvParams op_params;
-  op_params.stride_width = _strideWidth;
-  op_params.stride_height = _strideHeight;
-  op_params.dilation_width_factor = 1;
-  op_params.dilation_height_factor = 1;
-  op_params.padding_values.width = _paddingLeft;
-  op_params.padding_values.height = _paddingTop;
-  op_params.depth_multiplier = _multiplier;
-  op_params.float_activation_min = output_activation_min;
-  op_params.float_activation_max = output_activation_max;
-
-  nnfw::cker::DepthwiseConv(op_params, convertTensorDescriptorToCkerShape(_inputDescr),
-                            _inputData.f, convertTensorDescriptorToCkerShape(_kernelDescr),
-                            _kernelData.f, convertTensorDescriptorToCkerShape(_biasDescr),
-                            _biasData.f, convertTensorDescriptorToCkerShape(_outputDescr),
-                            _outputData.f);
-}
-
-void DepthwiseConvolutionLayer::convQuant8()
-{
-  int32_t output_activation_min = 0;
-  int32_t output_activation_max = 0;
-  CalculateActivationRangeUint8(_activation, _outputDescr, &output_activation_min,
-                                &output_activation_max);
-
-  float real_multiplier = 0.0;
-  int32_t output_multiplier = 0;
-  int32_t output_shift = 0;
-  GetQuantizedConvolutionMultiplier(_inputDescr, _kernelDescr, _biasDescr, _outputDescr,
-                                    &real_multiplier);
-  QuantizeMultiplier(real_multiplier, &output_multiplier, &output_shift);
-
-  nnfw::cker::DepthwiseConvParams op_params;
-  op_params.stride_width = _strideWidth;
-  op_params.stride_height = _strideHeight;
-  op_params.dilation_width_factor = 1;
-  op_params.dilation_height_factor = 1;
-  op_params.padding_values.width = _paddingLeft;
-  op_params.padding_values.height = _paddingTop;
-  op_params.depth_multiplier = _multiplier;
-  op_params.input_offset = -_inputDescr.offset;
-  op_params.weights_offset = -_kernelDescr.offset;
-  op_params.output_offset = _outputDescr.offset;
-  op_params.output_multiplier = output_multiplier;
-  op_params.output_shift = output_shift;
-  op_params.quantized_activation_min = output_activation_min;
-  op_params.quantized_activation_max = output_activation_max;
-
-  nnfw::cker::DepthwiseConv(op_params, convertTensorDescriptorToCkerShape(_inputDescr),
-                            _inputData.u8, convertTensorDescriptorToCkerShape(_kernelDescr),
-                            _kernelData.u8, convertTensorDescriptorToCkerShape(_biasDescr),
-                            _biasData.i32, convertTensorDescriptorToCkerShape(_outputDescr),
-                            _outputData.u8);
-}
-
-void DepthwiseConvolutionLayer::configure(uint8_t *inputData, const TensorDescriptor inputDescr,
-                                          uint8_t *kernelData, const TensorDescriptor kernelDescr,
-                                          uint8_t *biasData, const TensorDescriptor biasDescr,
-                                          const uint32_t paddingLeft, const uint32_t paddingRight,
-                                          const uint32_t paddingTop, const uint32_t paddingBottom,
-                                          const uint32_t strideWidth, const uint32_t strideHeight,
-                                          const uint32_t multiplier,
-                                          const ir::Activation activation, uint8_t *outputData,
-                                          const TensorDescriptor outputDescr)
-{
-  _inputData.u8 = inputData;
-  _inputDescr = inputDescr;
-  _inputType = inputDescr.type;
-  _kernelData.u8 = kernelData;
-  _kernelDescr = kernelDescr;
-  _biasData.u8 = biasData;
-  _biasDescr = biasDescr;
-  _paddingLeft = paddingLeft;
-  _paddingRight = paddingRight;
-  _paddingTop = paddingTop;
-  _paddingBottom = paddingBottom;
-  _strideWidth = strideWidth;
-  _strideHeight = strideHeight;
-  _multiplier = multiplier;
-  _activation = activation;
-  _outputData.u8 = outputData;
-  _outputDescr = outputDescr;
-}
-
-void DepthwiseConvolutionLayer::run()
-{
-  if (_inputType == OperandType::FLOAT32)
-  {
-    convFloat32();
-  }
-  else if (_inputType == OperandType::QUANT8_ASYMM)
-  {
-    convQuant8();
-  }
-}
-
-} // namespace kernel
-} // namespace cpu
-} // namespace backend
-} // namespace neurun