Concatenation.cpp

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/*
 * Copyright (c) 2020 Samsung Electronics Co., Ltd. All Rights Reserved
 * Copyright 2019 The TensorFlow Authors. 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 "kernels/Concatenation.h"
#include "kernels/Utils.h"
 
#include <tensorflow/lite/kernels/internal/reference/concatenation.h>
 
#include <stdexcept>
 
namespace luci_interpreter
{
namespace kernels
{
 
Concatenation::Concatenation(std::vector<const Tensor *> inputs, Tensor *output,
                             const ConcatenationParams &params)
  : KernelWithParams<ConcatenationParams>(std::move(inputs), {output}, params)
{
}
 
void Concatenation::configure()
{
  const int num_inputs = _inputs.size();
  LUCI_INTERPRETER_CHECK(num_inputs > 0);
  const Tensor *t0 = _inputs[0];
 
  // TODO: Support concat with fused activation function
  LUCI_INTERPRETER_CHECK(params().activation == luci::FusedActFunc::NONE);
 
  int axis = _params.axis;
  if (axis < 0)
    axis += t0->shape().num_dims();
  LUCI_INTERPRETER_CHECK(axis >= 0 && axis < t0->shape().num_dims());
 
  int32_t sum_axis = t0->shape().dim(axis);
  for (int i = 1; i < num_inputs; ++i)
  {
    const Tensor *tensor = _inputs[i];
    LUCI_INTERPRETER_CHECK(tensor->element_type() == t0->element_type());
    LUCI_INTERPRETER_CHECK(tensor->shape().num_dims() == t0->shape().num_dims());
    for (int d = 0; d < t0->shape().num_dims(); ++d)
    {
      if (d == axis)
      {
        sum_axis += tensor->shape().dim(axis);
      }
      else
      {
        LUCI_INTERPRETER_CHECK(tensor->shape().dim(d) == t0->shape().dim(d));
      }
    }
  }
 
  Shape output_shape = t0->shape();
  output_shape.dim(axis) = sum_axis;
 
  // If input tensors are INT8 type then quantization parameters of all input tensors and the output
  // should be the same
  for (auto current_tensor : _inputs)
  {
    if (current_tensor->element_type() == DataType::S8)
    {
      LUCI_INTERPRETER_CHECK(current_tensor->quantized_dimension() ==
                             output()->quantized_dimension());
 
      LUCI_INTERPRETER_CHECK(current_tensor->zero_points().size() ==
                             current_tensor->scales().size());
      LUCI_INTERPRETER_CHECK(current_tensor->zero_points() == output()->zero_points());
      LUCI_INTERPRETER_CHECK(current_tensor->scales() == output()->scales());
    }
  }
  output()->resize(output_shape);
}
 
void Concatenation::execute() const
{
  switch (_inputs[0]->element_type())
  {
    case DataType::FLOAT32:
      evalGeneric<float>();
      break;
    case DataType::U8:
      evalQuantized();
      break;
    case DataType::S8:
      evalGeneric<int8_t>();
      break;
    case DataType::S32:
      evalGeneric<int32_t>();
      break;
    case DataType::S64:
      evalGeneric<int64_t>();
      break;
    default:
      throw std::runtime_error("luci-intp Concatenation Unsupported type.");
  }
}
 
template <typename T> void Concatenation::evalGeneric() const
{
  int axis = _params.axis;
  if (axis < 0)
    axis += output()->shape().num_dims();
 
  VectorOfTensors<T, true> inputs(_inputs);
  tflite::ConcatenationParams params{};
  params.axis = axis;
  params.inputs_count = _inputs.size();
  tflite::reference_ops::Concatenation(params, inputs.shapes(), inputs.data(),
                                       getTensorShape(output()), getTensorData<T>(output()));
}
 
void Concatenation::evalQuantized() const
{
  int axis = _params.axis;
  if (axis < 0)
    axis += output()->shape().num_dims();
 
  VectorOfQuantizedTensors<true> inputs(_inputs);
  tflite::ConcatenationParams params{};
  params.axis = axis;
  params.input_zeropoint = inputs.zero_point();
  params.input_scale = inputs.scale();
  params.inputs_count = _inputs.size();
  params.output_zeropoint = output()->zero_point();
  params.output_scale = output()->scale();
 
  tflite::reference_ops::ConcatenationWithScaling(params, inputs.shapes(), inputs.data(),
                                                  getTensorShape(output()),
                                                  getTensorData<uint8_t>(output()));
}
 
} // namespace kernels
} // namespace luci_interpreter