compiler/luci-interpreter/src/kernels/Mul.cpp

   1 /*
   2  * Copyright (c) 2020 Samsung Electronics Co., Ltd. All Rights Reserved
   3  * Copyright 2019 The TensorFlow Authors. All Rights Reserved.
   4  *
   5  * Licensed under the Apache License, Version 2.0 (the "License");
   6  * you may not use this file except in compliance with the License.
   7  * You may obtain a copy of the License at
   8  *
   9  *    http://www.apache.org/licenses/LICENSE-2.0
  10  *
  11  * Unless required by applicable law or agreed to in writing, software
  12  * distributed under the License is distributed on an "AS IS" BASIS,
  13  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  14  * See the License for the specific language governing permissions and
  15  * limitations under the License.
  16  */
  17
  18 #include "kernels/Mul.h"
  19
  20 #include "kernels/Utils.h"
  21
  22 #include <tensorflow/lite/kernels/internal/optimized/optimized_ops.h>
  23 #include <tensorflow/lite/kernels/internal/reference/process_broadcast_shapes.h>
  24
  25 #include <stdexcept>
  26
  27 namespace luci_interpreter
  28 {
  29 namespace kernels
  30 {
  31
  32 Mul::Mul(const Tensor *input1, const Tensor *input2, Tensor *output, const MulParams &params)
  33     : KernelWithParams<MulParams>({input1, input2}, {output}, params)
  34 {
  35 }
  36
  37 void Mul::configure()
  38 {
  39   assert(input1()->element_type() == input2()->element_type());
  40   output()->resize(calculateShapeForBroadcast(input1()->shape(), input2()->shape()));
  41 }
  42
  43 void Mul::execute() const
  44 {
  45   switch (input1()->element_type())
  46   {
  47     case DataType::FLOAT32:
  48       evalFloat();
  49       break;
  50     default:
  51       throw std::runtime_error("Unsupported type.");
  52   }
  53 }
  54
  55 void Mul::evalFloat() const
  56 {
  57   float activation_min{};
  58   float activation_max{};
  59   calculateActivationRange(_params.activation, &activation_min, &activation_max);
  60
  61   tflite::ArithmeticParams params{};
  62   params.float_activation_min = activation_min;
  63   params.float_activation_max = activation_max;
  64
  65   const bool need_broadcast = tflite::reference_ops::ProcessBroadcastShapes(
  66       getTensorShape(input1()), getTensorShape(input2()), &params);
  67
  68   if (need_broadcast)
  69   {
  70     tflite::optimized_ops::BroadcastMul4DSlow(
  71         params, getTensorShape(input1()), getTensorData<float>(input1()), getTensorShape(input2()),
  72         getTensorData<float>(input2()), getTensorShape(output()), getTensorData<float>(output()));
  73   }
  74   else
  75   {
  76     tflite::optimized_ops::Mul(params, getTensorShape(input1()), getTensorData<float>(input1()),
  77                                getTensorShape(input2()), getTensorData<float>(input2()),
  78                                getTensorShape(output()), getTensorData<float>(output()));
  79   }
  80 }
  81
  82 } // namespace kernels
  83 } // namespace luci_interpreter