Imported Upstream version 1.25.0

[platform/core/ml/nnfw.git] / onert-micro / luci-interpreter / src / kernels / Softmax.cpp

diff --git a/onert-micro/luci-interpreter/src/kernels/Softmax.cpp b/onert-micro/luci-interpreter/src/kernels/Softmax.cpp
index cfc1dfc..4647cc9 100644 (file)
--- a/onert-micro/luci-interpreter/src/kernels/Softmax.cpp
+++ b/onert-micro/luci-interpreter/src/kernels/Softmax.cpp
@@ -1,6 +1,5 @@
 /*
  * 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.
@@ -17,8 +16,8 @@
 
 #include "Builders.h"
 #include "kernels/Utils.h"
+#include "SISOKernel.h"
 
-#include <tensorflow/lite/kernels/internal/reference/softmax.h>
 #include "PALSoftmax.h"
 
 namespace luci_interpreter
@@ -34,97 +33,48 @@ void evalFloat(const circle::Tensor *input, const circle::Tensor *output,
   const auto *input_data = runtime_graph->getDataByTensor(input);
   auto *output_data = runtime_graph->getDataByTensor(output);
 
-  tflite::SoftmaxParams op_params{};
-  op_params.beta = options->beta();
-
-  tflite::reference_ops::Softmax(
-    op_params, kernels::getTensorShape(input), kernels::getTensorData<float>(input_data),
-    kernels::getTensorShape(output), kernels::getTensorData<float>(output_data));
+  luci_interpreter_pal::Softmax(options->beta(), kernels::getTensorShape(input),
+                                kernels::getTensorData<float>(input_data),
+                                kernels::getTensorData<float>(output_data));
 }
 #endif // DIS_FLOAT
 
-#ifndef DIS_QUANT
-template <typename T>
-void evalQuantized(const circle::Tensor *input, const circle::Tensor *output,
-                   const circle::SoftmaxOptions *options, BaseRuntimeGraph *runtime_graph)
-{
-  // TODO: Enable it
-  assert(false && "Not impl yet");
-
-  const auto *input_data = runtime_graph->getDataByTensor(input);
-  auto *output_data = runtime_graph->getDataByTensor(output);
-
-  tflite::SoftmaxParams op_params{};
-
-  luci_interpreter_pal::InitializeParams(&op_params, Tensor::scale(input), options->beta());
-  luci_interpreter_pal::Softmax(
-    op_params, kernels::getTensorShape(input), kernels::getTensorData<T>(input_data),
-    kernels::getTensorShape(output), kernels::getTensorData<T>(output_data));
-}
-#endif
-
 } // namespace
 
 void configure_kernel_CircleSoftmax(const circle::Operator *cur_op, BaseRuntimeGraph *runtime_graph)
 {
-  const auto input_index = cur_op->inputs()->operator[](0);
-  const auto output_index = cur_op->outputs()->operator[](0);
-
-  assert(input_index != -1);
-  assert(output_index != -1);
-
-  const auto input = runtime_graph->getCircleTensorByIndex(input_index);
-  auto output = runtime_graph->getCircleTensorByIndex(output_index);
+  kernels::SISOKernel kernel(cur_op, runtime_graph);
 
-  assert(input != nullptr);
-  assert(output != nullptr);
-
-  LUCI_INTERPRETER_CHECK(Tensor::element_type(input) == Tensor::element_type(output));
-  LUCI_INTERPRETER_CHECK(Tensor::num_dims(input) >= 1);
+  LUCI_INTERPRETER_CHECK(Tensor::element_type(kernel.input()) ==
+                         Tensor::element_type(kernel.output()));
+  LUCI_INTERPRETER_CHECK(Tensor::num_dims(kernel.input()) >= 1);
 
 #ifndef DIS_QUANT
-  if (Tensor::element_type(input) == DataType::U8 || Tensor::element_type(input) == DataType::S8)
+  if (Tensor::element_type(kernel.input()) == DataType::U8 ||
+      Tensor::element_type(kernel.input()) == DataType::S8)
   {
-    LUCI_INTERPRETER_CHECK(Tensor::element_type(input) == DataType::S8 ||
-                           Tensor::zero_point(output) == 0);
-    LUCI_INTERPRETER_CHECK(Tensor::element_type(input) == DataType::U8 ||
-                           Tensor::zero_point(output) == std::numeric_limits<int8_t>::min());
+    LUCI_INTERPRETER_CHECK(Tensor::element_type(kernel.input()) == DataType::S8 ||
+                           Tensor::zero_point(kernel.output()) == 0);
+    LUCI_INTERPRETER_CHECK(Tensor::element_type(kernel.input()) == DataType::U8 ||
+                           Tensor::zero_point(kernel.output()) ==
+                             std::numeric_limits<int8_t>::min());
   }
 #endif
 }
 
-void execute_kernel_CircleSoftmax(const circle::Operator *cur_op, BaseRuntimeGraph *runtime_graph,
-                                  bool)
+void execute_kernel_CircleSoftmax(const circle::Operator *cur_op, BaseRuntimeGraph *runtime_graph)
 {
-  const auto input_index = cur_op->inputs()->operator[](0);
-  const auto output_index = cur_op->outputs()->operator[](0);
-
-  assert(input_index != -1);
-  assert(output_index != -1);
-
-  const auto input = runtime_graph->getCircleTensorByIndex(input_index);
-  auto output = runtime_graph->getCircleTensorByIndex(output_index);
-
-  assert(input != nullptr);
-  assert(output != nullptr);
+  kernels::SISOKernel kernel(cur_op, runtime_graph);
 
   const auto *options = cur_op->builtin_options_as_SoftmaxOptions();
 
-  switch (Tensor::element_type(input))
+  switch (Tensor::element_type(kernel.input()))
   {
 #ifndef DIS_FLOAT
     case DataType::FLOAT32:
-      evalFloat(input, output, options, runtime_graph);
+      evalFloat(kernel.input(), kernel.output(), options, runtime_graph);
       break;
 #endif // DIS_FLOAT
-#ifndef DIS_QUANT
-    case DataType::S8:
-      evalQuantized<int8_t>(input, output, options, runtime_graph);
-      break;
-    case DataType::U8:
-      evalQuantized<uint8_t>(input, output, options, runtime_graph);
-      break;
-#endif // DIS_QUANT
     default:
       assert(false && "Unsupported type.");
   }