2 * Copyright (c) 2020 Samsung Electronics Co., Ltd. All Rights Reserved
4 * Licensed under the Apache License, Version 2.0 (the "License");
5 * you may not use this file except in compliance with the License.
6 * You may obtain a copy of the License at
8 * http://www.apache.org/licenses/LICENSE-2.0
10 * Unless required by applicable law or agreed to in writing, software
11 * distributed under the License is distributed on an "AS IS" BASIS,
12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13 * See the License for the specific language governing permissions and
14 * limitations under the License.
17 #include "kernels/Logistic.h"
19 #include "kernels/Utils.h"
21 #include <tensorflow/lite/kernels/internal/reference/logistic.h>
23 namespace luci_interpreter
28 Logistic::Logistic(const Tensor *input, Tensor *output) : Kernel({input}, {output}) {}
30 void Logistic::configure()
32 LUCI_INTERPRETER_CHECK(input()->element_type() == output()->element_type());
33 if (input()->element_type() == DataType::U8)
35 LUCI_INTERPRETER_CHECK(output()->scale() == 1. / 256);
36 populateLookupTable();
38 output()->resize(input()->shape());
41 void Logistic::execute() const
43 switch (input()->element_type())
45 case DataType::FLOAT32:
52 throw std::runtime_error("Unsupported type.");
56 void Logistic::evalFloat() const
58 tflite::reference_ops::Logistic(getTensorShape(input()), getTensorData<float>(input()),
59 getTensorShape(output()), getTensorData<float>(output()));
62 void Logistic::evalQuantized() const
64 const int size = tflite::MatchingFlatSize(getTensorShape(input()), getTensorShape(output()));
65 uint8_t *output_data = getTensorData<uint8_t>(output());
66 const uint8_t *input_data = getTensorData<uint8_t>(input());
67 for (int i = 0; i < size; ++i)
69 output_data[i] = getTableValue(input_data[i]);
73 void Logistic::populateLookupTable()
75 const auto input_scale = static_cast<double>(input()->scale());
76 const auto input_zero_point = static_cast<int32_t>(input()->zero_point());
77 const auto output_scale = static_cast<double>(output()->scale());
78 const auto output_zero_point = static_cast<int32_t>(output()->zero_point());
79 const float inverse_scale = 1 / output_scale;
80 int32_t maxval = std::numeric_limits<uint8_t>::max();
81 int32_t minval = std::numeric_limits<uint8_t>::min();
82 for (int32_t val = minval; val <= maxval; ++val)
84 const float dequantized = input_scale * (val - input_zero_point);
85 const float transformed = 1.0f / (1.0f + std::exp(-dequantized));
86 const float rescaled = std::round(transformed * inverse_scale);
87 const int32_t quantized = static_cast<int32_t>(rescaled + output_zero_point);
88 setTableValue(static_cast<uint8_t>(std::max(std::min(maxval, quantized), minval)),
89 static_cast<uint8_t>(val));
93 } // namespace kernels
94 } // namespace luci_interpreter