| /* Copyright 2020 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. | |
| ==============================================================================*/ | |
| namespace tflite { | |
| namespace reference_ops { | |
| template <typename T> | |
| T FloorMod(T input1, T input2) { | |
| struct FloatMod { | |
| float operator()(const float lhs, const float rhs) const { | |
| return std::fmod(lhs, rhs); | |
| } | |
| }; | |
| using ModFunc = typename std::conditional<std::is_integral<T>::value, | |
| std::modulus<T>, FloatMod>::type; | |
| ModFunc mod_func; | |
| T trunc_mod = mod_func(input1, input2); | |
| return (trunc_mod != 0) && ((input2 < 0) != (trunc_mod < 0)) | |
| ? (trunc_mod + input2) | |
| : trunc_mod; | |
| } | |
| } // namespace reference_ops | |
| } // namespace tflite | |