| /* |
| * Copyright (C) 2018 The Android Open Source Project |
| * |
| * 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. |
| */ |
| |
| #ifndef FRAMEWORKS_ML_NN_MULTINOMIAL_H |
| #define FRAMEWORKS_ML_NN_MULTINOMIAL_H |
| |
| #include "HalOperation.h" |
| |
| #include "tensorflow/contrib/lite/kernels/internal/tensor_utils.h" |
| |
| #include <algorithm> |
| #include <cmath> |
| |
| namespace android { |
| namespace nn { |
| |
| struct RunTimeOperandInfo; |
| struct Shape; |
| |
| class Multinomial { |
| public: |
| Multinomial(const android::hardware::neuralnetworks::V1_2::Operation& operation, |
| std::vector<RunTimeOperandInfo>& operands); |
| |
| static bool Prepare(const hardware::neuralnetworks::V1_2::Operation& operation, |
| std::vector<RunTimeOperandInfo>& operands, Shape* outputShape); |
| bool Eval(); |
| |
| static constexpr int kInputTensor = 0; |
| static constexpr int kSampleCountParam = 1; |
| static constexpr int kRandomSeedsTensor = 2; |
| |
| static constexpr int kOutputTensor = 0; |
| |
| private: |
| RunTimeOperandInfo* input_; |
| int sample_count_; |
| RunTimeOperandInfo* random_seeds_; |
| |
| RunTimeOperandInfo* output_; |
| }; |
| |
| } // namespace nn |
| } // namespace android |
| |
| #endif // FRAMEWORKS_ML_NN_MULTINOMIAL_H |