| /* |
| * Copyright (c) 2016, Alliance for Open Media. All rights reserved |
| * |
| * This source code is subject to the terms of the BSD 2 Clause License and |
| * the Alliance for Open Media Patent License 1.0. If the BSD 2 Clause License |
| * was not distributed with this source code in the LICENSE file, you can |
| * obtain it at www.aomedia.org/license/software. If the Alliance for Open |
| * Media Patent License 1.0 was not distributed with this source code in the |
| * PATENTS file, you can obtain it at www.aomedia.org/license/patent. |
| */ |
| |
| #ifndef AV1_ENCODER_ML_H_ |
| #define AV1_ENCODER_ML_H_ |
| |
| #ifdef __cplusplus |
| extern "C" { |
| #endif |
| |
| #define NN_MAX_HIDDEN_LAYERS 10 |
| #define NN_MAX_NODES_PER_LAYER 128 |
| |
| typedef struct { |
| int num_inputs; // Number of input nodes, i.e. features. |
| int num_outputs; // Number of output nodes. |
| int num_hidden_layers; // Number of hidden layers, maximum 10. |
| // Number of nodes for each hidden layer. |
| int num_hidden_nodes[NN_MAX_HIDDEN_LAYERS]; |
| // Weight parameters, indexed by layer. |
| const float *weights[NN_MAX_HIDDEN_LAYERS + 1]; |
| // Bias parameters, indexed by layer. |
| const float *bias[NN_MAX_HIDDEN_LAYERS + 1]; |
| } NN_CONFIG; |
| |
| // Calculate prediction based on the given input features and neural net config. |
| // Assume there are no more than NN_MAX_NODES_PER_LAYER nodes in each hidden |
| // layer. |
| void av1_nn_predict(const float *features, const NN_CONFIG *nn_config, |
| float *output); |
| |
| #ifdef __cplusplus |
| } // extern "C" |
| #endif |
| |
| #endif // AV1_ENCODER_RD_H_ |