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Diffstat (limited to 'third_party/aom/av1/encoder/ml.h')
-rw-r--r-- | third_party/aom/av1/encoder/ml.h | 85 |
1 files changed, 85 insertions, 0 deletions
diff --git a/third_party/aom/av1/encoder/ml.h b/third_party/aom/av1/encoder/ml.h new file mode 100644 index 0000000000..566f9271dd --- /dev/null +++ b/third_party/aom/av1/encoder/ml.h @@ -0,0 +1,85 @@ +/* + * 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 AOM_AV1_ENCODER_ML_H_ +#define AOM_AV1_ENCODER_ML_H_ + +#ifdef __cplusplus +extern "C" { +#endif + +#include "config/av1_rtcd.h" + +#define NN_MAX_HIDDEN_LAYERS 10 +#define NN_MAX_NODES_PER_LAYER 128 + +struct NN_CONFIG { + 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]; +}; +// Typedef from struct NN_CONFIG to NN_CONFIG is in rtcd_defs + +#if CONFIG_NN_V2 +// Fully-connectedly layer configuration +struct FC_LAYER { + const int num_inputs; // Number of input nodes, i.e. features. + const int num_outputs; // Number of output nodes. + + float *weights; // Weight parameters. + float *bias; // Bias parameters. + const ACTIVATION activation; // Activation function. + + float *output; // The output array. + float *dY; // Gradient of outputs + float *dW; // Gradient of weights. + float *db; // Gradient of bias +}; + +// NN configure structure V2 +struct NN_CONFIG_V2 { + const int num_hidden_layers; // Number of hidden layers, max = 10. + FC_LAYER layer[NN_MAX_HIDDEN_LAYERS + 1]; // The layer array + const int num_logits; // Number of output nodes. + float *logits; // Raw prediction (same as output of final layer) + const LOSS loss; // Loss function +}; + +// 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_v2(const float *features, NN_CONFIG_V2 *nn_config, + int reduce_prec, float *output); +#endif // CONFIG_NN_V2 + +// Applies the softmax normalization function to the input +// to get a valid probability distribution in the output: +// output[i] = exp(input[i]) / sum_{k \in [0,n)}(exp(input[k])) +void av1_nn_softmax(const float *input, float *output, int n); + +// A faster but less accurate version of av1_nn_softmax(input, output, 16) +void av1_nn_fast_softmax_16_c(const float *input, float *output); + +// Applies a precision reduction to output of av1_nn_predict to prevent +// mismatches between C and SIMD implementations. +void av1_nn_output_prec_reduce(float *const output, int num_output); + +#ifdef __cplusplus +} // extern "C" +#endif + +#endif // AOM_AV1_ENCODER_ML_H_ |