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diff --git a/third_party/aom/av1/encoder/ml.h b/third_party/aom/av1/encoder/ml.h
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+/*
+ * 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_