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#pragma once
#include <neuralnet/types.h>
typedef struct nnMatrix nnMatrix;
typedef struct nnNeuralNetwork nnNeuralNetwork;
typedef struct nnQueryObject nnQueryObject;
/// Neuron activation.
typedef enum nnActivation {
nnIdentity,
nnSigmoid,
nnRelu,
} nnActivation;
/// Create a network.
nnNeuralNetwork* nnMakeNet(
int num_layers, const int* layer_sizes, const nnActivation* activations);
/// Delete the network and free its internal memory.
void nnDeleteNet(nnNeuralNetwork**);
/// Set the network's weights.
void nnSetWeights(nnNeuralNetwork*, const R* weights);
/// Set the network's biases.
void nnSetBiases(nnNeuralNetwork*, const R* biases);
/// Query the network.
///
/// |input| is a matrix of inputs, one row per input and as many columns as the
/// input's dimension.
///
/// The query object's output matrix (see nnQueryOutputs()) is a matrix of
/// outputs, one row per output and as many columns as the output's dimension.
void nnQuery(const nnNeuralNetwork*, nnQueryObject*, const nnMatrix* input);
/// Query the network, array version.
void nnQueryArray(
const nnNeuralNetwork*, nnQueryObject*, const R* input, R* output);
/// Create a query object.
///
/// The query object holds all the internal memory required to query a network.
/// Query objects allocate all memory up front so that network queries can run
/// without additional memory allocation.
nnQueryObject* nnMakeQueryObject(const nnNeuralNetwork*, int num_inputs);
/// Delete the query object and free its internal memory.
void nnDeleteQueryObject(nnQueryObject**);
/// Return the outputs of the query.
const nnMatrix* nnNetOutputs(const nnQueryObject*);
/// Return the network's input size.
int nnNetInputSize(const nnNeuralNetwork*);
/// Return the network's output size.
int nnNetOutputSize(const nnNeuralNetwork*);
/// Return the layer's input size.
int nnLayerInputSize(const nnMatrix* weights);
/// Return the layer's output size.
int nnLayerOutputSize(const nnMatrix* weights);
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