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#pragma once
#include <neuralnet/matrix.h>
#include <neuralnet/types.h>
typedef struct nnNeuralNetwork nnNeuralNetwork;
typedef struct nnQueryObject nnQueryObject;
/// Linear layer parameters.
///
/// Either one of the following must be set:
/// a) Training: input and output sizes.
/// b) Inference: weights + biases.
typedef struct nnLinearParams {
int input_size;
int output_size;
nnMatrix weights;
nnMatrix biases;
} nnLinearParams;
/// Layer type.
typedef enum nnLayerType {
nnLinear,
nnSigmoid,
nnRelu,
} nnLayerType;
/// Neural network layer.
typedef struct nnLayer {
nnLayerType type;
union {
nnLinearParams linear;
};
} nnLayer;
/// Create a network.
nnNeuralNetwork* nnMakeNet(
const nnLayer* layers, int num_layers, int input_size);
/// Delete the network and free its internal memory.
void nnDeleteNet(nnNeuralNetwork**);
/// 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
/// with batches of the given size. Memory is allocated up front so that network
/// queries can run without additional memory allocation.
nnQueryObject* nnMakeQueryObject(const nnNeuralNetwork*, int batch_size);
/// 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 nnNeuralNetwork*, int layer);
/// Return the layer's output size.
int nnLayerOutputSize(const nnNeuralNetwork*, int layer);
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