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#include "spires_interface.h"
#include <spires.h>
#include <math.h>
#include <stddef.h>
#include <stdint.h>
#include <stdio.h>
#include <stdlib.h>
int collect_reservoir_states(spires_reservoir *reservoir,
const double *input_series, size_t series_length,
Reservoir_State_Matrix *result)
{
// error checking
// RIP
// clear the result first
result->num_samples = 0;
result->num_features = 0;
result->states = NULL;
const size_t num_inputs = spires_num_inputs(reservoir);
const size_t num_neurons = spires_num_neurons(reservoir);
if (series_length > SIZE_MAX / num_neurons ||
series_length * num_neurons > SIZE_MAX / sizeof(double)) {
fprintf(stderr, "matrix size overloaded!!");
return -1;
}
double *states = malloc(num_neurons * series_length * sizeof(*states));
if (!states) {
fprintf(stderr, "failed to allocate memory for states");
return -1;
}
spires_status status = spires_reservoir_reset(reservoir);
if (status != SPIRES_OK) {
fprintf(stderr, "reservoir reset error");
free(states);
return -1;
}
// build state_matrix
for (size_t i = 0; i < series_length; i++) {
const double *current_input = &input_series[i * num_inputs];
status = spires_step(reservoir, current_input);
if (status != SPIRES_OK) {
free(states);
return -1;
}
double *current_state = &states[i * num_neurons];
status = spires_read_reservoir_state(reservoir, current_state);
if (status != SPIRES_OK) {
free(states);
return -1;
}
}
result->num_samples = series_length;
result->num_features = num_neurons;
result->states = states;
return 0;
}
int convert_weights_to_resistances(const spires_reservoir *reservoir,
size_t num_neurons, size_t num_outputs,
double r_on, double r_off,
double **resistances_out,
conductance_mapping *mapping)
{
double max_abs_weight = 0.0;
*resistances_out = NULL;
size_t weight_count = num_neurons * num_outputs;
size_t num_physical_columns = num_outputs * 2;
double *readout = malloc(num_neurons * num_outputs * sizeof(double));
spires_read_readout(reservoir, readout);
double *resistances =
malloc(num_neurons * num_physical_columns * sizeof(double));
if (resistances == NULL) {
fprintf(stderr, "Failed to allocated crossbar resistances");
free(readout);
return -1;
}
// get the max weight
for (size_t i = 0; i < weight_count; i++) {
if (!isfinite(readout[i])) {
fprintf(stderr,
"invalid readout weight at index %zu: %g\n", i,
readout[i]);
free(readout);
free(resistances);
return -1;
}
double abs_weight = fabs(readout[i]);
if (abs_weight > max_abs_weight) {
max_abs_weight = abs_weight;
}
}
printf("max absolute weight = %.12e\n", max_abs_weight);
mapping->g_min = 1.0 / r_off;
mapping->g_max = 1.0 / r_on;
mapping->max_abs_weight = max_abs_weight;
// calculate the alpha scaling parameter to normalize the weights
mapping->alpha = (mapping->g_max - mapping->g_min) / max_abs_weight;
// differential pair mapping
for (size_t neuron = 0; neuron < num_neurons; neuron++) {
for (size_t output = 0; output < num_outputs; output++) {
size_t weight_index = output * num_neurons + neuron;
size_t positive_column = 2 * output;
size_t negative_column = positive_column + 1;
double positive_conductance;
double negative_conductance;
size_t positive_index =
neuron * num_physical_columns + positive_column;
size_t negative_index =
neuron * num_physical_columns + negative_column;
double weight = readout[weight_index];
if (weight >= 0.0) {
positive_conductance =
mapping->g_min + mapping->alpha * weight;
negative_conductance = mapping->g_min;
}
if (weight < 0.0) {
positive_conductance = mapping->g_min;
negative_conductance =
mapping->g_min + mapping->alpha * (-weight);
}
resistances[positive_index] =
1.0 / positive_conductance;
resistances[negative_index] =
1.0 / negative_conductance;
}
}
printf("max absolute weight = %.12e\n", mapping->max_abs_weight);
printf("alpha = %.12e\n", mapping->alpha);
printf("physical crossbar dimensions: %zu x %zu\n", num_neurons,
num_physical_columns);
*resistances_out = resistances;
free(readout);
return 0;
}
int train_reservoir(spires_reservoir *reservoir, double *input_series,
double *target_series, size_t series_length, double lambda)
{
spires_status status =
spires_train_ridge(reservoir, (double *)input_series,
(double *)target_series, series_length, lambda);
if (status != SPIRES_OK) {
fprintf(stderr, "Spires ridge training failed");
return -1;
}
return 0;
}
void free_reservoir_state_matrix(Reservoir_State_Matrix *matrix)
{
if (!matrix) {
return;
}
free(matrix->states);
matrix->states = NULL;
matrix->num_samples = 0;
matrix->num_features = 0;
}
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