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#ifndef pAHg29dA1QrONep0XYIUhA0GC08
#define pAHg29dA1QrONep0XYIUhA0GC08
#include <iostream>
#include "trainer.hpp"
#include "model.hpp"
#include "index.hpp"
#include "index_global.hpp"
#include "index_randomspike.hpp"
#include "index_spike.hpp"
#include "index_spike_arrival.hpp"
namespace TrainerImpl {
namespace MC = ModelConsts;
const Time::type delays[6] =
{ Time::epsilon()(),
MC::TrainerInputWindow + MC::TrainerReadoutDelay,
MC::TrainerReadoutWindow,
Time::epsilon()(),
Time::epsilon()(),
MC::TrainerInterTrialDelay };
const Time::type randDelays[6] =
{ 0,
MC::TrainerReadoutRandDelay,
0, 0, 0,
MC::TrainerInterTrialRandDelay };
TrainerT::TrainerT(RNG::seed_t seed) :
rng(seed),
delay(delays[0]),
reward(0),
performance(1.0 / MC::TrainerNumSymbols),
generation(0),
input(0), output(2),
state(0),
resetCounter(1) {}
template <typename PC, typename MI, typename MQ>
struct Update {
static TrainerT eval(const TrainerT &old, PC &pc,
MI &indices, MQ &queues, Time t) {
TrainerT res = old;
res.generation++;
res.state++;
res.reward = 0;
auto sendSpikes = [&](int mult, double window, int fanIn, double freq) -> void {
Time ct = t + Time::epsilon();
while (ct < t + window) {
// determine dst
Ptr<Neuron> dst{uint16_t(RNG::integer(res.rng, fanIn)
* mult
% MC::NumExcitatory)};
Ptr<Neuron> src(dst() + ((Ptr<Neuron>::ptr_t) maxNeurons/2));
Ptr<RandomSpike> ptrNE(indices.template get<Index<RandomSpike>>().add(t, ct, src));
queues.insert(t, ct, Event<RandomSpike>(ct, src, ptrNE));
res.rng = RNG::next(res.rng);
// determine next spike
ct += RNG::expo(res.rng, 1.0 / freq / fanIn);
res.rng = RNG::next(res.rng);
}
};
switch (res.state) {
case 1: // pre: let the network settle
case 7: { // pre: give last reward
// select and give input
res.input = RNG::integer(res.rng, MC::TrainerNumSymbols);
res.rng = RNG::next(res.rng);
res.state = 1;
const int mult_in[10] = // some arbitrarily selected prime number except for
{1, 997, 1013, 1021, 1033, 1049, 1061, 1069, 1091, 1097}; // symbol one
BOOST_STATIC_ASSERT((MC::TrainerNumSymbols <= 10));
std::cerr << "INPUT " << t << std::endl;
sendSpikes(mult_in[res.input],
MC::TrainerInputWindow, MC::FanIn, MC::TrainerInputFreq);
} break;
case 2:
res.resetCounter = 0;
break;
case 4: case 6: // wait
break;
case 3: {
// send readout signal
std::cerr << "READOUT SIGNAL " << t << std::endl;
if (MC::TrainerReadoutFreq > 0)
sendSpikes(967, // arbitrary prime
MC::TrainerReadoutWindow, MC::FanIn, MC::TrainerReadoutFreq);
} break;
case 5: {
// evaluate which symbol won, reward (TODO), wait for a longer time
const int mult_out[10] = // some arbitrarily selected prime number except for
{1, 937, 919, 907, 883, 877, 859, 853, 829, 823}; // symbol one
BOOST_STATIC_ASSERT((MC::TrainerNumSymbols <= 10));
uint32_t freq[MC::TrainerNumSymbols + 1] = {};
uint8_t maxIdx = MC::TrainerNumSymbols,
sndIdx = MC::TrainerNumSymbols;
uint16_t overlap = uint16_t(MC::FanIn / MC::NumExcitatory * MC::FanOut);
std::cerr << "READOUT";
for (int o=0; o<MC::TrainerNumSymbols; o++) {
for (Ptr<Neuron>::ptr_t i = MC::FanIn - overlap;
i < MC::FanIn + MC::FanIn;
i++) {
Ptr<Neuron> src(uint16_t(mult_out[o] * i % MC::NumExcitatory));
PLA_Get<SpikeCounter, ContinuousContext<Neuron> >
pla_get(t, ContinuousContext<Neuron>(src));
freq[o] += pc.call(pla_get);
}
if (freq[o] > freq[maxIdx]) {
sndIdx = maxIdx;
maxIdx = o;
}else if (freq[o] > freq[sndIdx]) {
sndIdx = o;
}
std::cerr << " " << freq[o];
}
bool correct = maxIdx == res.input;
res.output = maxIdx;
res.reward = (correct ? MC::TrainerReward : (-MC::TrainerPunish))
* ((1.0 + MC::TrainerWinAdv) * freq[sndIdx] < freq[maxIdx]);
res.performance *= 0.9;
res.performance += correct * 0.1;
res.resetCounter = 1;
std::cerr << "\nWINNER @ " << t << " = " << uint16_t(maxIdx)
<< " correct = " << uint16_t(res.input)
<< " reward = " << res.reward
<< "\n";
} break;
default:
assert(false);
}
res.delay = delays[res.state]
+ randDelays[res.state] * RNG::equi(res.rng);
res.rng = RNG::next(res.rng);
return res;
}
};
/// dummy for sim_replay, must not be called
template <typename PC>
struct Update<PC, Void, Void> {
static TrainerT eval(const TrainerT&, PC &, Void&, Void&, Time) DO_NOT_CALL;
};
} // NS
#endif // pAHg29dA1QrONep0XYIUhA0GC08
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