def trainTimed(self, epochs, ds):
start = time.clock()
self.rdm.train(ds.rhythmTimesteps)
rdm = time.clock()
print('RDM: {}'.format(rdm-start))
mel.trainNetwork(self.net, ds.melodyDS, epochs)
net = time.clock()
print('Net: {}'.format(net-rdm))
bestHMM = self.hmm
bestScore = -np.inf
bestI = -1
for i in range(10):
nextHMM = deepcopy(self.hmm)
nextHMM.fit(ds.rhythmSamps, ds.rhythmLens)
nextScore = nextHMM.score(ds.rhythmSamps, ds.rhythmLens)
# print('Score {}: {}'.format(i,nextScore))
if nextScore > bestScore:
bestHMM = nextHMM
bestScore = nextScore
bestI = i
self.hmm = bestHMM
hmm = time.clock()
print('RDM: {}'.format(rdm-start))
print('Net: {}'.format(net-rdm))
print('HMM: {}'.format(hmm-net))
print('Total: {}'.format(hmm-start))
def train(self, epochs, tracks):
trackDS = TrackDataSet(tracks)
mel.trainNetwork(self.net, trackDS.melodyDS, epochs)
bestHMM = self.hmm
bestScore = 0
for i in range(20):
nextHMM = deepcopy(self.hmm)
nextHMM.fit(trackDS.rhythmSamps, trackDS.rhythmLens)
nextScore = nextHMM.score(trackDS.rhythmSamps, trackDS.rhythmLens)
if nextScore > bestScore:
bestHMM = nextHMM
bestScore = nextScore
self.rdm.train(trackDS.rhythmTimesteps)
self.hmm = bestHMM
