else:
status[key] = value
with open(ae.model_dir + "status.json", 'w') as f:
f.write(json.dumps(status, indent=2, sort_keys=True))
if __name__ == '__main__':
### SETUP ###
if not cross_validate:
l = LogSourceMaker(logfolder="/root/MatchBrain/logs/")
b = l.get_block(shift = shift)
bws = b.sources[0]
phs = b.sources[1]
prep = Preprocessing(bws)
print("prep output dim: "+str(prep.output_dim))
AutoTransformer.model_dir = "/root/MatchBrain/models/"
ae = AutoTransformer(prep.output_dim, prep, phs, epochs=epochs, num_sizes=5)
print("have ae")
### DATA ###
if generate_data:
update_status(ae, "current", "preprocessing data")
b.start()
while b.started and data_mins>0:
time.sleep(60)
print(ae.batched)
data_mins -= 1
if b.started:
b.stop()
print("stopped")
ae.cap_data()
update_status(ae, "current", "saving data")
ae.save_data()
status.setdefault("history", []).insert(0, value)
else:
status[key] = value
with open(ae.model_dir + "status.json", 'w') as f:
f.write(json.dumps(status, indent=2, sort_keys=True))
if __name__ == '__main__':
### SETUP ###
nsm = NormSourceMaker(datafolder="/home/joren/PycharmProjects/MatchBrain/ml/"
,phases=phase_names
,cross_val=True)
AutoTransformer.model_dir = "/home/joren/PycharmProjects/MatchBrain/models/"
for _ in xrange(len(nsm.cross_val_keys)):
blk = nsm.get_block()
#TODO get this size from somewhere better. Is it even correct?
ae = AutoTransformer(100, blk.sinks[0], blk.sinks[1], epochs=epochs, num_sizes=5) #TODO get this 100 from somewhere reliable
print("have ae")
blk.start()
while blk.started and data_mins>0:
time.sleep(60)
print(ae.batched)
data_mins -= 1
if blk.started:
blk.stop()
print("stopped")
ae.cap_data()
print("capped")
### PRETRAIN ###
losscomb = lambda zoo, h: ", ".join(map(lambda (i,e): str(i)+":"+('%.4f'%e[-1][zoo]), enumerate(h)))
n = nest(1,0.9)
counter = 0
with open(ae.model_dir + "status.json", 'w') as f:
f.write(json.dumps(status, indent=2, sort_keys=True))
if __name__ == '__main__':
### SETUP ###
nsm = NormSourceMaker(
datafolder="/home/joren/PycharmProjects/MatchBrain/ml/",
phases=phase_names,
cross_val=True)
AutoTransformer.model_dir = "/home/joren/PycharmProjects/MatchBrain/models/"
for _ in xrange(len(nsm.cross_val_keys)):
blk = nsm.get_block()
#TODO get this size from somewhere better. Is it even correct?
ae = AutoTransformer(
100, blk.sinks[0], blk.sinks[1], epochs=epochs,
num_sizes=5) #TODO get this 100 from somewhere reliable
print("have ae")
blk.start()
while blk.started and data_mins > 0:
time.sleep(60)
print(ae.batched)
data_mins -= 1
if blk.started:
blk.stop()
print("stopped")
ae.cap_data()
print("capped")
### PRETRAIN ###
losscomb = lambda zoo, h: ", ".join(
map(lambda (i, e): str(i) + ":" +
