def go(kargs, type):
"""
Execute SP.
@param kargs: The params for the SP.
@param type: Run type.
@return: The new sp and the execution time.
"""
# Run the SP
t = time.time()
for _ in xrange(n_iters):
sp = SPRegion(**kargs)
sp.c_sboost = 0 # Ensure that no permanence boosting occurs
sp.execute(ds, store=False)
t = time.time() - t
# Dump the permanence matrix
with open(os.path.join(p, '{0}-permanence.pkl'.format(type)), 'wb') \
as f:
cPickle.dump(sp.p, f, cPickle.HIGHEST_PROTOCOL)
# Dump the details
kargs['density'] = density
kargs['seed'] = seed
kargs['time'] = t
with open(os.path.join(p, '{0}-details.json'.format(type)), 'wb') as f:
f.write(json.dumps(kargs, sort_keys=True, indent=4,
separators=(',', ': ')))
return sp, t
def main(ds,
p,
ncols=2048,
duty_cycle=100,
nepochs=10,
global_inhibition=True,
seed=123456789):
"""Run an experiment.
@param ds: The dataset.
@param p: The full path to the directory to save the results.
@param ncols: The number of columns.
@param duty_cycle: The duty cycle.
@param nepochs: The number of epochs
@param global_inhibition: If True use global inhibition otherwise use local
inhibition.
@param seed: The random seed.
"""
# Get some parameters
ninputs = ds.shape[1]
density = np.sum(ds[0]) / float(ninputs)
# Make the directory if it doesn't exist
try:
os.makedirs(p)
except OSError:
pass
# Initializations
np.random.seed(seed)
kargs = {
'ninputs': ninputs,
'ncolumns': ncols,
'nsynapses': 40,
'random_permanence': True,
'pinc': 0.03,
'pdec': 0.05,
'seg_th': 15,
'nactive': int(0.02 * ncols),
'duty_cycle': duty_cycle,
'max_boost': 10,
'global_inhibition': global_inhibition,
'trim': 1e-4
}
# Create the region
delattr(SPRegion, '_phase3')
setattr(SPRegion, '_phase3', _phase3)
sp = SPRegion(**kargs)
sp.iter, sp.out_path = 1, p
# Train the region
t = time.time()
for i in range(nepochs):
for j, x in enumerate(ds):
sp.execute(x)
sp.iter += 1
t = time.time() - t
# Dump the details
kargs['density'] = density
kargs['seed'] = seed
kargs['nepochs'] = nepochs
kargs['time'] = t
with open(os.path.join(p, 'details.json'), 'w') as f:
f.write(
json.dumps(kargs, sort_keys=True, indent=4,
separators=(',', ': ')))
def main(ds, p, ncols=2048, duty_cycle=100, nepochs=10, global_inhibition=True,
seed=123456789):
"""
Run an experiment.
@param ds: The dataset.
@param p: The full path to the directory to save the results.
@param ncols: The number of columns.
@param duty_cycle: The duty cycle.
@param nepochs: The number of epochs
@param global_inhibition: If True use global inhibition otherwise use local
inhibition.
@param seed: The random seed.
"""
# Get some parameters
ninputs = ds.shape[1]
density = np.sum(ds[0]) / float(ninputs)
# Make the directory if it doesn't exist
try:
os.makedirs(p)
except OSError:
pass
# Initializations
np.random.seed(seed)
kargs = {
'ninputs': ninputs,
'ncolumns': ncols,
'nsynapses': 40,
'random_permanence': True,
'pinc':0.03, 'pdec':0.05,
'seg_th': 15,
'nactive': int(0.02 * ncols),
'duty_cycle': duty_cycle,
'max_boost': 10,
'global_inhibition': global_inhibition,
'trim': 1e-4
}
# Create the region
delattr(SPRegion, '_phase3')
setattr(SPRegion, '_phase3', _phase3)
sp = SPRegion(**kargs)
sp.iter, sp.out_path = 1, p
# Train the region
t = time.time()
for i in xrange(nepochs):
for j, x in enumerate(ds):
sp.execute(x)
sp.iter += 1
t = time.time() - t
# Dump the details
kargs['density'] = density
kargs['seed'] = seed
kargs['nepochs'] = nepochs
kargs['time'] = t
with open(os.path.join(p, 'details.json'), 'wb') as f:
f.write(json.dumps(kargs, sort_keys=True, indent=4,
separators=(',', ': ')))
