def build_v1_cortex():
strengths = 1.0 #0.526315789473684
v1_strength = strengths * 0.5 #1.0/3.0
v1_inhib = False
print "strengths:%.5f" % strengths
print "v1_strength:%.5f" % v1_strength
print "v1_inhib:", v1_inhib
print "--- Building Visual Cortex ---"
c.start_timer()
# retina.shape = (12,12)x
# v1.shape = (14,14)x
retina = RetinalLayer(12, 12, 'Retina') #emerg: 12x12
v1 = c.Layer(14, 14, 'V1') #,k=0.3) #emerg: 14x14
c.print_timer("made layers")
ret_v1_p = RetinaV1PositiveConnection(retina,
v1, (12, 12),
strength=strengths)
ret_v1_n = RetinaV1NegativeConnection(retina,
v1, (12, 12),
strength=strengths)
v1_v1 = c.FixedMountainConnection(v1,
v1, (11, 11),
inhib=v1_inhib,
strength=v1_strength) #emerg: 11x11
c.print_timer("made connections")
network = c.Cortex([retina, v1], [ret_v1_p, ret_v1_n, v1_v1],
'Visual Cortex')
network.print_structure()
network.load_data('../data/v1 tests/weights/')
return network
def build_visual_cortex():
strengths = 1.0
v1_strength = strengths*0.5
v1_inhib = False
print "strengths:%.5f"%strengths
print "v1_strength:%.5f"%v1_strength
print "v1_inhib:",v1_inhib
print "--- Building Visual Cortex ---"
c.start_timer()
# retina.shape = (12,12)x
# v1.shape = (14,14)x
retina = RetinalLayer(36,36,'Retina') #emerg: 12x12
v1 = c.Layer(168,168,'V1')#emerg: 14x14
v4 = c.Layer(24,24,'V4')
it = c.OutputLayer(10,10,'IT')
c.print_timer("made layers")
ret_v1_p = RetinaV1PositiveConnection(retina,v1,(12,12),strength=strengths,fixed=True)
ret_v1_n = RetinaV1NegativeConnection(retina,v1,(12,12),strength=strengths,fixed=True)
v1_v1 = c.FixedMountainConnection(v1,v1,(7,7),inhib=v1_inhib,strength=v1_strength) #emerg: 11x11
v1_v4 = c.Connection(v1,v4,(12,12))
v4_it = c.Connection(v4,it,None)
it_v4 = c.Connection(it,v4,None)
c.print_timer("made connections")
network = c.Cortex([retina,v1,v4,it],[ret_v1_p,ret_v1_n,v1_v4,v4_it,it_v4],'Visual Cortex')
network.print_structure()
network.load_data()
return network
def retina_test():
network = build_v1_cortex()
ret = network.get_layer('Retina')
c.print_timer("built layer")
start_time = time.time()
ret_v1_p = network.get_connection('Retina_V1_p')
ret_v1_n = network.get_connection('Retina_V1_n')
v1 = network.get_layer('v1')
c.print_stats('pos wt', ret_v1_p.weights)
c.print_stats('neg wt', ret_v1_n.weights)
base_path = '../kyo/'
for i in range(400): # go for 129
if i % 10 == 0:
val = i
ret_v1_p.save_image_rel(
'../data/v1 tests/ret_v1_' + str(val) + '.png', ret_v1_n)
ret_v1_p.save_as_image('../data/v1 tests/ret_v1_p_' + str(val) +
'.png')
ret_v1_n.save_as_image('../data/v1 tests/ret_v1_n_' + str(val) +
'.png')
v1.save_image_for_activations('../data/v1 tests/v1_' + str(val) +
'.png')
network.print_conn_wt_stats()
pass_time = time.time()
listing = os.listdir(base_path)
cycles = []
total_wt_change = 0
for idx, path in enumerate(listing):
ret.load_image(base_path + path, random=True, detailed=False)
cycle_cnt, wt_change = network.settle()
total_wt_change += wt_change
cycles.append(cycle_cnt)
if i % 50 == 0:
network.save_data('../data/v1 tests/weights/')
print '-- Pass %d: %.3fsec (%.2f cycles each for %d imgs)' % (
i, time.time() - pass_time, float(sum(cycles)) / len(cycles),
len(listing))
print '-- Total elapsed time:%.3fsec' % (time.time() - start_time)
ret_v1_p.save_image_rel('../data/v1 tests/post_ret_v1.png', ret_v1_n)
c.print_stats('pos wt', ret_v1_p.weights)
c.print_stats('neg wt', ret_v1_n.weights)
def build_visual_cortex():
strengths = 1.0
v1_strength = strengths * 0.5
v1_inhib = False
print "strengths:%.5f" % strengths
print "v1_strength:%.5f" % v1_strength
print "v1_inhib:", v1_inhib
print "--- Building Visual Cortex ---"
c.start_timer()
# retina.shape = (12,12)x
# v1.shape = (14,14)x
retina = RetinalLayer(36, 36, 'Retina') #emerg: 12x12
v1 = c.Layer(168, 168, 'V1') #emerg: 14x14
v4 = c.Layer(24, 24, 'V4')
it = c.OutputLayer(10, 10, 'IT')
c.print_timer("made layers")
ret_v1_p = RetinaV1PositiveConnection(retina,
v1, (12, 12),
strength=strengths,
fixed=True)
ret_v1_n = RetinaV1NegativeConnection(retina,
v1, (12, 12),
strength=strengths,
fixed=True)
v1_v1 = c.FixedMountainConnection(v1,
v1, (7, 7),
inhib=v1_inhib,
strength=v1_strength) #emerg: 11x11
v1_v4 = c.Connection(v1, v4, (12, 12))
v4_it = c.Connection(v4, it, None)
it_v4 = c.Connection(it, v4, None)
c.print_timer("made connections")
network = c.Cortex([retina, v1, v4, it],
[ret_v1_p, ret_v1_n, v1_v4, v4_it, it_v4],
'Visual Cortex')
network.print_structure()
network.load_data()
return network
def retina_test():
network = build_v1_cortex()
ret = network.get_layer('Retina')
c.print_timer("built layer")
start_time = time.time()
ret_v1_p = network.get_connection('Retina_V1_p')
ret_v1_n = network.get_connection('Retina_V1_n')
v1 = network.get_layer('v1')
c.print_stats('pos wt',ret_v1_p.weights)
c.print_stats('neg wt',ret_v1_n.weights)
base_path = '../kyo/'
for i in range(400): # go for 129
if i%10 == 0:
val = i
ret_v1_p.save_image_rel('../data/v1 tests/ret_v1_'+str(val)+'.png',ret_v1_n)
ret_v1_p.save_as_image('../data/v1 tests/ret_v1_p_'+str(val)+'.png')
ret_v1_n.save_as_image('../data/v1 tests/ret_v1_n_'+str(val)+'.png')
v1.save_image_for_activations('../data/v1 tests/v1_'+str(val)+'.png')
network.print_conn_wt_stats()
pass_time = time.time()
listing = os.listdir(base_path)
cycles = []
total_wt_change = 0
for idx,path in enumerate(listing):
ret.load_image(base_path + path,random=True,detailed=False)
cycle_cnt,wt_change = network.settle()
total_wt_change += wt_change
cycles.append(cycle_cnt)
if i%50 == 0:
network.save_data('../data/v1 tests/weights/')
print '-- Pass %d: %.3fsec (%.2f cycles each for %d imgs)'%(i,time.time()-pass_time,float(sum(cycles))/len(cycles),len(listing))
print '-- Total elapsed time:%.3fsec'%(time.time() - start_time)
ret_v1_p.save_image_rel('../data/v1 tests/post_ret_v1.png',ret_v1_n)
c.print_stats('pos wt',ret_v1_p.weights)
c.print_stats('neg wt',ret_v1_n.weights)
def build_v1_cortex():
strengths = 1.0#0.526315789473684
v1_strength = strengths*0.5#1.0/3.0
v1_inhib = False
print "strengths:%.5f"%strengths
print "v1_strength:%.5f"%v1_strength
print "v1_inhib:",v1_inhib
print "--- Building Visual Cortex ---"
c.start_timer()
# retina.shape = (12,12)x
# v1.shape = (14,14)x
retina = RetinalLayer(12,12,'Retina') #emerg: 12x12
v1 = c.Layer(14,14,'V1')#,k=0.3) #emerg: 14x14
c.print_timer("made layers")
ret_v1_p = RetinaV1PositiveConnection(retina,v1,(12,12),strength=strengths)
ret_v1_n = RetinaV1NegativeConnection(retina,v1,(12,12),strength=strengths)
v1_v1 = c.FixedMountainConnection(v1,v1,(11,11),inhib=v1_inhib,strength=v1_strength) #emerg: 11x11
c.print_timer("made connections")
network = c.Cortex([retina,v1],[ret_v1_p,ret_v1_n,v1_v1],'Visual Cortex')
network.print_structure()
network.load_data('../data/v1 tests/weights/')
return network
