training_error = []
test_error = []
hits_perc = []
for T in np.arange(DT, Tmax + 1, DT):
print 'T =', T
t0 = time.time()
[[w01, w12, w23], [a01, a12, a23],
[th1, th2, th3]] = bp.set_rand_omega(N)
fonts = np.random.choice(range(700), T, replace=False)
tr_err, ts_err, hits = bp.back_prop(
N, [[w01, w12, w23], [a01, a12, a23], [th1, th2, th3]],
fonts,
max_iterations=max_iterations,
n_fonts_error=n_fonts_error,
calculate_error=True,
calculate_train_error=True)[1][:3]
#[[w01,w12,w23],[a01,a12,a23],[th1,th2,th3]] = bp.back_prop(
#N,[[w01,w12,w23],[a01,a12,a23],[th1,th2,th3]],fonts,max_iterations=max_iterations,n_fonts_error=n_fonts_error)[0]
#tr_err = bp.evaluate(N,[[w01,w12,w23],[a01,a12,a23],[th1,th2,th3]],fonts,printerror=False)[0]
#ts_err, hits = bp.evaluate(N,[[w01,w12,w23],[a01,a12,a23],[th1,th2,th3]],np.arange(700,1000,1),printerror=False)[:2]
training_error += [tr_err]
test_error += [ts_err]
hits_perc += [(1. * np.array(hits) / 30).tolist()]
print time.time() - t0, 's'
dim=28 N = [28*28,16,16,10] max_iterations = 700*10*10 lyapunov = [] n=0 while True: W = np.array(bp.set_rand_omega(N)) W_ = W + np.array([ 2e-10*(np.array([np.random.random((N[1],N[0])),np.random.random((N[2],N[1])),np.random.random((N[3],N[2]))])-0.5), 0*W[1], 2e-10*(np.array([np.random.random(N[1]),np.random.random(N[2]),np.random.random(N[3])])-0.5) ]) Wt = bp.back_prop(N, W, range(700),max_iterations=max_iterations)[0] W_t = bp.back_prop(N, W_, range(700),max_iterations=max_iterations)[0] num = 0 den = 0 for i in range(3): for j in range(3): num += ((Wt[i][j]-W_t[i][j])**2).sum() den += ((W[i][j]-W_[i][j])**2).sum() num = np.sqrt(num) den = np.sqrt(den) lyapunov += [(700.*10/max_iterations)*np.log(num/den)] n+=1 #print lyapunov
hits_perc = []
error_prediction = []
err_pred = []
print 'T =', 0
t0 = time.time()
[[w01, w12, w23], [a01, a12, a23], [th1, th2, th3]] = bp.set_rand_omega(N)
fonts = []
font_extra = np.random.choice([k for k in range(700) if not k in fonts],
1)[0]
err_pred += [
bp.back_prop(N, [[w01, w12, w23], [a01, a12, a23], [th1, th2, th3]],
fonts,
f_extra=font_extra,
max_iterations=max_iterations,
n_fonts_error=n_fonts_error)[1][4]
]
print time.time() - t0, 's'
for T in np.arange(1, Tmax + 1, 1):
print 'T =', T
t0 = time.time()
[[w01, w12, w23], [a01, a12, a23], [th1, th2,
th3]] = bp.set_rand_omega(N)
if (T + 1) % DT == 0:
fonts += [font_extra]