def validate():
acc = []
for (i, (x, y)) in enumerate(examples.get_validation_example()):
if HYPERPARAMETERS["locally normalize"]:
targety = N.array([y])
else:
targety = N.zeros(ODIM)
targety[y] = 1.
if HLAYERS == 2:
o = graph.validatefn([x.data], targety, w1[x.indices], b1, wh, bh, w2, b2)
(kl, softmax, argmax, prehidden1, prehidden2) = o
else:
o = graph.validatefn([x.data], targety, w1[x.indices], b1, w2, b2)
(kl, softmax, argmax, prehidden) = o
if argmax == y: acc.append(1.)
else: acc.append(0.)
if i < 5:
if HLAYERS == 2:
abs_prehidden(prehidden1, "Prehidden1")
abs_prehidden(prehidden2, "Prehidden2")
else:
abs_prehidden(prehidden)
return N.mean(acc), N.std(acc)
def validate():
acc = []
for (i, (x, y)) in enumerate(examples.get_validation_example()):
if HLAYERS == 2:
o = graph.validatefn(x, N.array([y]), w1, b1, wh, bh, w2, b2)
(kl, softmax, argmax, prehidden1, prehidden2) = o
else:
o = graph.validatefn(x, N.array([y]), w1, b1, w2, b2)
(kl, softmax, argmax, prehidden) = o
if argmax == y: acc.append(1.)
else: acc.append(0.)
if i < 5:
if HLAYERS == 2:
abs_prehidden(prehidden1, "Prehidden1")
abs_prehidden(prehidden2, "Prehidden2")
else:
abs_prehidden(prehidden)
return N.mean(acc), N.std(acc)
def validate():
acc = []
for (i, (x, y)) in enumerate(examples.get_validation_example()):
if HLAYERS == 2:
o = graph.validatefn(x, N.array([y]), w1, b1, wh, bh, w2, b2)
(kl, softmax, argmax, prehidden1, prehidden2) = o
else:
o = graph.validatefn(x, N.array([y]), w1, b1, w2, b2)
(kl, softmax, argmax, prehidden) = o
if argmax == y: acc.append(1.)
else: acc.append(0.)
if i < 5:
if HLAYERS == 2:
abs_prehidden(prehidden1, "Prehidden1")
abs_prehidden(prehidden2, "Prehidden2")
else:
abs_prehidden(prehidden)
return N.mean(acc), N.std(acc)
import examples, sys
import graph
import numpy as N
from vocabulary import labelmap
ODIM = labelmap.len
from common.mydict import sort as dictsort
for l in sys.stdin:
e = examples._example_from_string(l)
(x, y) = e
if HYPERPARAMETERS["locally normalize"]:
targety = N.array([y])
else:
targety = N.zeros(ODIM)
targety[y] = 1.
if HLAYERS == 2:
o = graph.validatefn([x.data], targety, w1[x.indices], b1, wh, bh,
w2, b2)
(kl, softmax, argmax, prehidden1, prehidden2) = o
else:
o = graph.validatefn([x.data], targety, w1[x.indices], b1, w2, b2)
(kl, softmax, argmax, prehidden) = o
assert softmax.shape[0] == 1
softmax = softmax[0]
prs = {}
for i in range(softmax.shape[0]):
prs[labelmap.str(i)] = softmax[i]
print dictsort(prs)[:3]
# print argmax, softmax
