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)
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