用python修改以下代码使其能正确运行：# 定义维特比算法 def viterbi(obs, states, start_p, trans_p, emit_p): V = [{}] path = {} for y in states: V[0][y] = start_p[y] * emit_p[y].get(obs[0], 0) path[y] = [y] for t in range(1, len(obs)): V.append({}) newpath = {} for y in states: (prob, state) = max([(V[t-1][y0] * trans_p[y0].get(y, 0) * emit_p[y].get(obs[t], 0), y0) for y0 in states if V[t-1][y0] > 0]) V[t][y] = prob newpath[y] = path[state] + [y] path = newpath (prob, state) = max([(V[len(obs)-1][y], y) for y in states]) return prob, path[state] # 对测试集进行词性标注并计算准确率 total_count = 0 correct_count = 0 for word, pos in test_words: if word in word_pos_prob.get(pos, {}): obs = [word] states = list(pos_count.keys()) start_p = pos_init_prob trans_p = pos_trans_prob emit_p = word_pos_prob[pos] prob, path = viterbi(obs, states, start_p, trans_p, emit_p) if path[pos][0] == pos: correct_count += 1 total_count += 1 accuracy = correct_count / total_count print('Accuracy: {}'.format(accuracy))

# 定义维特比算法
def viterbi(obs, states, start_p, trans_p, emit_p):
V = [{}]
path = {}
for y in states:
V[0][y] = start_p[y] * emit_p[y].get(obs[0], 0)
path[y] = [y]
for t in range(1, len(obs)):
V.append({})
newpath = {}
for y in states:
(prob, state) = max([(V[t-1][y0] * trans_p[y0].get(y, 0) * emit_p[y].get(obs[t], 0), y0) for y0 in states if V[t-1][y0] > 0])
V[t][y] = prob
newpath[y] = path[state] + [y]
path = newpath
(prob, state) = max([(V[len(obs)-1][y], y) for y in states])
return prob, path[state]

# 对测试集进行词性标注并计算准确率
total_count = 0
correct_count = 0
for word, pos in test_words:
if word in word_pos_prob.get(pos, {}):
obs = [word]
states = list(pos_count.keys())
start_p = pos_init_prob
trans_p = pos_trans_prob
emit_p = word_pos_prob[pos]
prob, path = viterbi(obs, states, start_p, trans_p, emit_p)
if path[pos][0] == pos:
correct_count += 1
total_count += 1
accuracy = correct_count / total_count
print('Accuracy: {}'.format(accuracy))