def count_polY_accuracy(model, num_batchs, sess, save_dir):
symbol = Symbol(hp.vocab_path, hp.poly_dict_path)
with open(hp.poly_dict_path, 'r') as f:
POLY_DICT = json.load(f)
test_poly_dict = {}
for key, value in POLY_DICT.items():
POLY_DICT[key] = sorted(value)
test_poly_dict[key] = np.zeros((len(value), len(value)))
for i in range(num_batchs):
model_inputs, model_pre, mask, poly_mask, model_correct_pred, model_acc, model_outputs, model_targets, model_target_seq \
= sess.run([model.inputs, model.pred, model.mask, model.poly_mask, model.correct_pred, model.accuracy, model.outputs, model.targets, model.target_seq])
print("model_pred", model_pre)
print("model_accruacy", model_acc)
print("model_outputs", model_outputs)
print("model_mask", mask)
print("model_poly_mask", poly_mask)
print("model_targets", model_targets)
print("model_target_seq", model_target_seq)
print("model_correct_pred", model_correct_pred)
for pred_poly_seq, ta, model_input in zip(model_pre, model_target_seq,
model_inputs):
pred_poly = symbol.sequence_to_label(pred_poly_seq)
target_poly = symbol.sequence_to_label(ta)
word_value = symbol.input_to_word_value(model_input)
print(pred_poly)
print(target_poly)
print(word_value)
if len(pred_poly_seq) != len(ta):
print("length not equal")
print("-----------------")
continue
for p, t, w in zip(pred_poly, target_poly, word_value):
if t == "-":
continue
else:
i = POLY_DICT[w].index(p)
j = POLY_DICT[w].index(t)
test_poly_dict[w][i, j] += 1
print(w)
print(test_poly_dict[w])
print("Model Accuracy: {}".format(model_acc))
poly_accuracy_out = open(os.path.join(save_dir, "accuracy.out"), "w")
poly_count = open(os.path.join(save_dir, "poly_count.out"), "w")
for key, value in test_poly_dict.items():
accuracy = np.trace(value) / np.sum(value)
poly_accuracy_out.writelines("{}\t{}\t{}\t{}\n".format(
key, int(np.sum(value)), int(np.trace(value)), accuracy))
poly_count.writelines(key + "\n")
for i, poly_i in enumerate(POLY_DICT[key]):
for j, poly_j in enumerate(POLY_DICT[key]):
poly_count.write("{}->{}:{}\n".format(poly_i, poly_j,
int(value[i, j])))
def test_symbol(vocab_path, data_path, poly_dict_path):
symbol = Symbol(vocab_path, poly_dict_path)
with open(data_path, "r") as json_file:
data = json.load(json_file)
metadata = list(zip(data["features"], data["labels"]))
for meta in metadata:
input_data = np.asarray(symbol.feature_to_sequence(meta[0]),
dtype=np.float32)
target_data = np.asarray(symbol.label_to_sequence(meta[1]),
dtype=np.float32)
poly_mask = symbol.poly_mask(meta[0])
print(meta[0])
print(meta[1])
print("input_data" + "=" * 50)
print(input_data)
print("target_data" + "=" * 50)
print(target_data)
print("poly_mask" + "=" * 50)
print(poly_mask)
print("sequence to feature value " + "=" * 50)
print(symbol.input_to_word_value(input_data))
