def test_seq_label(self):
model_args = {
"vocab_size": 10,
"word_emb_dim": 100,
"rnn_hidden_units": 100,
"num_classes": 5
}
infer_data = [['a', 'b', 'c', 'd', 'e'], ['a', '@', 'c', 'd', 'e'],
['a', 'b', '#', 'd', 'e'], ['a', 'b', 'c', '?', 'e'],
['a', 'b', 'c', 'd', '$'], ['!', 'b', 'c', 'd', 'e']]
vocab = Vocabulary()
vocab.word2idx = {
'a': 0,
'b': 1,
'c': 2,
'd': 3,
'e': 4,
'!': 5,
'@': 6,
'#': 7,
'$': 8,
'?': 9
}
class_vocab = Vocabulary()
class_vocab.word2idx = {"0": 0, "1": 1, "2": 2, "3": 3, "4": 4}
os.system("mkdir save")
save_pickle(class_vocab, "./save/", "class2id.pkl")
save_pickle(vocab, "./save/", "word2id.pkl")
model = SeqLabeling(model_args)
predictor = Predictor("./save/", task="seq_label")
results = predictor.predict(network=model, data=infer_data)
self.assertTrue(isinstance(results, list))
self.assertGreater(len(results), 0)
for res in results:
self.assertTrue(isinstance(res, list))
self.assertEqual(len(res), 5)
self.assertTrue(isinstance(res[0], str))
os.system("rm -rf save")
print("pickle path deleted")
def test_seq_label(self):
model_args = {
"vocab_size": 10,
"word_emb_dim": 100,
"rnn_hidden_units": 100,
"num_classes": 5
}
infer_data = [['a', 'b', 'c', 'd', 'e'], ['a', '@', 'c', 'd', 'e'],
['a', 'b', '#', 'd', 'e'], ['a', 'b', 'c', '?', 'e'],
['a', 'b', 'c', 'd', '$'], ['!', 'b', 'c', 'd', 'e']]
vocab = Vocabulary()
vocab.word2idx = {
'a': 0,
'b': 1,
'c': 2,
'd': 3,
'e': 4,
'!': 5,
'@': 6,
'#': 7,
'$': 8,
'?': 9
}
class_vocab = Vocabulary()
class_vocab.word2idx = {"0": 0, "1": 1, "2": 2, "3": 3, "4": 4}
os.system("mkdir save")
save_pickle(class_vocab, "./save/", "label2id.pkl")
save_pickle(vocab, "./save/", "word2id.pkl")
model = CNNText(model_args)
import fastNLP.core.predictor as pre
predictor = Predictor("./save/", pre.text_classify_post_processor)
# Load infer data
infer_data_set = convert_seq_dataset(infer_data)
infer_data_set.index_field("word_seq", vocab)
results = predictor.predict(network=model, data=infer_data_set)
self.assertTrue(isinstance(results, list))
self.assertGreater(len(results), 0)
self.assertEqual(len(results), len(infer_data))
for res in results:
self.assertTrue(isinstance(res, str))
self.assertTrue(res in class_vocab.word2idx)
del model, predictor
infer_data_set.set_origin_len("word_seq")
model = SeqLabeling(model_args)
predictor = Predictor("./save/", pre.seq_label_post_processor)
results = predictor.predict(network=model, data=infer_data_set)
self.assertTrue(isinstance(results, list))
self.assertEqual(len(results), len(infer_data))
for i in range(len(infer_data)):
res = results[i]
self.assertTrue(isinstance(res, list))
self.assertEqual(len(res), len(infer_data[i]))
os.system("rm -rf save")
print("pickle path deleted")
