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- import unittest
- from fastNLP.io.pipe.coreference import CoReferencePipe
-
-
- class TestCR(unittest.TestCase):
-
- def test_load(self):
- class Config():
- max_sentences = 50
- filter = [3, 4, 5]
- char_path = None
- config = Config()
-
- file_root_path = "test/data_for_tests/io/coreference/"
- train_path = file_root_path + "coreference_train.json"
- dev_path = file_root_path + "coreference_dev.json"
- test_path = file_root_path + "coreference_test.json"
-
- paths = {"train": train_path, "dev": dev_path, "test": test_path}
-
- bundle1 = CoReferencePipe(config).process_from_file(paths)
- bundle2 = CoReferencePipe(config).process_from_file(file_root_path)
- print(bundle1)
- print(bundle2)
- self.assertEqual(bundle1.num_dataset, 3)
- self.assertEqual(bundle2.num_dataset, 3)
- self.assertEqual(bundle1.num_vocab, 1)
- self.assertEqual(bundle2.num_vocab, 1)
-
- self.assertEqual(len(bundle1.get_dataset('train')), 1)
- self.assertEqual(len(bundle1.get_dataset('dev')), 1)
- self.assertEqual(len(bundle1.get_dataset('test')), 1)
- self.assertEqual(len(bundle1.get_vocab('words1')), 84)
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