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- import os
- import unittest
-
- from fastNLP import DataSet
- from fastNLP import FieldArray
- from fastNLP import Instance
- from fastNLP.io import CSVLoader
-
-
- class TestDataSetInit(unittest.TestCase):
- """初始化DataSet的办法有以下几种:
- 1) 用dict:
- 1.1) 二维list DataSet({"x": [[1, 2], [3, 4]]})
- 1.2) 二维array DataSet({"x": np.array([[1, 2], [3, 4]])})
- 1.3) 三维list DataSet({"x": [[[1, 2], [3, 4]], [[1, 2], [3, 4]]]})
- 2) 用list of Instance:
- 2.1) 一维list DataSet([Instance(x=[1, 2, 3, 4])])
- 2.2) 一维array DataSet([Instance(x=np.array([1, 2, 3, 4]))])
- 2.3) 二维list DataSet([Instance(x=[[1, 2], [3, 4]])])
- 2.4) 二维array DataSet([Instance(x=np.array([[1, 2], [3, 4]]))])
-
- 只接受纯list或者最外层ndarray
- """
- def test_init_v1(self):
- # 一维list
- ds = DataSet([Instance(x=[1, 2, 3, 4], y=[5, 6])] * 40)
- self.assertTrue("x" in ds.field_arrays and "y" in ds.field_arrays)
- self.assertEqual(ds.field_arrays["x"].content, [[1, 2, 3, 4], ] * 40)
- self.assertEqual(ds.field_arrays["y"].content, [[5, 6], ] * 40)
-
- def test_init_v2(self):
- # 用dict
- ds = DataSet({"x": [[1, 2, 3, 4]] * 40, "y": [[5, 6]] * 40})
- self.assertTrue("x" in ds.field_arrays and "y" in ds.field_arrays)
- self.assertEqual(ds.field_arrays["x"].content, [[1, 2, 3, 4], ] * 40)
- self.assertEqual(ds.field_arrays["y"].content, [[5, 6], ] * 40)
-
- def test_init_assert(self):
- with self.assertRaises(AssertionError):
- _ = DataSet({"x": [[1, 2, 3, 4]] * 40, "y": [[5, 6]] * 100})
- with self.assertRaises(AssertionError):
- _ = DataSet([[1, 2, 3, 4]] * 10)
- with self.assertRaises(ValueError):
- _ = DataSet(0.00001)
-
-
- class TestDataSetMethods(unittest.TestCase):
- def test_append(self):
- dd = DataSet()
- for _ in range(3):
- dd.append(Instance(x=[1, 2, 3, 4], y=[5, 6]))
- self.assertEqual(len(dd), 3)
- self.assertEqual(dd.field_arrays["x"].content, [[1, 2, 3, 4]] * 3)
- self.assertEqual(dd.field_arrays["y"].content, [[5, 6]] * 3)
-
- def test_add_field(self):
- dd = DataSet()
- dd.add_field("x", [[1, 2, 3]] * 10)
- dd.add_field("y", [[1, 2, 3, 4]] * 10)
- dd.add_field("z", [[5, 6]] * 10)
- self.assertEqual(len(dd), 10)
- self.assertEqual(dd.field_arrays["x"].content, [[1, 2, 3]] * 10)
- self.assertEqual(dd.field_arrays["y"].content, [[1, 2, 3, 4]] * 10)
- self.assertEqual(dd.field_arrays["z"].content, [[5, 6]] * 10)
-
- with self.assertRaises(RuntimeError):
- dd.add_field("??", [[1, 2]] * 40)
-
- def test_add_field_ignore_type(self):
- dd = DataSet()
- dd.add_field("x", [(1, "1"), (2, "2"), (3, "3"), (4, "4")], ignore_type=True, is_target=True)
- dd.add_field("y", [{1, "1"}, {2, "2"}, {3, "3"}, {4, "4"}], ignore_type=True, is_target=True)
-
- def test_delete_field(self):
- dd = DataSet()
- dd.add_field("x", [[1, 2, 3]] * 10)
- dd.add_field("y", [[1, 2, 3, 4]] * 10)
- dd.delete_field("x")
- self.assertFalse("x" in dd.field_arrays)
- self.assertTrue("y" in dd.field_arrays)
-
- def test_getitem(self):
- ds = DataSet({"x": [[1, 2, 3, 4]] * 40, "y": [[5, 6]] * 40})
- ins_1, ins_0 = ds[0], ds[1]
- self.assertTrue(isinstance(ins_1, Instance) and isinstance(ins_0, Instance))
- self.assertEqual(ins_1["x"], [1, 2, 3, 4])
- self.assertEqual(ins_1["y"], [5, 6])
- self.assertEqual(ins_0["x"], [1, 2, 3, 4])
- self.assertEqual(ins_0["y"], [5, 6])
-
- sub_ds = ds[:10]
- self.assertTrue(isinstance(sub_ds, DataSet))
- self.assertEqual(len(sub_ds), 10)
-
- def test_get_item_error(self):
- with self.assertRaises(RuntimeError):
- ds = DataSet({"x": [[1, 2, 3, 4]] * 10, "y": [[5, 6]] * 10})
- _ = ds[40:]
-
- with self.assertRaises(KeyError):
- ds = DataSet({"x": [[1, 2, 3, 4]] * 10, "y": [[5, 6]] * 10})
- _ = ds["kom"]
-
- def test_len_(self):
- ds = DataSet({"x": [[1, 2, 3, 4]] * 40, "y": [[5, 6]] * 40})
- self.assertEqual(len(ds), 40)
-
- ds = DataSet()
- self.assertEqual(len(ds), 0)
-
- def test_apply(self):
- ds = DataSet({"x": [[1, 2, 3, 4]] * 40, "y": [[5, 6]] * 40})
- ds.apply(lambda ins: ins["x"][::-1], new_field_name="rx")
- self.assertTrue("rx" in ds.field_arrays)
- self.assertEqual(ds.field_arrays["rx"].content[0], [4, 3, 2, 1])
-
- ds.apply(lambda ins: len(ins["y"]), new_field_name="y")
- self.assertEqual(ds.field_arrays["y"].content[0], 2)
-
- res = ds.apply(lambda ins: len(ins["x"]))
- self.assertTrue(isinstance(res, list) and len(res) > 0)
- self.assertTrue(res[0], 4)
-
- ds.apply(lambda ins: (len(ins["x"]), "hahaha"), new_field_name="k", ignore_type=True)
- # expect no exception raised
-
- def test_drop(self):
- ds = DataSet({"x": [[1, 2, 3, 4]] * 40, "y": [[5, 6], [7, 8, 9, 0]] * 20})
- ds.drop(lambda ins: len(ins["y"]) < 3, inplace=True)
- self.assertEqual(len(ds), 20)
-
- def test_contains(self):
- ds = DataSet({"x": [[1, 2, 3, 4]] * 40, "y": [[5, 6]] * 40})
- self.assertTrue("x" in ds)
- self.assertTrue("y" in ds)
- self.assertFalse("z" in ds)
-
- def test_rename_field(self):
- ds = DataSet({"x": [[1, 2, 3, 4]] * 10, "y": [[5, 6]] * 10})
- ds.rename_field("x", "xx")
- self.assertTrue("xx" in ds)
- self.assertFalse("x" in ds)
-
- with self.assertRaises(KeyError):
- ds.rename_field("yyy", "oo")
-
- def test_input_target(self):
- ds = DataSet({"x": [[1, 2, 3, 4]] * 10, "y": [[5, 6]] * 10})
- ds.set_input("x")
- ds.set_target("y")
- self.assertTrue(ds.field_arrays["x"].is_input)
- self.assertTrue(ds.field_arrays["y"].is_target)
-
- with self.assertRaises(KeyError):
- ds.set_input("xxx")
- with self.assertRaises(KeyError):
- ds.set_input("yyy")
-
- def test_get_input_name(self):
- ds = DataSet({"x": [[1, 2, 3, 4]] * 10, "y": [[5, 6]] * 10})
- self.assertEqual(ds.get_input_name(), [_ for _ in ds.field_arrays if ds.field_arrays[_].is_input])
-
- def test_get_target_name(self):
- ds = DataSet({"x": [[1, 2, 3, 4]] * 10, "y": [[5, 6]] * 10})
- self.assertEqual(ds.get_target_name(), [_ for _ in ds.field_arrays if ds.field_arrays[_].is_target])
-
- def test_split(self):
- ds = DataSet({"x": [[1, 2, 3, 4]] * 10, "y": [[5, 6]] * 10})
- d1, d2 = ds.split(0.1)
-
- def test_apply2(self):
- def split_sent(ins):
- return ins['raw_sentence'].split()
- csv_loader = CSVLoader(headers=['raw_sentence', 'label'],sep='\t')
- dataset = csv_loader.load('test/data_for_tests/tutorial_sample_dataset.csv')
- dataset.drop(lambda x: len(x['raw_sentence'].split()) == 0, inplace=True)
- dataset.apply(split_sent, new_field_name='words', is_input=True)
- # print(dataset)
-
- def test_add_field_v2(self):
- ds = DataSet({"x": [3, 4]})
- ds.add_field('y', [['hello', 'world'], ['this', 'is', 'a', 'test']], is_input=True, is_target=True)
- # ds.apply(lambda x:[x['x']]*3, is_input=True, is_target=True, new_field_name='y')
- print(ds)
-
- def test_save_load(self):
- ds = DataSet({"x": [[1, 2, 3, 4]] * 10, "y": [[5, 6]] * 10})
- ds.save("./my_ds.pkl")
- self.assertTrue(os.path.exists("./my_ds.pkl"))
-
- ds_1 = DataSet.load("./my_ds.pkl")
- os.remove("my_ds.pkl")
-
- def test_get_all_fields(self):
- ds = DataSet({"x": [[1, 2, 3, 4]] * 10, "y": [[5, 6]] * 10})
- ans = ds.get_all_fields()
- self.assertEqual(ans["x"].content, [[1, 2, 3, 4]] * 10)
- self.assertEqual(ans["y"].content, [[5, 6]] * 10)
-
- def test_get_field(self):
- ds = DataSet({"x": [[1, 2, 3, 4]] * 10, "y": [[5, 6]] * 10})
- ans = ds.get_field("x")
- self.assertTrue(isinstance(ans, FieldArray))
- self.assertEqual(ans.content, [[1, 2, 3, 4]] * 10)
- ans = ds.get_field("y")
- self.assertTrue(isinstance(ans, FieldArray))
- self.assertEqual(ans.content, [[5, 6]] * 10)
-
- def test_add_null(self):
- # TODO test failed because 'fastNLP\core\field.py:143: RuntimeError'
- ds = DataSet()
- with self.assertRaises(RuntimeError) as RE:
- ds.add_field('test', [])
-
-
- class TestDataSetIter(unittest.TestCase):
- def test__repr__(self):
- ds = DataSet({"x": [[1, 2, 3, 4]] * 10, "y": [[5, 6]] * 10})
- for iter in ds:
- self.assertEqual(iter.__repr__(), "{'x': [1, 2, 3, 4] type=list,\n'y': [5, 6] type=list}")
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