Adds unit test for columnvector function

Summary: Adds unit test to the test_processing.py for columnvector function from transform.py

Reviewed By: igfox

Differential Revision: D31247953

fbshipit-source-id: 8e6eee0fecf3dfb0bff8fb3d168e15f002c0acf3

reagent/test/preprocessing/test_preprocessing.py

@@ -7,7 +7,7 @@
 import numpy.testing as npt
 import six
 import torch
-from reagent.preprocessing import identify_types, normalization
+from reagent.preprocessing import identify_types, normalization, transforms
 from reagent.preprocessing.identify_types import BOXCOX, CONTINUOUS, ENUM
 from reagent.preprocessing.normalization import (
     MISSING_VALUE,
@@ -363,3 +363,46 @@ def test_type_override_quantile(self):
             "_", probability_values, feature_type=identify_types.QUANTILE
         )
         self.assertEqual(parameter.feature_type, "QUANTILE")
+
+    def test_columnvector(self):
+        def format_input2output(test_keys, inp_form):
+            test_data = {}
+            for ky in test_keys:
+                test_data[ky] = inp_form
+            test_instance = transforms.ColumnVector(test_keys)
+            output_data = test_instance(test_data)
+            return output_data
+
+        test_values = range(0, 5)
+        test_keys = []
+        for k in test_values:
+            test_keys.append(str(k))
+
+        # Possible input formats: tuple, list, torch.Tensor
+        for n_len in [1, 3]:
+            test_input_forms = [
+                (np.ones((n_len, 1)), 0),
+                n_len * [1],
+                torch.tensor(np.ones((n_len, 1))),
+            ]
+            for inp_form in test_input_forms:
+                output_data = format_input2output(test_keys, inp_form)
+                for ky in test_keys:
+                    self.assertEqual(output_data[ky].shape[0], n_len)
+                    self.assertEqual(output_data[ky].shape[1], 1)
+
+        # Input as in row format
+        test_data = {}
+        for ky in test_keys:
+            test_data[ky] = (np.ones((1, 3)), 0)
+        test_instance = transforms.ColumnVector(test_keys)
+        with self.assertRaisesRegex(AssertionError, "Invalid shape for key"):
+            output_data = test_instance(test_data)
+
+        # Input as unimplemented type (number)
+        test_data = {}
+        for ky in test_keys:
+            test_data[ky] = 1
+        test_instance = transforms.ColumnVector(test_keys)
+        with self.assertRaisesRegex(NotImplementedError, "value of type"):
+            output_data = test_instance(test_data)