feat(tests): add unittest for PCAEncoder

tests/test_pca_encoder.py

@@ -0,0 +1,30 @@
+import os
+import unittest
+import numpy as np
+
+from gnes.encoder.base import BaseEncoder
+
+
+class TestPCAEncoder(unittest.TestCase):
+
+    def setUp(self):
+        dirname = os.path.dirname(__file__)
+        self.dump_path = os.path.join(dirname, 'pca_encoder.bin')
+        self.yaml_path = os.path.join(dirname, 'yaml', 'pca.yml')
+        self.test_numeric = np.random.randint(0, 255, (1000, 1024)).astype('float32')
+
+    def test_encoding(self):
+        self.encoder = BaseEncoder.load_yaml(self.yaml_path)
+        # train before encode to create pca_components
+        self.encoder.train(self.test_numeric)
+        vec = self.encoder.encode(self.test_numeric)
+        self.assertEqual(vec.shape, (1000, 300))
+        # dump after train with valied pca_components
+        self.encoder.dump(self.dump_path)
+        encoder2 = BaseEncoder.load(self.dump_path)
+        vec = encoder2.encode(self.test_numeric)
+        self.assertEqual(vec.shape, (1000, 300))
+
+    def tearDown(self):
+        if os.path.exists(self.dump_path):
+            os.remove(self.dump_path)

tests/yaml/pca.yml

@@ -0,0 +1,8 @@
+!PCAEncoder
+parameters:
+  output_dim: 300
+gnes_config:
+  name: pca_encoder
+  on_gpu: false
+  work_dir: ./
+