Add tests for torchtext and torchvision (#1046)

tests/test_torchtext.py

@@ -0,0 +1,12 @@
+import unittest
+
+from torchtext.data.metrics import bleu_score
+
+
+class TestTorchtext(unittest.TestCase):
+ def test_bleu_score(self):
+ candidate = [['I', 'love', 'Kaggle', 'Notebooks']]
+ refs = [[['Completely', 'Different']]]
+
+ self.assertEqual(0, bleu_score(candidate, refs))
+

tests/test_torchvision.py

@@ -0,0 +1,25 @@
+import unittest
+
+import torch
+import torchvision.transforms as transforms
+import torchvision.transforms.functional as F
+
+
+class TestTorchvision(unittest.TestCase):
+ def test_float_to_float(self):
+ input_dtype=torch.float32
+ output_dtype=torch.float64
+ input_image = torch.tensor((0.0, 1.0), dtype=input_dtype)
+ transform = transforms.ConvertImageDtype(output_dtype)
+ transform_script = torch.jit.script(F.convert_image_dtype)
+
+ output_image = transform(input_image)
+ output_image_script = transform_script(input_image, output_dtype)
+
+ # TODO(b/181966788) Uncomment after upgrade to pytorch 1.9.0 is done.
+ # torch.testing.assert_close(output_image_script, output_image, rtol=0.0, atol=1e-6)
+
+ actual_min, actual_max = output_image.tolist()
+
+ self.assertAlmostEqual(0, actual_min)
+ self.assertAlmostEqual(1, actual_max)