add tests to encoder-decoder model

transformers/tests/modeling_common_test.py

@@ -704,6 +704,22 @@ def ids_tensor(shape, vocab_size, rng=None, name=None):
     return torch.tensor(data=values, dtype=torch.long).view(shape).contiguous()
 
 
+def floats_tensor(shape, scale=1.0, rng=None, name=None):
+    """Creates a random float32 tensor of the shape within the vocab size."""
+    if rng is None:
+        rng = global_rng
+
+    total_dims = 1
+    for dim in shape:
+        total_dims *= dim
+
+    values = []
+    for _ in range(total_dims):
+        values.append(rng.random() * scale)
+
+    return torch.tensor(data=values, dtype=torch.float).view(shape).contiguous()
+
+
 class ModelUtilsTest(unittest.TestCase):
     def test_model_from_pretrained(self):
         logging.basicConfig(level=logging.INFO)