Merge pull request #344 from markstur/embed_same_test

Embedding add a test that would have helped

Author: evaline-ju

tests/modules/text_embedding/test_embedding.py

@@ -1054,3 +1054,43 @@ def test_encode_extensions(loaded_model):
     BOOTSTRAPPED_MODEL._encode_with_retry(
         "text here"
     )  # and no KeyError trying to remove non-existing keys
+
+
+@pytest.mark.parametrize(
+    "truncate_input_tokens",
+    [0, 1, 2, 3, 4, 5, 99, 100, 101, 300, 510, 511, 512, 513, 1000, -1],
+)
+def test_same_same(loaded_model: EmbeddingModule, truncate_input_tokens):
+    """Confirm that same text gives same results"""
+
+    inputs = ["What is generative ai?", "What is generative ai?", "different"]
+
+    # First ensuring that batch input vs loop over inputs is the same
+    separate_embeddings = [
+        loaded_model.run_embedding(text=i, truncate_input_tokens=truncate_input_tokens)
+        for i in inputs
+    ]
+    combined_embeddings = loaded_model.run_embeddings(
+        texts=inputs, truncate_input_tokens=truncate_input_tokens
+    )
+
+    separate_vectors = [
+        e.to_dict()["result"]["data"]["values"] for e in separate_embeddings
+    ]
+    combined_vectors = [
+        e["data"]["values"] for e in combined_embeddings.to_dict()["results"]["vectors"]
+    ]
+
+    assert len(separate_vectors) == len(
+        combined_vectors
+    ), "expected the same number separate and combined embeddings"
+
+    # test order by comparing value of individual embeddings in sequence
+    for i, e in enumerate(separate_vectors):
+        assert np.allclose(e, combined_vectors[i])
+
+    # Next ensuring that the two identical sentences yield identical results (and 3rd does not)
+    assert np.array_equal(combined_vectors[0], combined_vectors[1])
+    assert not np.array_equal(combined_vectors[1], combined_vectors[2])
+    assert np.array_equal(separate_vectors[0], separate_vectors[1])
+    assert not np.array_equal(separate_vectors[1], separate_vectors[2])