Make zip strict in apply_function_over_dataset

tests/variational/test_inference.py

@@ -188,33 +188,10 @@ def test_fit_start(inference_spec, simple_model):
     with simple_model:
         inference = inference_spec(**kw)
 
-    # Minibatch data can't be extracted into the `observed_data` group in the final InferenceData
-    [observed_value] = [simple_model.rvs_to_values[obs] for obs in simple_model.observed_RVs]
-
-    # We can`t use pytest.warns here because after version 8.0 it`s still check for warning when
-    # exception raised and test failed instead being skipped
-    warning_raised = False
-    expected_warning = observed_value.name.startswith("minibatch")
-    with warnings.catch_warnings(record=True) as record:
-        warnings.simplefilter("always")
-        with warnings.catch_warnings():
-            # Related to https://github.com/arviz-devs/arviz/issues/2327
-            warnings.filterwarnings(
-                "ignore", message="datetime.datetime.utcnow()", category=DeprecationWarning
-            )
-
-            try:
-                trace = inference.fit(n=0).sample(10000)
-            except NotImplementedInference as e:
-                pytest.skip(str(e))
-
-    if expected_warning:
-        assert len(record) > 0
-        for item in record:
-            assert issubclass(item.category, UserWarning)
-            assert "Could not extract data from symbolic observation" in str(item.message)
-    if not expected_warning:
-        assert not record
+    try:
+        trace = inference.fit(n=0).sample(10000)
+    except NotImplementedInference as e:
+        pytest.skip(str(e))
 
     np.testing.assert_allclose(np.mean(trace.posterior["mu"]), mu_init, rtol=0.05)
     if has_start_sigma: