Distribute test_variational_inference

Author: Armavica

.github/workflows/tests.yml

@@ -147,7 +147,7 @@ jobs:
         floatx: [float64]
         python-version: ["3.8"]
         test-subset:
-          - pymc/tests/test_variational_inference.py pymc/tests/test_initial_point.py
+          - pymc/tests/variational/test_approximations.py pymc/tests/variational/test_callbacks.py pymc/tests/variational/test_inference.py pymc/tests/variational/test_opvi.py pymc/tests/test_initial_point.py
           - pymc/tests/test_model.py pymc/tests/test_step.py
           - pymc/tests/gp/test_cov.py pymc/tests/gp/test_gp.py pymc/tests/gp/test_mean.py pymc/tests/gp/test_util.py pymc/tests/ode/test_ode.py pymc/tests/ode/test_utils.py pymc/tests/test_smc.py pymc/tests/test_parallel_sampling.py
           - pymc/tests/test_sampling.py pymc/tests/step_methods/test_metropolis.py pymc/tests/step_methods/test_slicer.py pymc/tests/step_methods/hmc/test_nuts.py

pymc/tests/models.py

@@ -35,6 +35,13 @@ def simple_model():
     return model.initial_point(), model, (mu, tau**-0.5)
 
 
+def another_simple_model():
+    _, _model, _ = simple_model()
+    with _model:
+        pm.Potential("pot", at.ones((10, 10)))
+    return _model
+
+
 def simple_categorical():
     p = floatX_array([0.1, 0.2, 0.3, 0.4])
     v = floatX_array([0.0, 1.0, 2.0, 3.0])