Reenable tests that were mostly good already

.github/workflows/pytest.yml

@@ -34,9 +34,12 @@ jobs:
             --ignore=pymc3/tests/test_model_graph.py
             --ignore=pymc3/tests/test_modelcontext.py
             --ignore=pymc3/tests/test_parallel_sampling.py
+            --ignore=pymc3/tests/test_posteriors.py
+            --ignore=pymc3/tests/test_sampling.py
             --ignore=pymc3/tests/test_profile.py
             --ignore=pymc3/tests/test_step.py
             --ignore=pymc3/tests/test_tuning.py
+            --ignore=pymc3/tests/test_transforms.py
             --ignore=pymc3/tests/test_types.py
             --ignore=pymc3/tests/test_variational_inference.py
             --ignore=pymc3/tests/test_sampling_jax.py
@@ -57,25 +60,35 @@ jobs:
             --ignore=pymc3/tests/test_distributions_random.py
             --ignore=pymc3/tests/test_idata_conversion.py
 
+          - pymc3/tests/test_distributions.py
+
           - |
             pymc3/tests/test_modelcontext.py
             pymc3/tests/test_dist_math.py
             pymc3/tests/test_minibatches.py
             pymc3/tests/test_pickling.py
             pymc3/tests/test_plots.py
             pymc3/tests/test_updates.py
+            pymc3/tests/test_transforms.py
+
+          - |
+            pymc3/tests/test_parallel_sampling.py
+            pymc3/tests/test_sampling.py
+            pymc3/tests/test_tuning.py
+            pymc3/tests/test_posteriors.py
 
           - |
             pymc3/tests/test_idata_conversion.py
-            pymc3/tests/test_distributions.py
             pymc3/tests/test_distributions_random.py
+            pymc3/tests/test_distributions_timeseries.py
             pymc3/tests/test_examples.py
             pymc3/tests/test_gp.py
             pymc3/tests/test_model.py
             pymc3/tests/test_model_func.py
             pymc3/tests/test_model_graph.py
             pymc3/tests/test_ode.py
             pymc3/tests/test_posdef_sym.py
+            pymc3/tests/test_profile.py
             pymc3/tests/test_quadpotential.py
             pymc3/tests/test_shape_handling.py
             pymc3/tests/test_step.py
@@ -140,8 +153,11 @@ jobs:
         test-subset:
           - |
             pymc3/tests/test_distributions_random.py
+            pymc3/tests/test_distributions_timeseries.py
           - |
+            pymc3/tests/test_parallel_sampling.py
             pymc3/tests/test_sampling.py
+            pymc3/tests/test_tuning.py
             pymc3/tests/test_shared.py
           - |
             pymc3/tests/test_gp.py
@@ -152,6 +168,7 @@ jobs:
             pymc3/tests/test_modelcontext.py
             pymc3/tests/test_model_graph.py
             pymc3/tests/test_pickling.py
+            pymc3/tests/test_profile.py
 
       fail-fast: false
     runs-on: ${{ matrix.os }}

pymc3/tests/test_distributions.py

@@ -1056,7 +1056,7 @@ def test_chisquared_logp(self):
             lambda value, nu: sp.chi2.logpdf(value, df=nu),
         )
 
-    @pytest.mark.xfail(
+    @pytest.mark.skipif(
         condition=(aesara.config.floatX == "float32"),
         reason="Fails on float32 due to numerical issues",
     )
@@ -1423,7 +1423,7 @@ def test_fun(value, mu, sigma):
             test_fun,
         )
 
-    @pytest.mark.xfail(
+    @pytest.mark.skipif(
         condition=(aesara.config.floatX == "float32"),
         reason="Fails on float32 due to numerical issues",
     )
@@ -1449,7 +1449,7 @@ def test_inverse_gamma_logp(self):
         # pymc-devs/aesara#224: skip_paramdomain_outside_edge_test has to be set
         # True to avoid triggering a C-level assertion in the Aesara GammaQ function
 
-    @pytest.mark.xfail(
+    @pytest.mark.skipif(
         condition=(aesara.config.floatX == "float32"),
         reason="Fails on float32 due to numerical issues",
     )
@@ -1465,7 +1465,7 @@ def test_inverse_gamma_logcdf(self):
             skip_paramdomain_outside_edge_test=True,
         )
 
-    @pytest.mark.xfail(
+    @pytest.mark.skipif(
         condition=(aesara.config.floatX == "float32"),
         reason="Fails on float32 due to scaling issues",
     )
@@ -1496,7 +1496,7 @@ def test_pareto(self):
             lambda value, alpha, m: sp.pareto.logcdf(value, alpha, scale=m),
         )
 
-    @pytest.mark.xfail(
+    @pytest.mark.skipif(
         condition=(aesara.config.floatX == "float32"),
         reason="Fails on float32 due to numerical issues",
     )
@@ -1508,7 +1508,7 @@ def test_weibull_logp(self):
             lambda value, alpha, beta: sp.exponweib.logpdf(value, 1, alpha, scale=beta),
         )
 
-    @pytest.mark.xfail(
+    @pytest.mark.skipif(
         condition=(aesara.config.floatX == "float32"),
         reason="Fails on float32 due to inf issues",
     )
@@ -1560,7 +1560,7 @@ def test_binomial(self):
         )
 
     @pytest.mark.xfail(reason="checkd tests has not been refactored")
-    @pytest.mark.xfail(condition=(aesara.config.floatX == "float32"), reason="Fails on float32")
+    @pytest.mark.skipif(condition=(aesara.config.floatX == "float32"), reason="Fails on float32")
     def test_beta_binomial_distribution(self):
         self.checkd(
             BetaBinomial,
@@ -1681,7 +1681,7 @@ def test_constantdist(self):
         self.check_logp(Constant, I, {"c": I}, lambda value, c: np.log(c == value))
 
     @pytest.mark.xfail(reason="Test has not been refactored")
-    @pytest.mark.xfail(
+    @pytest.mark.skipif(
         condition=(aesara.config.floatX == "float32"),
         reason="Fails on float32 due to inf issues",
     )
@@ -1723,7 +1723,7 @@ def logcdf_fn(value, psi, theta):
         )
 
     @pytest.mark.xfail(reason="Test not refactored yet")
-    @pytest.mark.xfail(
+    @pytest.mark.skipif(
         condition=(aesara.config.floatX == "float32"),
         reason="Fails on float32 due to inf issues",
     )
@@ -1860,7 +1860,7 @@ def test_mvnormal(self, n):
             extra_args={"lower": False},
         )
 
-    @pytest.mark.xfail(
+    @pytest.mark.skipif(
         condition=(aesara.config.floatX == "float32"),
         reason="Fails on float32 due to inf issues",
     )
@@ -2521,7 +2521,7 @@ def test_ex_gaussian_cdf_outside_edges(self):
             skip_paramdomain_inside_edge_test=True,  # Valid values are tested above
         )
 
-    @pytest.mark.xfail(condition=(aesara.config.floatX == "float32"), reason="Fails on float32")
+    @pytest.mark.skipif(condition=(aesara.config.floatX == "float32"), reason="Fails on float32")
     def test_vonmises(self):
         self.check_logp(
             VonMises,
@@ -2571,7 +2571,7 @@ def test_logitnormal(self):
             decimal=select_by_precision(float64=6, float32=1),
         )
 
-    @pytest.mark.xfail(
+    @pytest.mark.skipif(
         condition=(aesara.config.floatX == "float32"),
         reason="Some combinations underflow to -inf in float32 in pymc version",
     )
@@ -2603,7 +2603,7 @@ def test_moyal_logp(self):
             lambda value, mu, sigma: floatX(sp.moyal.logpdf(value, mu, sigma)),
         )
 
-    @pytest.mark.xfail(
+    @pytest.mark.skipif(
         condition=(aesara.config.floatX == "float32"),
         reason="Pymc3 underflows earlier than scipy on float32",
     )
@@ -2617,7 +2617,7 @@ def test_moyal_logcdf(self):
         if aesara.config.floatX == "float32":
             raise Exception("Flaky test: It passed this time, but XPASS is not allowed.")
 
-    @pytest.mark.xfail(condition=(aesara.config.floatX == "float32"), reason="Fails on float32")
+    @pytest.mark.skipif(condition=(aesara.config.floatX == "float32"), reason="Fails on float32")
     def test_interpolated(self):
         for mu in R.vals:
             for sigma in Rplus.vals:

pymc3/tests/test_parallel_sampling.py

@@ -89,39 +89,51 @@ def test_remote_pipe_closed():
             pm.sample(step=step, mp_ctx="spawn", tune=2, draws=2, cores=2, chains=2)
 
 
+@pytest.mark.xfail(
+    reason="Possibly the same issue described in https://github.com/pymc-devs/pymc3/pull/4701"
+)
 def test_abort():
     with pm.Model() as model:
         a = pm.Normal("a", shape=1)
         pm.HalfNormal("b")
         step1 = pm.NUTS([a])
-        step2 = pm.Metropolis([model.b_log__])
+        step2 = pm.Metropolis([model["b_log__"]])
 
     step = pm.CompoundStep([step1, step2])
 
-    ctx = multiprocessing.get_context()
-    proc = ps.ProcessAdapter(
-        10,
-        10,
-        step,
-        chain=3,
-        seed=1,
-        mp_ctx=ctx,
-        start={"a": 1.0, "b_log__": 2.0},
-        step_method_pickled=None,
-        pickle_backend="pickle",
-    )
-    proc.start()
-    proc.write_next()
-    proc.abort()
-    proc.join()
-
-
+    for abort in [False, True]:
+        ctx = multiprocessing.get_context()
+        proc = ps.ProcessAdapter(
+            10,
+            10,
+            step,
+            chain=3,
+            seed=1,
+            mp_ctx=ctx,
+            start={"a": np.array([1.0]), "b_log__": np.array(2.0)},
+            step_method_pickled=None,
+            pickle_backend="pickle",
+        )
+        proc.start()
+        while True:
+            proc.write_next()
+            out = ps.ProcessAdapter.recv_draw([proc])
+            if out[1]:
+                break
+        if abort:
+            proc.abort()
+        proc.join()
+
+
+@pytest.mark.xfail(
+    reason="Possibly the same issue described in https://github.com/pymc-devs/pymc3/pull/4701"
+)
 def test_explicit_sample():
     with pm.Model() as model:
         a = pm.Normal("a", shape=1)
         pm.HalfNormal("b")
         step1 = pm.NUTS([a])
-        step2 = pm.Metropolis([model.b_log__])
+        step2 = pm.Metropolis([model["b_log__"]])
 
     step = pm.CompoundStep([step1, step2])
 
@@ -133,7 +145,7 @@ def test_explicit_sample():
         chain=3,
         seed=1,
         mp_ctx=ctx,
-        start={"a": 1.0, "b_log__": 2.0},
+        start={"a": np.array([1.0]), "b_log__": np.array(2.0)},
         step_method_pickled=None,
         pickle_backend="pickle",
     )
@@ -149,22 +161,26 @@ def test_explicit_sample():
     proc.join()
 
 
+@pytest.mark.xfail(
+    reason="Possibly the same issue described in https://github.com/pymc-devs/pymc3/pull/4701"
+)
 def test_iterator():
     with pm.Model() as model:
         a = pm.Normal("a", shape=1)
         pm.HalfNormal("b")
         step1 = pm.NUTS([a])
-        step2 = pm.Metropolis([model.b_log__])
+        step2 = pm.Metropolis([model["b_log__"]])
 
     step = pm.CompoundStep([step1, step2])
 
-    start = {"a": 1.0, "b_log__": 2.0}
+    start = {"a": np.array([1.0]), "b_log__": np.array(2.0)}
     sampler = ps.ParallelSampler(10, 10, 3, 2, [2, 3, 4], [start] * 3, step, 0, False)
     with sampler:
         for draw in sampler:
             pass
 
 
+@pytest.mark.xfail(reason="DensityDist was not yet refactored for v4")
 def test_spawn_densitydist_function():
     with pm.Model() as model:
         mu = pm.Normal("mu", 0, 1)
@@ -176,16 +192,19 @@ def func(x):
         pm.sample(draws=10, tune=10, step=pm.Metropolis(), cores=2, mp_ctx="spawn")
 
 
+@pytest.mark.xfail(reason="DensityDist was not yet refactored for v4")
 def test_spawn_densitydist_bound_method():
     with pm.Model() as model:
         mu = pm.Normal("mu", 0, 1)
         normal_dist = pm.Normal.dist(mu, 1)
-        obs = pm.DensityDist("density_dist", normal_dist.logp, observed=np.random.randn(100))
+        logp = lambda x: pm.logp(normal_dist, x, transformed=False)
+        obs = pm.DensityDist("density_dist", logp, observed=np.random.randn(100))
         msg = "logp for DensityDist is a bound method, leading to RecursionError while serializing"
         with pytest.raises(ValueError, match=msg):
             pm.sample(draws=10, tune=10, step=pm.Metropolis(), cores=2, mp_ctx="spawn")
 
 
+@pytest.mark.xfail(reason="DensityDist was not yet refactored for v4")
 def test_spawn_densitydist_syswarning(monkeypatch):
     monkeypatch.setattr("pymc3.distributions.distribution.PLATFORM", "win32")
     with pm.Model() as model:
@@ -195,6 +214,7 @@ def test_spawn_densitydist_syswarning(monkeypatch):
             obs = pm.DensityDist("density_dist", normal_dist.logp, observed=np.random.randn(100))
 
 
+@pytest.mark.xfail(reason="DensityDist was not yet refactored for v4")
 def test_spawn_densitydist_mpctxwarning(monkeypatch):
     ctx = multiprocessing.get_context("spawn")
     monkeypatch.setattr(multiprocessing, "get_context", lambda: ctx)

pymc3/tests/test_profile.py

@@ -12,6 +12,8 @@
 #   See the License for the specific language governing permissions and
 #   limitations under the License.
 
+import pymc3 as pm
+
 from pymc3.tests.models import simple_model
 
 
@@ -23,7 +25,8 @@ def test_profile_model(self):
         assert self.model.profile(self.model.logpt).fct_call_time > 0
 
     def test_profile_variable(self):
-        assert self.model.profile(self.model.value_vars[0].logpt).fct_call_time > 0
+        rv = self.model.basic_RVs[0]
+        assert self.model.profile(pm.logpt(rv, self.model.rvs_to_values[rv])).fct_call_time
 
     def test_profile_count(self):
         count = 1005