Float32 skipif on Beta and StudentT logcdf tests

Author: ricardoV94

pymc3/tests/test_distributions.py

@@ -1151,7 +1151,7 @@ def test_wald_logp_custom_points(self, value, mu, lam, phi, alpha, logp):
         decimals = select_by_precision(float64=6, float32=1)
         assert_almost_equal(model.fastlogp(pt), logp, decimal=decimals, err_msg=str(pt))
 
-    def test_beta(self):
+    def test_beta_logp(self):
         self.check_logp(
             Beta,
             Unit,
@@ -1164,12 +1164,17 @@ def test_beta(self):
             {"mu": Unit, "sigma": Rplus},
             beta_mu_sigma,
         )
+
+    @pytest.mark.skipif(
+        condition=(aesara.config.floatX == "float32"),
+        reason="Fails on float32 due to numerical issues",
+    )
+    def test_beta_logcdf(self):
         self.check_logcdf(
             Beta,
             Unit,
             {"alpha": Rplus, "beta": Rplus},
             lambda value, alpha, beta: sp.beta.logcdf(value, alpha, beta),
-            decimal=select_by_precision(float64=5, float32=3),
         )
 
     def test_kumaraswamy(self):
@@ -1373,7 +1378,7 @@ def test_lognormal(self):
             lambda value, mu, sigma: sp.lognorm.logcdf(value, sigma, 0, np.exp(mu)),
         )
 
-    def test_t(self):
+    def test_studentt_logp(self):
         self.check_logp(
             StudentT,
             R,
@@ -1386,21 +1391,24 @@ def test_t(self):
             {"nu": Rplus, "mu": R, "sigma": Rplus},
             lambda value, nu, mu, sigma: sp.t.logpdf(value, nu, mu, sigma),
         )
+
+    @pytest.mark.skipif(
+        condition=(aesara.config.floatX == "float32"),
+        reason="Fails on float32 due to numerical issues",
+    )
+    def test_studentt_logcdf(self):
         self.check_logcdf(
             StudentT,
             R,
             {"nu": Rplus, "mu": R, "lam": Rplus},
             lambda value, nu, mu, lam: sp.t.logcdf(value, nu, mu, lam ** -0.5),
         )
-        # TODO: reenable when PR #4736 is merged
-        """
         self.check_logcdf(
             StudentT,
             R,
             {"nu": Rplus, "mu": R, "sigma": Rplus},
             lambda value, nu, mu, sigma: sp.t.logcdf(value, nu, mu, sigma),
         )
-        """
 
     def test_cauchy(self):
         self.check_logp(