Fix GPU tests in test_mixture and test_models (#2060)

* Switch MAP solver to one that supports float32

* Switch MAP solver to one that supports float32

* Adjust precision in test_model for float32 mode

* Fix floatX in test_mixture

* Fix floatX in test_quad

Author: kyleabeauchamp

pymc3/tests/test_mixture.py

@@ -3,6 +3,7 @@
 
 from .helpers import SeededTest
 from pymc3 import Dirichlet, Gamma, Metropolis, Mixture, Model, Normal, NormalMixture, Poisson, sample
+from pymc3.theanof import floatX
 
 
 # Generate data
@@ -36,7 +37,7 @@ def setup_class(cls):
 
     def test_mixture_list_of_normals(self):
         with Model() as model:
-            w = Dirichlet('w', np.ones_like(self.norm_w))
+            w = Dirichlet('w', floatX(np.ones_like(self.norm_w)))
             mu = Normal('mu', 0., 10., shape=self.norm_w.size)
             tau = Gamma('tau', 1., 1., shape=self.norm_w.size)
             Mixture('x_obs', w,
@@ -54,7 +55,7 @@ def test_mixture_list_of_normals(self):
 
     def test_normal_mixture(self):
         with Model() as model:
-            w = Dirichlet('w', np.ones_like(self.norm_w))
+            w = Dirichlet('w', floatX(np.ones_like(self.norm_w)))
             mu = Normal('mu', 0., 10., shape=self.norm_w.size)
             tau = Gamma('tau', 1., 1., shape=self.norm_w.size)
             NormalMixture('x_obs', w, mu, tau=tau, observed=self.norm_x)
@@ -70,7 +71,7 @@ def test_normal_mixture(self):
 
     def test_poisson_mixture(self):
         with Model() as model:
-            w = Dirichlet('w', np.ones_like(self.pois_w))
+            w = Dirichlet('w', floatX(np.ones_like(self.pois_w)))
             mu = Gamma('mu', 1., 1., shape=self.pois_w.size)
             Mixture('x_obs', w, Poisson.dist(mu), observed=self.pois_x)
             step = Metropolis()
@@ -85,7 +86,7 @@ def test_poisson_mixture(self):
 
     def test_mixture_list_of_poissons(self):
         with Model() as model:
-            w = Dirichlet('w', np.ones_like(self.pois_w))
+            w = Dirichlet('w', floatX(np.ones_like(self.pois_w)))
             mu = Gamma('mu', 1., 1., shape=self.pois_w.size)
             Mixture('x_obs', w,
                     [Poisson.dist(mu[0]), Poisson.dist(mu[1])],

pymc3/tests/test_model.py

@@ -5,6 +5,7 @@
 from pymc3.distributions import HalfCauchy, Normal
 from pymc3 import Potential, Deterministic
 from pymc3.theanof import generator
+from .helpers import select_by_precision
 import pytest
 
 
@@ -171,7 +172,7 @@ def true_dens():
 
         for i in range(10):
             _1, _2, _t = p1(), p2(), next(t)
-            np.testing.assert_almost_equal(_1, _t)
+            np.testing.assert_almost_equal(_1, _t, decimal=select_by_precision(float64=7, float32=2))  # Value O(-50,000)
             np.testing.assert_almost_equal(_1, _2)
         # Done
 

pymc3/tests/test_quadpotential.py

@@ -5,6 +5,7 @@
 
 from pymc3.step_methods.hmc import quadpotential
 import pymc3
+from pymc3.theanof import floatX
 import pytest
 
 
@@ -22,7 +23,7 @@ def test_elemwise_posdef2():
 
 def test_elemwise_velocity():
     scaling = np.array([1, 2, 3])
-    x_ = np.ones_like(scaling)
+    x_ = floatX(np.ones_like(scaling))
     x = tt.vector()
     x.tag.test_value = x_
     pot = quadpotential.quad_potential(scaling, True, False)
@@ -35,7 +36,7 @@ def test_elemwise_velocity():
 
 def test_elemwise_energy():
     scaling = np.array([1, 2, 3])
-    x_ = np.ones_like(scaling)
+    x_ = floatX(np.ones_like(scaling))
     x = tt.vector()
     x.tag.test_value = x_
     pot = quadpotential.quad_potential(scaling, True, False)
@@ -50,7 +51,7 @@ def test_equal_diag():
     np.random.seed(42)
     for _ in range(3):
         diag = np.random.rand(5)
-        x_ = np.random.randn(5)
+        x_ = floatX(np.random.randn(5))
         x = tt.vector()
         x.tag.test_value = x_
         pots = [
@@ -80,7 +81,7 @@ def test_equal_dense():
         cov += 10 * np.eye(5)
         inv = np.linalg.inv(cov)
         assert np.allclose(inv.dot(cov), np.eye(5))
-        x_ = np.random.randn(5)
+        x_ = floatX(np.random.randn(5))
         x = tt.vector()
         x.tag.test_value = x_
         pots = [