Disable DebugMode.check_isfinite when we know there are inf

theano/gpuarray/tests/test_elemwise.py

 from __future__ import absolute_import, print_function, division
+from copy import copy
+from unittest import TestCase
+
 import numpy as np
 import scipy.special
 
 import theano
 from theano import scalar, gof, tensor
-from unittest import TestCase
+from theano.compile import DebugMode
 from theano.tests.unittest_tools import SkipTest, assert_allclose
 
 from theano.tensor.tests import test_elemwise
@@ -79,6 +82,19 @@ class TestMathErrorFunctions(TestCase):
             self.expected_erfinv_outputs[dtype] = scipy.special.erfinv(numpy_array)
             self.expected_erfcinv_outputs[dtype] = scipy.special.erfcinv(numpy_array)
 
+        # Since there are infinite values, we need to disable that check
+        # in DebugMode if needed
+        if isinstance(mode_with_gpu, DebugMode):
+            self.mode_with_gpu = copy(mode_with_gpu)
+            self.mode_with_gpu.check_isfinite = False
+        else:
+            self.mode_with_gpu = mode_with_gpu
+        if isinstance(mode_without_gpu, DebugMode):
+            self.mode_without_gpu = copy(mode_without_gpu)
+            self.mode_without_gpu.check_isfinite = False
+        else:
+            self.mode_without_gpu = mode_without_gpu
+
     def check_gpu_scalar_op(self, theano_function, scalar_optype):
         for node in theano_function.maker.fgraph.apply_nodes:
             if isinstance(node.op, GpuElemwise) and isinstance(node.op.scalar_op, scalar_optype):
@@ -90,8 +106,8 @@ class TestMathErrorFunctions(TestCase):
         for dtype in self.dtypes:
             vector = theano.tensor.vector(dtype=dtype)
             output = theano.tensor.erfinv(vector)
-            f_host = theano.function([vector], output, name='HOST/erfinv/' + dtype, mode=mode_without_gpu)
-            f_gpu = theano.function([vector], output, name='GPU/erfinv/' + dtype, mode=mode_with_gpu)
+            f_host = theano.function([vector], output, name='HOST/erfinv/' + dtype, mode=self.mode_without_gpu)
+            f_gpu = theano.function([vector], output, name='GPU/erfinv/' + dtype, mode=self.mode_with_gpu)
             assert len([n for n in f_host.maker.fgraph.apply_nodes if isinstance(n.op, GpuElemwise)]) == 0
             if not theano.config.device.startswith('opencl'):
                 assert self.check_gpu_scalar_op(f_gpu, GpuErfinv), \
@@ -108,8 +124,8 @@ class TestMathErrorFunctions(TestCase):
         for dtype in self.dtypes:
             vector = theano.tensor.vector(dtype=dtype)
             output = theano.tensor.erfcinv(vector)
-            f_host = theano.function([vector], output, name='HOST/erfcinv/' + dtype, mode=mode_without_gpu)
-            f_gpu = theano.function([vector], output, name='GPU/erfcinv/' + dtype, mode=mode_with_gpu)
+            f_host = theano.function([vector], output, name='HOST/erfcinv/' + dtype, mode=self.mode_without_gpu)
+            f_gpu = theano.function([vector], output, name='GPU/erfcinv/' + dtype, mode=self.mode_with_gpu)
             assert len([n for n in f_host.maker.fgraph.apply_nodes if isinstance(n.op, GpuElemwise)]) == 0
             if not theano.config.device.startswith('opencl'):
                 assert self.check_gpu_scalar_op(f_gpu, GpuErfcinv), \