Fixed test when cast_policy == numpy+floatX and floatX == float64

theano/sandbox/cuda/tests/test_opt.py

@@ -5,7 +5,7 @@ import numpy
 from nose.plugins.skip import SkipTest
 
 from theano.compile.pfunc import pfunc
-from theano import tensor
+from theano import config, tensor
 import theano
 
 import theano.sandbox.cuda as cuda
@@ -35,18 +35,28 @@ def test_no_shared_var_graph():
     assert numpy.any(isinstance(x.op,cuda.HostFromGpu) for x in l)
 
 def test_int_pow():
-    a = CudaNdarrayType([False])()
+    # This is to ensure that '4' does not upcast to float64.
+    if config.cast_policy == 'numpy+floatX':
+        floatX_backup = config.floatX
+        config.floatX = 'float32'
 
-    f = theano.function([a], (a*4).sum(), mode=mode_with_gpu)
+    try:
+        a = CudaNdarrayType([False])()
 
-    op_names = [n.op.__class__.__name__ for n in f.maker.env.toposort()]
-    assert op_names == ['GpuSum', 'GpuElemwise', 'HostFromGpu']
+        f = theano.function([a], (a*4).sum(), mode=mode_with_gpu)
 
-    f = theano.function([a], tensor.pow(a,4).sum(), mode=mode_with_gpu)
-    op_names = [n.op.__class__.__name__ for n in f.maker.env.toposort()]
-    assert op_names == ['GpuElemwise', 'GpuSum', 'HostFromGpu']
+        op_names = [n.op.__class__.__name__ for n in f.maker.env.toposort()]
+        assert op_names == ['GpuSum', 'GpuElemwise', 'HostFromGpu']
 
-    #theano.printing.debugprint(f)
+        f = theano.function([a], tensor.pow(a,4).sum(), mode=mode_with_gpu)
+        op_names = [n.op.__class__.__name__ for n in f.maker.env.toposort()]
+        assert op_names == ['GpuElemwise', 'GpuSum', 'HostFromGpu']
+
+        #theano.printing.debugprint(f)
+
+    finally:
+        if config.cast_policy == 'numpy+floatX':
+            config.floatX = floatX_backup
 
 def test_gpualloc():
     '''