Revert 4c71de43057f now that numpy+floatX is not the default.

theano/sandbox/cuda/tests/test_basic_ops.py

@@ -318,11 +318,11 @@ def test_elemwise3():
     a = tcn.shared_constructor(theano._asarray(numpy.random.rand(*shape), dtype='float32'), 'a')
     b = tensor.fvector()
     print b.type
-    fone = tensor.constant(1, dtype='float32')
-    print (fone + b).type
-    print (fone + b**a).type
-    print tensor.exp((fone + b**a)).type
-    f = pfunc([b], [], updates=[(a, (a+b).dimshuffle([2,0,3,1]) * tensor.exp(fone +
+    print tensor.constant(1).type
+    print (1 + b).type
+    print (1 + b**a).type
+    print tensor.exp((1 + b**a)).type
+    f = pfunc([b], [], updates=[(a, (a+b).dimshuffle([2,0,3,1]) * tensor.exp(1 +
         b**a).dimshuffle([2,0,3,1]))], mode=mode_with_gpu)
     has_elemwise = False
     for i, node in enumerate(f.maker.env.toposort()):

theano/sandbox/cuda/tests/test_opt.py

@@ -144,8 +144,7 @@ def test_opt_gpujoin_joinvectors_elemwise_then_minusone():
 def test_print_op():
     """ Test that print ops don't block gpu optimization"""
     b = tensor.fmatrix()
-    ftwo = tensor.constant(2, dtype='float32')
-    f = theano.function([b],theano.printing.Print()(b) * ftwo, mode=mode_with_gpu)
+    f = theano.function([b],theano.printing.Print()(b)*2, mode=mode_with_gpu)
     #theano.printing.debugprint(f)
     #print f.maker.env.toposort()
 #[GpuFromHost(<TensorType(float32, matrix)>), <theano.printing.Print object at 0x3581210>(GpuFromHost.0), GpuElemwise{mul}(CudaNdarray{[[ 2.]]}, <theano.printing.Print object at 0x3581210>.0), HostFromGpu(GpuElemwise{mul}.0)]