Implement all missing case of GPU min/max that was supported by GPU sum.

This mean the not available case 1010, 1011 and 0111. The following case where implemented with reshape for min/max, but not for sum:110, 001, 0011, 100.

Implement all missing case of GPU min/max that was supported by GPU sum.
1b3c8f1b · Frederic · 827cb8cc · 1b3c8f1b · 1b3c8f1b
--- a/theano/sandbox/cuda/basic_ops.py
+++ b/theano/sandbox/cuda/basic_ops.py
--- a/theano/sandbox/cuda/tests/test_basic_ops.py
+++ b/theano/sandbox/cuda/tests/test_basic_ops.py
@@ -124,21 +124,6 @@ def test_careduce():
            op = careduce_op(scalar_op, axis=pattern)
            pat = tensor_pattern_to_gpu_pattern(shape, pattern)
-            #GpuCAReduce{maximum/minimum} support only those patterns
-            if scalar_op in [theano.scalar.maximum,
-                             theano.scalar.minimum] and pat not in [
-                                 (1,), (1, 1), (0, 1), (1, 0),
-                                 (0, 1, 0), (0, 1, 1), (1, 1, 1),
-                                 (1, 0, 0, 0), (0, 1, 0, 0),
-                                 (0, 0, 1, 0), (0, 0, 0, 1),
-                                 (1, 1, 1, 1), (1, 1, 1, 1, 1),
-                                 (0, 0, 1), (0, 1, 0), (1, 0, 0), (1, 1, 0),
-                                 (0, 0, 1, 1), # by reshape
-                                 # (0, 1, 0, 1), #not supported for max/min
-                                 (0, 1, 1, 1), # by reshape
-                                 #(1, 0, 1, 1) #not supported for max/min
-                             ]:
-                continue
            a = tensor.TensorType('float32', (False,) * len(shape))()
            b = op(a)
@@ -206,11 +191,6 @@ def test_careduce():
                               ((5,4,3,2),[0,1,2,3]), ((5,4,3,2),[0,2,3])]:
            op = careduce_op(scalar_op, axis=pattern)
            pat = tensor_pattern_to_gpu_pattern(shape, pattern)
-            #GpuCAReduce{maximum/minimum} support only those patterns
-            if scalar_op in [theano.scalar.maximum,
-                             theano.scalar.minimum] and pat not in [
-                                 (0, 1), (0, 1, 1), (0, 1, 1), (1, 0)]:
-                continue
            a = tensor.TensorType('float32', (False,) * len(shape))()
            dim_pattern = range(len(shape))
@@ -243,11 +223,6 @@ def test_careduce():
                               ((5,4,3,2),[0,1,2,3]), ((5,4,3,2),[0,2,3])]:
            op = careduce_op(scalar_op, axis=pattern)
            pat = tensor_pattern_to_gpu_pattern(shape, pattern)
-            #GpuCAReduce{maximum/minimum} support only those patterns
-            if scalar_op in [theano.scalar.maximum,
-                             theano.scalar.minimum] and pat not in [
-                                 (0, 1), (0, 1, 1), (0, 1, 1), (1, 0)]:
-                continue
            shape = numpy.asarray(shape) * 2
            a = tensor.TensorType('float32', (False,) * len(shape))()