Small corrections

theano/gpuarray/tests/test_reduction.py

@@ -104,7 +104,7 @@ class BaseTest:
     def compute_host(self, test_tensor, axis):
         M = self.get_host_tensor()
         f = theano.function([M], [T.max(M, axis=axis), T.argmax(M, axis=axis)],
-                            name='HOST/shape:' + str(test_tensor.shape) + '/axis:' + str(axis), mode=mode_without_gpu)
+                            name='shape:' + str(test_tensor.shape) + '/axis:' + str(axis) + '/HOST', mode=mode_without_gpu)
         check_if_gpu_maxandargmax_not_in_graph(f)
         f(test_tensor)
         theano_max, theano_argmax = f(test_tensor)
@@ -115,7 +115,7 @@ class BaseTest:
     def compute_gpu(self, test_gpu_tensor, test_host_tensor, axis):
         M = self.get_gpu_tensor()
         f = theano.function([M], [T.max(M, axis=axis), T.argmax(M, axis=axis)],
-                            name='GPU/shape:' + str(test_gpu_tensor.shape) + '/axis:' + str(axis), mode=mode_with_gpu)
+                            name='shape:' + str(test_gpu_tensor.shape) + '/axis:' + str(axis) + '/GPU', mode=mode_with_gpu)
         check_if_gpu_maxandargmax_in_graph(f)
         f(test_gpu_tensor)
         theano_max, theano_argmax = f(test_gpu_tensor)

theano/tensor/basic.py

@@ -1312,7 +1312,7 @@ class MaxAndArgmax(Op):
             return [None, None]
         if len(self.axis) != 1:
             raise ValueError(('R_op supported for arg_max only for '
-                              'constant axis!'))
+                              'one axis!'))
         if self.axis[0] > 1:
             raise ValueError(('R_op supported for arg_max only when '
                               ' axis is 0 or 1'))

theano/tensor/opt_uncanonicalize.py

@@ -56,10 +56,6 @@ def local_max_and_argmax(node):
     if isinstance(node.op, T.MaxAndArgmax):
         axis = node.op.get_params(node)
         if len(node.outputs[1].clients) == 0:
-            # MaxAndArgmax support variable axis,
-            # but CAReduce support only constant axis.
-            # Axis il already constant in the new version of MaxAndArgmax.
-
             new = CAReduce(scal.maximum, axis)(node.inputs[0])
             return [new, None]