Explicitly use 'axis' parameter in more calls to min, max, etc.

theano/sandbox/cuda/tests/test_nnet.py

@@ -50,7 +50,7 @@ def test_GpuCrossentropySoftmaxArgmax1HotWithBias():
     dot_value = numpy.asarray(numpy.dot(xx, W_values),dtype='float32')
 
     p_y_given_x = T.nnet.softmax(dot_result+b)
-    y_pred = T.argmax(p_y_given_x)
+    y_pred = T.argmax(p_y_given_x, axis=-1)
     loss = -T.mean(T.log(p_y_given_x)[T.arange(y.shape[0]), y])
     dW = T.grad(loss,W)
     classify = theano.function( inputs = [x,y,b,W,dot_result], outputs = [loss,y_pred,dW],

theano/tensor/nnet/tests/test_nnet.py

@@ -808,7 +808,9 @@ def test_argmax_pushdown():
     x = tensor.dmatrix()
 
     #test that the max_and_argmax is pushed down if the max is not used
-    out = tensor.max_and_argmax(softmax(tensor.exp(tensor.tanh(sigmoid(x)))))[1]
+    out = tensor.max_and_argmax(
+            softmax(tensor.exp(tensor.tanh(sigmoid(x)))),
+            axis=-1)[1]
     env = gof.Env(
             [x],
             [out])
@@ -824,7 +826,9 @@ def test_argmax_pushdown():
     assert str(env.toposort()[1].op) == 'OutputGuard'
     x = tensor.dmatrix()
     #test that the max_and_argmax is not pushed down if the max is used
-    out = tensor.max_and_argmax(softmax(tensor.exp(tensor.tanh(sigmoid(x)))))[0]
+    out = tensor.max_and_argmax(
+            softmax(tensor.exp(tensor.tanh(sigmoid(x)))),
+            axis=-1)[0]
     env = gof.Env(
             [x],
             [out])
@@ -847,7 +851,7 @@ def test_argmax_pushdown_bias():
     x = tensor.dmatrix()
     b = tensor.dvector()
 
-    out = tensor.argmax(softmax_with_bias(x, b))
+    out = tensor.argmax(softmax_with_bias(x, b), axis=-1)
     env = gof.Env(
             [x,b],
             [out])
@@ -867,7 +871,7 @@ def test_argmax_pushdown_bias():
     x = tensor.dmatrix()
     b = tensor.dvector()
 
-    out = tensor.max_and_argmax(softmax_with_bias(x, b))[0]
+    out = tensor.max_and_argmax(softmax_with_bias(x, b), axis=-1)[0]
     env = gof.Env(
             [x,b],
             [out])

theano/tensor/signal/tests/test_downsample.py

@@ -122,7 +122,11 @@ class TestDownsampleFactorMax(unittest.TestCase):
                 c_val = function([images], c)(imval)
 
                 g = tensor.grad(c, images)
-                g_val = function([images], [g.shape, tensor.min(tensor.min(tensor.min(g))), tensor.max(tensor.max(tensor.max(g)))])(imval)
+                g_val = function([images],
+                        [g.shape,
+                            tensor.min(g, axis=(0,1,2)),
+                            tensor.max(g, axis=(0,1,2))]
+                        )(imval)
 
 #removed as already tested in test_max_pool_2d_2D
 #This make test in debug mode too slow.