pep8

theano/tensor/nnet/tests/test_nnet.py

@@ -1124,10 +1124,10 @@ class T_CrossentropyCategorical1Hot(utt.InferShapeTester):
 
 def test_argmax_pushdown():
     x = tensor.matrix()
-    for softmax in [softmax_graph, softmax_op]:
+    for sm in [softmax_graph, softmax_op]:
         # 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)))),
+                sm(tensor.exp(tensor.tanh(sigmoid(x)))),
                 axis=-1)[1]
         fgraph = gof.FunctionGraph(
                 [x],
@@ -1144,7 +1144,7 @@ def test_argmax_pushdown():
         x = tensor.matrix()
         # 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)))),
+                sm(tensor.exp(tensor.tanh(sigmoid(x)))),
                 axis=-1)[0]
         fgraph = gof.FunctionGraph(
                 [x],
@@ -1420,12 +1420,12 @@ def test_relu():
     X = rng.randn(20, 30).astype(config.floatX)
 
     # test the base case, without custom alpha value
-    y = theano.tensor.nnet.relu(x).eval({x: X})
+    y = relu(x).eval({x: X})
     assert numpy.allclose(y, numpy.maximum(X, 0))
 
     # test for different constant alpha values (also outside of [0, 1])
     for alpha in 0, 0.3, 1, 2, -0.3, -1, -2:
-        y = theano.tensor.nnet.relu(x, alpha).eval({x: X})
+        y = relu(x, alpha).eval({x: X})
         assert numpy.allclose(y, numpy.where(X > 0, X, alpha * X))
 
     # test for variable alpha (scalar, vector and matrix)
@@ -1433,7 +1433,7 @@ def test_relu():
         # create value for alpha (correct ndim and broadcastable against X)
         A = numpy.array(rng.randn(*X.shape[::-1][:alpha.ndim][::-1]),
                         dtype=config.floatX)
-        y = theano.tensor.nnet.relu(x, alpha).eval({x: X, alpha: A})
+        y = relu(x, alpha).eval({x: X, alpha: A})
         assert numpy.allclose(y, numpy.where(X > 0, X, A * X), rtol=3e-5)