pep8

theano/sandbox/gpuarray/tests/test_nnet.py

@@ -7,6 +7,9 @@ import theano.tensor as T
 import theano.tests.unittest_tools as utt
 
 from theano.sandbox import gpuarray
+from theano.sandbox.gpuarray.nnet import (
+    GpuCrossentropySoftmaxArgmax1HotWithBias,
+    GpuCrossentropySoftmax1HotWithBiasDx)
 
 if theano.sandbox.gpuarray.pygpu is None:
     raise SkipTest("pygpu not installed")
@@ -25,8 +28,9 @@ if cuda_ndarray.cuda_available and not theano.sandbox.gpuarray.pygpu_activated:
 if not gpuarray.pygpu_activated:
     raise SkipTest("pygpu disabled")
 
-from theano.sandbox.gpuarray.nnet import (GpuCrossentropySoftmaxArgmax1HotWithBias,
-                                          GpuCrossentropySoftmax1HotWithBiasDx)
+from theano.sandbox.gpuarray.nnet import (
+    GpuCrossentropySoftmaxArgmax1HotWithBias,
+    GpuCrossentropySoftmax1HotWithBiasDx)
 
 if theano.config.mode == 'FAST_COMPILE':
     mode_with_gpu = theano.compile.mode.get_mode('FAST_RUN').including('gpuarray').excluding('gpu')
@@ -86,7 +90,7 @@ def test_GpuCrossentropySoftmaxArgmax1HotWithBias():
                                mode=mode_without_gpu)
     classify_gpu = theano.function(inputs=[y, b, dot_result],
                                    outputs=[loss, y_pred, dW],
-                                    mode=mode_with_gpu)
+                                   mode=mode_with_gpu)
     #theano.printing.debugprint(classify)
     #theano.printing.debugprint(classify_gpu)
 
@@ -94,7 +98,7 @@ def test_GpuCrossentropySoftmaxArgmax1HotWithBias():
                            T.nnet.CrossentropySoftmaxArgmax1HotWithBias)
                 for node in classify.maker.fgraph.toposort()])
     assert any([isinstance(node.op,
-                           gpuarray.nnet.GpuCrossentropySoftmaxArgmax1HotWithBias)
+                           GpuCrossentropySoftmaxArgmax1HotWithBias)
                 for node in classify_gpu.maker.fgraph.toposort()])
 
     out = classify(yy, b_values, dot_value)
@@ -149,7 +153,7 @@ def test_GpuCrossentropySoftmax1HotWithBiasDx():
     assert any([isinstance(node.op, T.nnet.CrossentropySoftmax1HotWithBiasDx)
                 for node in cpu_f.maker.fgraph.toposort()])
     assert any([isinstance(node.op,
-                           gpuarray.nnet.GpuCrossentropySoftmax1HotWithBiasDx)
+                           GpuCrossentropySoftmax1HotWithBiasDx)
                 for node in gpu_f.maker.fgraph.toposort()])
 
     cpu_out = cpu_f(softmax_output_value)
@@ -163,7 +167,7 @@ def test_GpuCrossentropySoftmax1HotWithBiasDx():
         max_i = scaled_err.argmax()
 
         print 'max err index:', max_i, max_i / batch_size,
-        print  max_i % batch_size, max_i / n_out, max_i & n_out
+        print max_i % batch_size, max_i / n_out, max_i & n_out
         print 'At that index:'
         print 'err:', scaled_err.flatten()[max_i]
         print 'absolute error:', abs_err.flatten()[max_i]
@@ -175,4 +179,4 @@ def test_GpuCrossentropySoftmax1HotWithBiasDx():
         print 'y_idx_value:', y_idx_value[max_i / n_out]
 
         assert False, "numpy.allclose(cpu_out, gpu_out, rtol=%s, atol=%s)" % (
-                rtol, atol)
+            rtol, atol)