Fix style and import

chainer/functions/connection/convolution_2d.py

@@ -411,4 +411,5 @@ def convolution_2d(x, W, b=None, stride=1, pad=0, cover_all=False, **kwargs):
         args = x, W
     else:
         args = x, W, b
-    return fnode.apply(args)[0]
+    y, = fnode.apply(args)
+    return y

chainer/functions/connection/deconvolution_2d.py

@@ -4,7 +4,7 @@
 from chainer import configuration
 from chainer import cuda
 from chainer import function_node
-from chainer import functions as F
+import chainer.functions
 from chainer.functions.connection import convolution_2d
 from chainer.utils import argument
 from chainer.utils import conv
@@ -216,7 +216,7 @@ def backward(self, indexes, grad_outputs):
         if 0 in indexes:
             if self.cover_all is None:
                 self._set_cover_all(x, W)
-            gx = F.convolution_2d(
+            gx = chainer.functions.convolution_2d(
                 gy, W, stride=(self.sy, self.sx), pad=(self.ph, self.pw),
                 cover_all=self.cover_all)
             ret.append(gx)
@@ -226,7 +226,7 @@ def backward(self, indexes, grad_outputs):
             gW, = convolution_2d.Convolution2DGradW(self).apply((gy, x))
             ret.append(gW)
         if 2 in indexes:
-            gb = F.sum(gy, axis=(0, 2, 3))
+            gb = chainer.functions.sum(gy, axis=(0, 2, 3))
             ret.append(gb)
 
         return ret
@@ -347,7 +347,9 @@ def deconvolution_2d(x, W, b=None, stride=1, pad=0, outsize=None, **kwargs):
     argument.assert_kwargs_empty(kwargs)
 
     func = Deconvolution2DFunction(stride, pad, outsize)
-    args = x, W
-    if b is not None:
-        args += b,
-    return func.apply(args)[0]
+    if b is None:
+        args = x, W
+    else:
+        args = x, W, b
+    y, = func.apply(args)
+    return y