[pycaffe] pep8 coord map

python/caffe/coord_map.py

@@ -3,24 +3,28 @@
 from caffe import layers as L
 
 PASS_THROUGH_LAYERS = ['AbsVal', 'BatchNorm', 'Bias', 'BNLL', 'Dropout',
-        'Eltwise', 'ELU', 'Log', 'LRN', 'Exp', 'MVN', 'Power', 'ReLU', 'PReLU',
-        'Scale', 'Sigmoid', 'Split', 'TanH', 'Threshold']
+                       'Eltwise', 'ELU', 'Log', 'LRN', 'Exp', 'MVN', 'Power',
+                       'ReLU', 'PReLU', 'Scale', 'Sigmoid', 'Split', 'TanH',
+                       'Threshold']
+
 
 def conv_params(fn):
     params = fn.params.get('convolution_param', fn.params)
     axis = params.get('axis', 1)
     ks = np.array(params['kernel_size'], ndmin=1)
     dilation = np.array(params.get('dilation', 1), ndmin=1)
     assert len({'pad_h', 'pad_w', 'kernel_h', 'kernel_w', 'stride_h',
-        'stride_w'} & set(fn.params)) == 0, \
-                'cropping does not support legacy _h/_w params'
+                'stride_w'} & set(fn.params)) == 0, \
+        'cropping does not support legacy _h/_w params'
     return (axis, np.array(params.get('stride', 1), ndmin=1),
             (ks - 1) * dilation + 1,
             np.array(params.get('pad', 0), ndmin=1))
 
+
 class UndefinedMapException(Exception):
     pass
 
+
 def coord_map(fn):
     if fn.type_name in ['Convolution', 'Pooling', 'Im2col']:
         axis, stride, ks, pad = conv_params(fn)
@@ -36,9 +40,11 @@ def coord_map(fn):
     else:
         raise UndefinedMapException
 
+
 class AxisMismatchException(Exception):
     pass
 
+
 def compose((ax1, a1, b1), (ax2, a2, b2)):
     if ax1 is None:
         ax = ax2
@@ -48,9 +54,11 @@ def compose((ax1, a1, b1), (ax2, a2, b2)):
         raise AxisMismatchException
     return ax, a1 * a2, a1 * b2 + b1
 
+
 def inverse((ax, a, b)):
     return ax, 1 / a, -b / a
 
+
 def coord_map_from_to(top_from, top_to):
     # We need to find a common ancestor of top_from and top_to.
     # We'll assume that all ancestors are equivalent here (otherwise the graph
@@ -84,12 +92,16 @@ def coord_map_from_to(top_from, top_to):
             continue
 
     # if we got here, we did not find a blob in common
-    raise RuntimeError, 'Could not compute map between tops; are they connected ' \
-            'by spatial layers?'
+    raise RuntimeError('Could not compute map between tops; are they '
+                       'connected by spatial layers?')
+
 
 def crop(top_from, top_to):
     ax, a, b = coord_map_from_to(top_from, top_to)
     assert (a == 1).all(), 'scale mismatch on crop (a = {})'.format(a)
     assert (b <= 0).all(), 'cannot crop negative width (b = {})'.format(b)
-    assert (np.round(b) == b).all(), 'cannot crop noninteger width (b = {})'.format(b)
-    return L.Crop(top_from, top_to, crop_param=dict(axis=ax, crop=list(-np.round(b).astype(int))))
+    assert (np.round(b) == b).all(),
+    'cannot crop noninteger width (b = {})'.format(b)
+    return L.Crop(top_from, top_to,
+                  crop_param=dict(axis=ax,
+                                  crop=list(-np.round(b).astype(int))))