legacy fixes (pytorch#287)

Author: szagoruyko

torch/legacy/nn/ConcatTable.py

@@ -35,12 +35,15 @@ def _map_list(self, l1, l2, f):
             del l1[i]
         return l1
 
-    def _backward(self, method, input, gradOutput, scale):
+    def _backward(self, method, input, gradOutput, scale=1):
         isTable = isinstance(input, list)
         wasTable = isinstance(self.gradInput, list)
         if isTable:
             for i, module in enumerate(self.modules):
-                currentGradInput = getattr(module, method)(input, gradOutput[i], scale)
+                if method == 'updateGradInput':
+                    currentGradInput = module.updateGradInput(input, gradOutput[i])
+                elif method == 'backward':
+                    currentGradInput = module.backward(input, gradOutput[i], scale)
                 if not isinstance(currentGradInput, list):
                     raise RuntimeError("currentGradInput is not a table!")
 
@@ -68,7 +71,10 @@ def fn(l, i, v):
         else:
             self.gradInput = self.gradInput if not wasTable else input.clone()
             for i, module in enumerate(self.modules):
-                currentGradInput = getattr(module, method)(input, gradOutput[i], scale)
+                if method == 'updateGradInput':
+                    currentGradInput = module.updateGradInput(input, gradOutput[i])
+                elif method == 'backward':
+                    currentGradInput = module.backward(input, gradOutput[i], scale)
                 if i == 0:
                     self.gradInput.resize_as_(currentGradInput).copy_(currentGradInput)
                 else:

torch/utils/serialization/read_lua_file.py

@@ -344,6 +344,7 @@ def ensure_type(obj, type_map):
 ensure_attr('ClassNLLCriterion', 'weights')
 ensure_attr('ParallelCriterion', 'repeatTarget')
 ensure_attr('MultiMarginCriterion', 'weights')
+ensure_attr('SpatialConvolution', 'bias', 'finput', 'fgradInput', 'gradWeight', 'gradBias')
 attr_map('ReLU', {'val': 'value'})
 attr_map('Threshold', {'val': 'value'})
 attr_map('Unsqueeze', {'pos': 'dim'})