fix NetworkInNetwork on CPU; tidy

sparseconvnet/SCN/CPU/NetworkInNetwork.cpp

@@ -17,7 +17,7 @@ double cpu_NetworkInNetwork_updateOutput(/*float*/ at::Tensor input_features,
     output_features.copy_(bias);
   else
     output_features.zero_();
-  output_features.addmm(input_features, weight);
+  output_features.addmm_(input_features, weight);
   return nActive * input_nPlanes * output_nPlanes;
 }
 template <typename T>

sparseconvnet/__init__.py

@@ -32,19 +32,4 @@ from .spectral_norm import spectral_norm
 from .submanifoldConvolution import SubmanifoldConvolution, ValidConvolution
 from .tables import *
 from .unPooling import UnPooling
-from .utils import appendSparseConvTensors, AddCoords
-
-def concatenate_feature_planes(input):
-    output = SparseConvNetTensor()
-    output.metadata = input[0].metadata
-    output.spatial_size = input[0].metadata
-    output.features = torch.cat([i.features for i in input], 1)
-    return output
-
-
-def add_feature_planes(input):
-    output = SparseConvNetTensor()
-    output.metadata = input[0].metadata
-    output.spatial_size = input[0].metadata
-    output.features = sum([i.features for i in input])
-    return output
+from .utils import append_tensors, AddCoords, add_feature_planes, concatenate_feature_planes

sparseconvnet/utils.py

@@ -49,7 +49,23 @@ def threadDatasetIterator(d):
     return iterator
 
 
-def appendSparseConvTensors(tensors):
+
+def concatenate_feature_planes(input):
+    output = SparseConvNetTensor()
+    output.metadata = input[0].metadata
+    output.spatial_size = input[0].spatial_size
+    output.features = torch.cat([i.features for i in input], 1)
+    return output
+
+
+def add_feature_planes(input):
+    output = SparseConvNetTensor()
+    output.metadata = input[0].metadata
+    output.spatial_size = input[0].spatial_size
+    output.features = sum([i.features for i in input])
+    return output
+
+def append_tensors(tensors):
     spatial_size=tensors[0].spatial_size
     dimension=len(spatial_size)
     x=SparseConvNetTensor(