Merge pull request #757 from jaswanthbjk/inplace_fix

fix for issue #741

torch_points3d/modules/MinkowskiEngine/api_modules.py

@@ -76,9 +76,9 @@ def __init__(self, input_nc, output_nc, convolution, dimension=3):
     def forward(self, x):
         out = self.block(x)
         if self.downsample:
-            out += self.downsample(x)
+            out = out + self.downsample(x)
         else:
-            out += x
+            out = out + x
         return out
 
 
@@ -153,9 +153,9 @@ def __init__(self, input_nc, output_nc, convolution, dimension=3, reduction=4):
     def forward(self, x):
         out = self.block(x)
         if self.downsample:
-            out += self.downsample(x)
+            out = out + self.downsample(x)
         else:
-            out += x
+            out = out + x
         return out
 
 
@@ -204,9 +204,9 @@ def forward(self, x):
         out = self.block(x)
         out = self.SE(out)
         if self.downsample:
-            out += self.downsample(x)
+            out = out + self.downsample(x)
         else:
-            out += x
+            out = out + x
         return out
 
 
@@ -223,9 +223,9 @@ def forward(self, x):
         out = self.block(x)
         out = self.SE(out)
         if self.downsample:
-            out += self.downsample(x)
+            out = out + self.downsample(x)
         else:
-            out += x
+            out = out + x
         return out
 
 

torch_points3d/modules/MinkowskiEngine/modules.py

@@ -52,7 +52,7 @@ def forward(self, x):
         if self.downsample is not None:
             residual = self.downsample(x)
 
-        out += residual
+        out = out + residual
         out = self.relu(out)
 
         return out
@@ -96,7 +96,7 @@ def forward(self, x):
         if self.downsample is not None:
             residual = self.downsample(x)
 
-        out += residual
+        out = out + residual
         out = self.relu(out)
 
         return out
@@ -315,7 +315,7 @@ def forward(self, x):
         if self.downsample is not None:
             residual = self.downsample(x)
 
-        out += residual
+        out = out + residual
         out = self.relu(out)
 
         return out
@@ -360,7 +360,7 @@ def forward(self, x):
         if self.downsample is not None:
             residual = self.downsample(x)
 
-        out += residual
+        out = out + residual
         out = self.relu(out)
 
         return out

torch_points3d/modules/MinkowskiEngine/res16unet.py

@@ -46,7 +46,7 @@ def forward(self, x):
         if self.downsample is not None:
             residual = self.downsample(x)
 
-        out += residual
+        out = out + residual
         out = self.relu(out)
 
         return out
@@ -109,7 +109,7 @@ def forward(self, x):
         if self.downsample is not None:
             residual = self.downsample(x)
 
-        out += residual
+        out = out + residual
         out = self.relu(out)
 
         return out

torch_points3d/modules/PPNet/blocks.py

@@ -288,7 +288,7 @@ def forward(self, data, precomputed=None, **kwargs):
             shortcut_x = torch.max(neighborhood_features, dim=1, keepdim=False)[0]
 
         shortcut = self.shortcut_op(shortcut_x)
-        output.x += shortcut
+        output.x = output.x + shortcut
         output.x = self.activation(output.x)
         return output
 

torch_points3d/modules/SparseConv3d/modules.py

@@ -44,9 +44,9 @@ def __init__(self, input_nc, output_nc, convolution):
     def forward(self, x):
         out = self.block(x)
         if self.downsample:
-            out += self.downsample(x)
+            out = out + self.downsample(x)
         else:
-            out += x
+            out = out + x
         return out
 
 
@@ -94,9 +94,9 @@ def __init__(self, input_nc, output_nc, convolution, reduction=4):
     def forward(self, x):
         out = self.block(x)
         if self.downsample:
-            out += self.downsample(x)
+            out = out + self.downsample(x)
         else:
-            out += x
+            out = out + x
         return out