Fix DCNv3 version compatibility (#108)

classification/ops_dcnv3/functions/dcnv3_func.py

@@ -15,6 +15,9 @@ from torch.autograd.function import once_differentiable
 from torch.cuda.amp import custom_bwd, custom_fwd
 import DCNv3
 
+import pkg_resources
+dcn_version = float(pkg_resources.get_distribution('DCNv3').version)
+
 
 class DCNv3Function(Function):
     @staticmethod
@@ -38,15 +41,16 @@ class DCNv3Function(Function):
         ctx.im2col_step = im2col_step
         ctx.remove_center = remove_center
 
-        kwargs = {}
-        if remove_center:
-            kwargs['remove_center'] = remove_center
-
-        output = DCNv3.dcnv3_forward(
+        args = [
             input, offset, mask, kernel_h,
             kernel_w, stride_h, stride_w, pad_h,
             pad_w, dilation_h, dilation_w, group,
-            group_channels, offset_scale, ctx.im2col_step, **kwargs)
+            group_channels, offset_scale, ctx.im2col_step
+        ]
+        if remove_center or dcn_version > 1.0:
+            args.append(remove_center)
+
+        output = DCNv3.dcnv3_forward(*args)
         ctx.save_for_backward(input, offset, mask)
 
         return output
@@ -57,16 +61,17 @@ class DCNv3Function(Function):
     def backward(ctx, grad_output):
         input, offset, mask = ctx.saved_tensors
 
-        kwargs = {}
-        if ctx.remove_center:
-            kwargs['remove_center'] = ctx.remove_center
-
-        grad_input, grad_offset, grad_mask = \
-            DCNv3.dcnv3_backward(
+        args = [
             input, offset, mask, ctx.kernel_h,
             ctx.kernel_w, ctx.stride_h, ctx.stride_w, ctx.pad_h,
             ctx.pad_w, ctx.dilation_h, ctx.dilation_w, ctx.group,
-                ctx.group_channels, ctx.offset_scale, grad_output.contiguous(), ctx.im2col_step, **kwargs)
+            ctx.group_channels, ctx.offset_scale, grad_output.contiguous(), ctx.im2col_step
+        ]
+        if ctx.remove_center or dcn_version > 1.0:
+            args.append(ctx.remove_center)
+
+        grad_input, grad_offset, grad_mask = \
+            DCNv3.dcnv3_backward(*args)
 
         return grad_input, grad_offset, grad_mask, \
             None, None, None, None, None, None, None, None, None, None, None, None, None