chore(megbrain): fix megskull cnn/img opr compatiblity

    for add convolutionv2 param

GitOrigin-RevId: 9d0cf55ef46448c8d26682a8d365612880eb1321

src/opr/impl/dnn/dnn.oprdecl

@@ -65,7 +65,7 @@ decl_opr('MaskConvolution',
          params=[('param', 'Convolution')],
          desc=('batched mask conv on channeled 2D images, mask is correspoding '
                'to output'),
-         version=1)
+         version=2)
 
 decl_opr('MaskPropagate',
          inputs=[Doc('src',
@@ -102,10 +102,11 @@ decl_opr('Local',
                      'convolution kernel in '
                      '(out row, out col, in channel, '
                      'kern row, kern col, out channel) format')],
-         params='ConvolutionV0',
+         params='Convolution',
          desc='batched convolution on channeled 2D images, but kernels are '
-         'not shared across different output positions')
+         'not shared across different output positions', version=2)
 
+"""
 decl_opr('Local',
          pyname='local_v1',
          inputs=[Doc('src',
@@ -118,6 +119,7 @@ decl_opr('Local',
          desc='batched convolution on channeled 2D images, but kernels are '
          'not shared across different output positions',
          version=1)
+"""
 
 decl_opr('GroupLocal',
          inputs=[Doc('src',
@@ -129,7 +131,7 @@ decl_opr('GroupLocal',
          params=[('param', 'Convolution')],
          desc='batched convolution on groupped channeled 2D images, but '
          'kernels are not shared across different output positions',
-         version=1)
+         version=2)
 
 decl_opr('LRN',
          inputs=['src'],
@@ -280,7 +282,7 @@ decl_opr('DeformableConvForward',
                  Doc('mask', 'deformable mask in (batch, deformable group * filter row * filter col, output row, output col) format')],
          params=[('param', 'Convolution'), ('execution_policy', 'ExecutionPolicy')],
          desc=Doc(None, r""" Apply a deformable convolution to input tensor and filter tensor. The offset tensor will adjust the position of each grid of a convolution filter. The mask tensor will be applied to the deformed input tensor. """),
-         has_out_dtype=True)
+         has_out_dtype=True, version=1)
 
 decl_opr('DeformablePSROIPoolingForward',
          pyname='deformable_psroi_pooling',

src/opr/impl/dnn/dnn.sereg.h

@@ -514,19 +514,19 @@ MGB_SEREG_OPR(ConvolutionBackwardFilterV2, 0);
 MGB_SEREG_OPR(Images2Neibs, 1);
 MGB_SEREG_OPR(Images2NeibsBackward, 2);
 
-using LocalV1 = Local;
-using LocalBackwardDataV1 = LocalBackwardData;
-using LocalBackwardFilterV1 = LocalBackwardFilter;
-MGB_SEREG_OPR(LocalV1, 2);
-MGB_SEREG_OPR(LocalBackwardDataV1, 3);
-MGB_SEREG_OPR(LocalBackwardFilterV1, 3);
-
-using GroupLocalV1 = GroupLocal;
-using GroupLocalBackwardDataV1 = GroupLocalBackwardData;
-using GroupLocalBackwardFilterV1 = GroupLocalBackwardFilter;
-MGB_SEREG_OPR(GroupLocalV1, 2);
-MGB_SEREG_OPR(GroupLocalBackwardDataV1, 3);
-MGB_SEREG_OPR(GroupLocalBackwardFilterV1, 3);
+using LocalV2 = Local;
+using LocalBackwardDataV2 = LocalBackwardData;
+using LocalBackwardFilterV2 = LocalBackwardFilter;
+MGB_SEREG_OPR(LocalV2, 2);
+MGB_SEREG_OPR(LocalBackwardDataV2, 3);
+MGB_SEREG_OPR(LocalBackwardFilterV2, 3);
+
+using GroupLocalV2 = GroupLocal;
+using GroupLocalBackwardDataV2 = GroupLocalBackwardData;
+using GroupLocalBackwardFilterV2 = GroupLocalBackwardFilter;
+MGB_SEREG_OPR(GroupLocalV2, 2);
+MGB_SEREG_OPR(GroupLocalBackwardDataV2, 3);
+MGB_SEREG_OPR(GroupLocalBackwardFilterV2, 3);
 
 MGB_SEREG_OPR(LRN, 1);
 MGB_SEREG_OPR(LRNBackward, 3);
@@ -542,8 +542,8 @@ MGB_SEREG_OPR(AdaptivePoolingBackwardV1, 4);
 MGB_SEREG_OPR(ROIPooling, 3);
 MGB_SEREG_OPR(ROIPoolingBackward, 4);
 
-using MaskConvolutionV1 = MaskConvolution;
-MGB_SEREG_OPR(MaskConvolutionV1, 3);
+using MaskConvolutionV2 = MaskConvolution;
+MGB_SEREG_OPR(MaskConvolutionV2, 3);
 MGB_SEREG_OPR(MaskPropagate, 1);
 
 MGB_SEREG_OPR(Convolution3D, 0);
@@ -567,9 +567,12 @@ using ROIAlignV1 = ROIAlign;
 using ROIAlignBackwardV1 = ROIAlignBackward;
 MGB_SEREG_OPR(ROIAlignV1, 2);
 MGB_SEREG_OPR(ROIAlignBackwardV1, 4);
-MGB_SEREG_OPR(DeformableConvForward, 0);
-MGB_SEREG_OPR(DeformableConvBackwardData, 0);
-MGB_SEREG_OPR(DeformableConvBackwardFilter, 0);
+using DeformableConvForwardV1 = DeformableConvForward;
+using DeformableConvBackwardDataV1 = DeformableConvBackwardData;
+using DeformableConvBackwardFilterV1 = DeformableConvBackwardFilter;
+MGB_SEREG_OPR(DeformableConvForwardV1, 0);
+MGB_SEREG_OPR(DeformableConvBackwardDataV1, 0);
+MGB_SEREG_OPR(DeformableConvBackwardFilterV1, 0);
 
 MGB_SEREG_OPR(DeformablePSROIPoolingForward, 3);
 MGB_SEREG_OPR(DeformablePSROIPoolingBackward, 5);

src/opr/impl/imgproc.oprdecl

@@ -24,8 +24,8 @@ decl_opr(
     params='WarpPerspective',
     desc='like :func:`warp_perspective`, but the **mat** param does not have '
     'to have the same batch size as **src**; instead, **mat_idx** specifies '
-    'the batch number of each matrix in **mat**'
-)
+    'the batch number of each matrix in **mat**',
+    version=2)
 
 decl_opr('Rotate',
     inputs=[
@@ -111,7 +111,7 @@ decl_raw_opr(
         'assert not kwargs, "extra kwargs: {}".format(kwargs)',
         'all_params = []',
         'all_params.append(param.serialize())',
-        'output = _mgb._create_opr("DctChannelSelect", all_inputs, all_params, config)',
+        'output = _mgb._create_opr("DctChannelSelectV1", all_inputs, all_params, config)',
     ],
     has_out_dtype=True,
     desc='DctChannelSelect do DCT with channel select'