fix: change ops.pad input format which changed in mindspore in Nov 2022

mindcv/models/halonet.py

@@ -150,10 +150,10 @@ def rel_logits_1d(q, rel_k, permute_mask):
     x = msnp.tensordot(q, rel_k, axes=1)
     x = ops.reshape(x, (-1, W, rel_size))
     # pad to shift from relative to absolute indexing
-    x_pad = ops.pad(x, paddings=((0, 0), (0, 0), (0, 1)))
+    x_pad = ops.pad(x, padding=(0, 1))
     x_pad = ops.flatten(x_pad)
     x_pad = ops.expand_dims(x_pad, 1)
-    x_pad = ops.pad(x_pad, paddings=((0, 0), (0, 0), (0, rel_size - W)))
+    x_pad = ops.pad(x_pad, padding=(0, rel_size - W))
     x_pad = ops.squeeze(x_pad, axis=())
     # reshape adn slice out the padded elements
     x_pad = ops.reshape(x_pad, (-1, W+1, rel_size))

mindcv/models/repvgg.py

@@ -145,7 +145,7 @@ def get_equivalent_kernel_bias(self):
     def _pad_1x1_to_3x3_tensor(self, kernel1x1):
         if kernel1x1 is None:
             return 0
-        return ops.pad(kernel1x1, ((1, 1), (1, 1)))
+        return ops.pad(kernel1x1, (1, 1, 1, 1))
 
     def _fuse_bn_tensor(self, branch):
         if branch is None:

mindcv/models/volo.py

@@ -151,7 +151,7 @@ def construct(self, x: Tensor) -> Tensor:
 
         h = int((H - 1) / self.stride + 1)
         w = int((W - 1) / self.stride + 1)
-        v = ops.pad(v, ((0, 0), (0, 0), (1, 1), (1, 1)))
+        v = ops.pad(v, (1, 1, 1, 1))
         v = self.unfold(v)
         v = ops.reshape(v, (B, self.num_heads, C // self.num_heads, self.kernel_size * self.kernel_size, h * w))
         v = ops.transpose(v, (0, 1, 4, 3, 2))  # B,H,N,kxk,C/H