Add edge padding mode

Author: guan404ming

python/tvm/relax/frontend/onnx/onnx_frontend.py

@@ -1881,8 +1881,8 @@ def _impl_v2(cls, bb, inputs, attr, params):
         elif pad_mode == "reflect":
             return bb.emit_te(topi.nn.mirror_pad, inputs[0], pad_before, pad_after, "REFLECT")
         else:
-            # TODO(gigiblender) Support edge mode.
-            raise NotImplementedError("Pad mode {} not implemented".format(pad_mode))
+            # edge mode - replicate border values
+            return bb.emit_te(topi.nn.replicate_pad, inputs[0], pad_before, pad_after)
 
     @classmethod
     def _impl_v11(cls, bb, inputs, attr, params):
@@ -1911,8 +1911,8 @@ def _impl_v11(cls, bb, inputs, attr, params):
         elif pad_mode == "reflect":
             return bb.emit_te(topi.nn.mirror_pad, inputs[0], pad_before, pad_after, "REFLECT")
         else:
-            # TODO(gigiblender) Support edge mode.
-            raise NotImplementedError("Pad mode {} not implemented".format(pad_mode))
+            # edge mode - replicate border values
+            return bb.emit_te(topi.nn.replicate_pad, inputs[0], pad_before, pad_after)
 
 
 class Tile(OnnxOpConverter):

tests/python/relax/test_frontend_onnx.py

@@ -2440,6 +2440,8 @@ def verify_pad(input_shape, pads, mode="constant", value=0.0):
     verify_pad((2, 3), [1, 0, 0, 1], "constant", 0.0)
     verify_pad((3, 2), [0, 0, 1, 0], "constant", 5.0)
     verify_pad((1, 3, 4, 5), [0, 1, 1, 1, 0, 0, 1, 1], "reflect")
+    verify_pad((2, 3), [1, 1, 1, 1], "edge")
+    verify_pad((1, 3, 4, 5), [0, 1, 1, 1, 0, 0, 1, 1], "edge")
 
 
 @pytest.mark.parametrize("dynamic", [True, False])
@@ -2496,6 +2498,8 @@ def verify_pad(input_shape, pads, mode="constant", value=0.0):
     verify_pad((2, 3), [1, 0, 0, 1], "constant", 0.0)
     verify_pad((3, 2), [0, 0, 1, 0], "constant", 5.0)
     verify_pad((1, 3, 4, 5), [0, 1, 1, 1, 0, 0, 1, 1], "reflect")
+    verify_pad((2, 3), [1, 1, 1, 1], "edge")
+    verify_pad((1, 3, 4, 5), [0, 1, 1, 1, 0, 0, 1, 1], "edge")
 
 
 @pytest.mark.parametrize("fp_arith", [np.float16, np.float32])