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[Relax][Frontend][ONNX] Add support for Pad mode="wrap" for opset 19 #19827

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[Relax][Frontend][ONNX] Add support for Pad mode="wrap" for opset 19 #19827

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32 changes: 32 additions & 0 deletions python/tvm/relax/frontend/onnx/onnx_frontend.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2759,6 +2759,38 @@ def _impl_v11(cls, bb, inputs, attr, params):
# edge mode - replicate border values
return bb.emit_te(topi.nn.replicate_pad, inputs[0], pad_before, pad_after)

@classmethod
def _impl_v19(cls, bb, inputs, attr, params):
pads = get_constant(inputs[1], params)
constant_value = get_constant(inputs[2], params)
if constant_value is not None:
constant_value = constant_value.data.numpy().item()
else:
constant_value = 0.0

if isinstance(pads, relax.Constant):
pad_before, pad_after = _np.split(pads.data.numpy(), 2)
pad_before = _np.ndarray.tolist(pad_before)
pad_after = _np.ndarray.tolist(pad_after)
else:
raise ValueError("Dynamic pads are not supported yet.")

pad_mode = attr.get("mode", b"constant").decode("utf-8")
if pad_mode not in ["constant", "edge", "reflect", "wrap"]:
raise tvm.error.OpAttributeInvalid(
"Value " + pad_mode + ' in attribute "mode" is invalid for operator Pad.'
)

if pad_mode == "constant":
return bb.emit_te(topi.nn.pad, inputs[0], pad_before, pad_after, constant_value)
elif pad_mode == "reflect":
return bb.emit_te(topi.nn.mirror_pad, inputs[0], pad_before, pad_after, "REFLECT")
elif pad_mode == "wrap":
return bb.emit_te(topi.nn.circular_pad, inputs[0], pad_before, pad_after)
else:
# edge mode - replicate border values
return bb.emit_te(topi.nn.replicate_pad, inputs[0], pad_before, pad_after)

Comment on lines +2762 to +2793

@gemini-code-assist gemini-code-assist Bot Jun 18, 2026

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medium

The implementation of _impl_v19 is almost identical to _impl_v11, introducing significant code duplication. Since the only difference is the support for mode="wrap", we can simplify _impl_v19 by handling the "wrap" mode directly and delegating all other modes to _impl_v11. This reduces duplication and improves maintainability.

    @classmethod
    def _impl_v19(cls, bb, inputs, attr, params):
        pad_mode = attr.get("mode", b"constant").decode("utf-8")
        if pad_mode == "wrap":
            pads = get_constant(inputs[1], params)
            if isinstance(pads, relax.Constant):
                pad_before, pad_after = _np.split(pads.data.numpy(), 2)
                pad_before = _np.ndarray.tolist(pad_before)
                pad_after = _np.ndarray.tolist(pad_after)
            else:
                raise ValueError("Dynamic pads are not supported yet.")
            return bb.emit_te(topi.nn.circular_pad, inputs[0], pad_before, pad_after)

        return cls._impl_v11(bb, inputs, attr, params)


class Tile(OnnxOpConverter):
"""Converts an onnx Tile node into an equivalent Relax expression."""
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7 changes: 4 additions & 3 deletions tests/python/relax/test_frontend_onnx.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3656,14 +3656,14 @@ def test_pad(dynamic):
if dynamic:
pytest.skip("Dynamic pad not supported")

def verify_pad(input_shape, pads, mode="constant", value=0.0):
def verify_pad(input_shape, pads, mode="constant", value=0.0, opset=14):
indata = np.random.normal(size=input_shape).astype(np.float32)
# numpy expect result
len_dim = len(pads) // 2
np_pads = [(pads[i], pads[i + len_dim]) for i in range(len_dim)]
pads = np.array(pads)
# onnx graph
if mode in ["edge", "reflect"]:
if mode in ["edge", "reflect", "wrap"]:
outdata = np.pad(indata, pad_width=np_pads, mode=mode)
node = helper.make_node("Pad", inputs=["input", "pads"], outputs=["output"], mode=mode)
graph = helper.make_graph(
Expand Down Expand Up @@ -3700,14 +3700,15 @@ def verify_pad(input_shape, pads, mode="constant", value=0.0):
],
)
model = helper.make_model(graph, producer_name="pad_test")
check_correctness(model)
check_correctness(model, opset=opset)

verify_pad((2, 2), [0, 1, 0, 0], "constant", 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")
verify_pad((1, 3, 4, 5), [0, 1, 1, 1, 0, 0, 1, 1], "wrap", opset=19)


@pytest.mark.parametrize("dynamic", [True, False])
Expand Down