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[Relax] Add FRelaxInferLayout for scatter_elements operator #18638

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Merged
mshr-h merged 2 commits into from
Jan 6, 2026
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Merged

[Relax] Add FRelaxInferLayout for scatter_elements operator #18638

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39967d7
[Relax] Add FRelaxInferLayout for scatter_elements operator
guan404ming Jan 5, 2026
7cc46e9
Update test
guan404ming Jan 6, 2026
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31 changes: 30 additions & 1 deletion src/relax/op/tensor/manipulate.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -2613,14 +2613,43 @@ StructInfo InferStructInfoScatterElements(const Call& call, const BlockBuilder&
return TensorStructInfo(data_sinfo->dtype, data_sinfo->ndim, data_sinfo->vdevice);
}

// TODO(relax-team): implement FRelaxInferLayout for scatter_elements
InferLayoutOutput InferLayoutScatterElements(
const Call& call, const ffi::Map<ffi::String, ffi::Array<ffi::String>>& desired_layouts,
const VarLayoutMap& var_layout_map) {
ICHECK(NoDesiredLayout(call, desired_layouts));
const auto* attrs = call->attrs.as<ScatterElementsAttrs>();
ICHECK(attrs) << "Invalid Call";

LayoutDecision data_layout = GetLayoutDecision(var_layout_map, call->args[0]);
LayoutDecision indices_layout = GetLayoutDecision(var_layout_map, call->args[1]);
LayoutDecision updates_layout = GetLayoutDecision(var_layout_map, call->args[2]);

LayoutDecision layout = data_layout;
if (NLayoutEqual()(indices_layout, updates_layout)) {
layout = indices_layout;
}

if (layout->layout.ndim() != layout->layout.ndim_primal()) {
const auto* tensor_sinfo = GetStructInfoAs<TensorStructInfoNode>(call->args[0]);
ICHECK(tensor_sinfo != nullptr) << "Invalid Call";
ICHECK(!tensor_sinfo->IsUnknownNdim()) << "Only support static ndim for now";
int ndim = tensor_sinfo->ndim;
layout = LayoutDecision(InitialLayout(ndim));
}

ObjectPtr<ScatterElementsAttrs> new_attrs = ffi::make_object<ScatterElementsAttrs>(*attrs);
new_attrs->axis = FindAxis(layout->layout, attrs->axis->value);
return InferLayoutOutput({layout, layout, layout}, {layout}, Attrs(new_attrs));
}

TVM_REGISTER_OP("relax.scatter_elements")
.set_attrs_type<ScatterElementsAttrs>()
.set_num_inputs(3)
.add_argument("data", "Tensor", "The input tensor.")
.add_argument("indices", "Tensor", "The indices tensor.")
.add_argument("updates", "Tensor", "The input tensor of updates.")
.set_attr<FInferStructInfo>("FInferStructInfo", InferStructInfoScatterElements)
.set_attr<FRelaxInferLayout>("FRelaxInferLayout", InferLayoutScatterElements)
.set_attr<Bool>("FPurity", Bool(true));

/* relax.scatter_nd */
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14 changes: 7 additions & 7 deletions tests/python/contrib/test_msc/test_graph_build.py
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Expand Up @@ -2443,22 +2443,22 @@ def forward(self, data, index, src):

expected1 = {
"inputs": [
{"name": "inp_0", "shape": [bz, 20], "dtype": "float32", "layout": ""},
{"name": "inp_1", "shape": [2, 5], "dtype": "float32", "layout": ""},
{"name": "inp_0", "shape": [bz, 20], "dtype": "float32", "layout": "AB"},
{"name": "inp_1", "shape": [2, 5], "dtype": "float32", "layout": "AB"},
],
"outputs": [
{"name": "scatter_elements", "shape": [bz, 20], "dtype": "float32", "layout": ""}
{"name": "scatter_elements", "shape": [bz, 20], "dtype": "float32", "layout": "AB"}
],
"nodes": {"total": 4, "input": 2, "constant": 1, "scatter_elements": 1},
}
expected2 = {
"inputs": [
{"name": "inp_0", "shape": [bz, 20], "dtype": "float32", "layout": ""},
{"name": "inp_1", "shape": [2, 5], "dtype": "int64", "layout": ""},
{"name": "inp_2", "shape": [2, 5], "dtype": "float32", "layout": ""},
{"name": "inp_0", "shape": [bz, 20], "dtype": "float32", "layout": "AB"},
{"name": "inp_1", "shape": [2, 5], "dtype": "int64", "layout": "AB"},
{"name": "inp_2", "shape": [2, 5], "dtype": "float32", "layout": "AB"},
],
"outputs": [
{"name": "scatter_elements", "shape": [bz, 20], "dtype": "float32", "layout": ""}
{"name": "scatter_elements", "shape": [bz, 20], "dtype": "float32", "layout": "AB"}
],
"nodes": {"total": 4, "input": 3, "scatter_elements": 1},
}
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55 changes: 55 additions & 0 deletions tests/python/relax/test_transform_convert_layout.py
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Expand Up @@ -5327,5 +5327,60 @@ def main(
verify(Input, Expected)


def test_conv2d_scatter_elements():
@I.ir_module
class Input:
@R.function
def main(
x: R.Tensor((2, 3, 28, 28), "float32"),
w: R.Tensor((4, 3, 3, 3), "float32"),
indices: R.Tensor((2, 4, 26, 26), "int64"),
) -> R.Tensor(None, "float32", ndim=4):
with R.dataflow():
data: R.Tensor((2, 4, 26, 26), "float32") = R.nn.conv2d(x, w, out_dtype="float32")
updates: R.Tensor((2, 4, 26, 26), "float32") = R.nn.relu(data)
gv = R.scatter_elements(data, indices, updates, axis=1)
R.output(gv)
return gv

@I.ir_module
class Expected:
@R.function
def main(
x: R.Tensor((2, 3, 28, 28), dtype="float32"),
w: R.Tensor((4, 3, 3, 3), dtype="float32"),
indices: R.Tensor((2, 4, 26, 26), dtype="int64"),
) -> R.Tensor(None, dtype="float32", ndim=4):
with R.dataflow():
lv: R.Tensor((2, 28, 28, 3), dtype="float32") = R.permute_dims(x, axes=[0, 2, 3, 1])
lv1: R.Tensor((4, 3, 3, 3), dtype="float32") = R.permute_dims(w, axes=[0, 2, 3, 1])
data: R.Tensor((2, 26, 26, 4), dtype="float32") = R.nn.conv2d(
lv,
lv1,
strides=[1, 1],
padding=[0, 0, 0, 0],
dilation=[1, 1],
groups=1,
data_layout="NHWC",
kernel_layout="OHWI",
out_layout="NHWC",
out_dtype="float32",
)
updates: R.Tensor((2, 26, 26, 4), dtype="float32") = R.nn.relu(data)
lv2: R.Tensor((2, 26, 26, 4), dtype="int64") = R.permute_dims(
indices, axes=[0, 2, 3, 1]
)
lv3: R.Tensor((2, 26, 26, 4), dtype="float32") = R.scatter_elements(
data, lv2, updates, axis=3, reduction="update"
)
gv: R.Tensor((2, 4, 26, 26), dtype="float32") = R.permute_dims(
lv3, axes=[0, 3, 1, 2]
)
R.output(gv)
return gv

verify(Input, Expected)


if __name__ == "__main__":
tvm.testing.main()
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