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[Topi] Support negative indices in topi.gather_nd #20316

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[Topi] Support negative indices in topi.gather_nd #20316

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13 changes: 9 additions & 4 deletions include/tvm/topi/transform.h
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Original file line number Diff line number Diff line change
Expand Up @@ -1606,11 +1606,16 @@ inline Tensor gather_nd(const Tensor& data, const Tensor& indices, int batch_dim
// Index tensors are validated by integer element kind; vector lane encoding is
// irrelevant for choosing whether an index cast is needed.
PrimType indices_ty = indices->dtype;
if (indices_ty.MatchesCode(DLDataTypeCode::kDLInt, DLDataTypeCode::kDLUInt)) {
real_indices.push_back(indices(indices_position));
} else {
real_indices.push_back(tvm::cast(tvm::PrimType::Int(32), indices(indices_position)));
PrimExpr idx = indices(indices_position);
if (!indices_ty.MatchesCode(DLDataTypeCode::kDLInt, DLDataTypeCode::kDLUInt)) {
idx = tvm::cast(tvm::PrimType::Int(32), idx);
}
// Support negative indices like the ONNX GatherND op does (and
// topi.scatter_elements already does): an in-range negative index
// counts from the end of the corresponding data axis.
PrimExpr axis_size = data->shape[batch_dims + i];
idx = idx + tvm::cast(tvm::PrimType::Int(32), idx < 0) * axis_size;
real_indices.push_back(idx);
}
if (real_indices.size() == ndim_d) {
return data(real_indices);
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30 changes: 29 additions & 1 deletion tests/python/relax/test_op_manipulate.py
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Original file line number Diff line number Diff line change
Expand Up @@ -17,9 +17,10 @@
# ruff: noqa: E731, F841
import pytest

import numpy as np
import tvm
import tvm.testing
from tvm import relax, tirx
from tvm import relax, te, tirx, topi
from tvm.ir import Op, VDevice
from tvm.script import relax as R
from tvm.script import tirx as T
Expand Down Expand Up @@ -3209,6 +3210,33 @@ def test_gather_nd_infer_ty_wrong_inputs():
bb.normalize(relax.op.gather_nd(x0, i1))


@pytest.mark.parametrize("batch_dims", [0, 1])
def test_gather_nd_negative_indices_topi(batch_dims):
# topi.gather_nd supports in-range negative indices (ONNX GatherND
# semantics) even when the indices are runtime values, matching what
# topi.scatter_elements already does.
data_np = np.arange(24, dtype="int32").reshape(2, 3, 4)
if batch_dims == 0:
# index row k addresses data axis k (sizes 2, 3, 4)
indices_np = np.array(
[[[0, -1], [-1, 1]], [[-2, 1], [2, -2]], [[-4, 3], [3, -1]]], dtype="int64"
)
expected = data_np[tuple(indices_np)]
else:
indices_np = np.array([[[-1, -2], [-3, 1]], [[2, -1], [0, -3]]], dtype="int64")
expected = np.stack([data_np[b][tuple(indices_np[:, b])] for b in range(2)])

data = te.placeholder(tuple(data_np.shape), dtype="int32", name="data")
indices = te.placeholder(tuple(indices_np.shape), dtype="int64", name="indices")
out = topi.gather_nd(data, indices, batch_dims)
func = te.create_prim_func([data, indices, out]).with_attr("target", tvm.target.Target("llvm"))
f = tvm.build(tvm.IRModule({"main": func}), target="llvm")

out_t = tvm.runtime.tensor(np.zeros(expected.shape, dtype="int32"))
f(tvm.runtime.tensor(data_np), tvm.runtime.tensor(indices_np), out_t)
tvm.testing.assert_allclose(out_t.numpy(), expected)


def test_scatter_elements_infer_ty():
bb = relax.BlockBuilder()
vdev0 = VDevice("llvm")
Expand Down