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[Fix][Relax] Normalize squeeze axes before layout inference #20773

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[Fix][Relax] Normalize squeeze axes before layout inference #20773

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4 changes: 2 additions & 2 deletions src/relax/op/tensor/manipulate.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -1494,9 +1494,9 @@ InferLayoutOutput InferLayoutSqueeze(
const auto* shape = tensor_ty->shape.as<ShapeExprNode>();
TVM_FFI_ICHECK(shape != nullptr) << "Only support static shape for now";

ffi::Array<int64_t> axis;
std::vector<int> axis;
if (attrs->axis.has_value()) {
axis = attrs->axis.value();
axis = NormalizeAxes(call, ndim, attrs->axis.value());
} else {
axis.reserve(ndim);
for (int i = 0; i < ndim; ++i) {
Expand Down
56 changes: 52 additions & 4 deletions tests/python/relax/test_transform_convert_layout.py
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Original file line number Diff line number Diff line change
Expand Up @@ -16,6 +16,8 @@
# under the License.
# ruff: noqa: E501, F841

import pytest

import tvm
import tvm_tirx
import tvm_tirx.testing
Expand Down Expand Up @@ -922,7 +924,8 @@ def main(
verify(Input, Expected)


def test_conv2d_expand_dims_squeeze():
@pytest.mark.parametrize("axis", [[1, 3], [-5, -3], [1, -3]])
def test_conv2d_expand_dims_squeeze(axis):
@I.ir_module
class Input:
@R.function
Expand All @@ -932,7 +935,7 @@ def main(
with R.dataflow():
gv: R.Tensor((2, 4, 26, 26), "float32") = R.nn.conv2d(x, w, out_dtype="float32")
gv2: R.Tensor((2, 1, 4, 1, 26, 26), "float32") = R.expand_dims(gv, axis=(-3, 1))
gv3: R.Tensor((2, 4, 26, 26), "float32") = R.squeeze(gv2, axis=[1, 3])
gv3: R.Tensor((2, 4, 26, 26), "float32") = R.squeeze(gv2, axis=axis)
R.output(gv3)
return gv3

Expand Down Expand Up @@ -970,6 +973,50 @@ def main(
verify(Input, Expected)


@pytest.mark.parametrize(
"shape, axis, expected_axis",
[
((1, 10), [-2], [0]),
((10, 1), [-1], [1]),
((1, 10, 1), None, [0, 2]),
((1, 10, 1), [], []),
],
)
def test_squeeze_axes_without_layout_change(shape, axis, expected_axis):
def make_module(axes):
builder = tvm.relax.BlockBuilder()
x = tvm.relax.Var("x", tvm.relax.TensorType(shape, "float32"))
with builder.function("main", [x]):
with builder.dataflow():
output = builder.emit_output(tvm.relax.op.squeeze(x, axis=axes))
builder.emit_func_output(output)
return builder.get()

actual = ConvertLayout({})(make_module(axis))
tvm_tirx.ir.assert_structural_equal(actual, make_module(expected_axis))


@pytest.mark.parametrize("axis", [[1], [-3]])
def test_conv2d_squeeze_channel(axis):
def make_module(axes):
builder = tvm.relax.BlockBuilder()
x = tvm.relax.Var("x", tvm.relax.TensorType((2, 3, 28, 28), "float32"))
w = tvm.relax.Var("w", tvm.relax.TensorType((1, 3, 3, 3), "float32"))
with builder.function("main", [x, w]):
with builder.dataflow():
conv = builder.emit(tvm.relax.op.nn.conv2d(x, w, out_dtype="float32"))
output = builder.emit_output(tvm.relax.op.squeeze(conv, axis=axes))
builder.emit_func_output(output)
return builder.get()

convert = ConvertLayout({"relax.nn.conv2d": ["NHWC", "OHWI"]})
actual = convert(make_module(axis))
tvm_tirx.ir.assert_structural_equal(actual, convert(make_module([1])))
squeeze = actual["main"].body.blocks[0].bindings[-1].value
assert squeeze.op == tvm_tirx.ir.Op.get("relax.squeeze")
assert list(squeeze.attrs.axis) == [3]


def test_conv2d_strided_slice():
@I.ir_module
class Input:
Expand Down Expand Up @@ -3336,7 +3383,8 @@ def main(
verify(Input, Expected_NHWC4c, {"relax.nn.conv2d": ["NHWC4c", "OHWI4o"]})


def test_conv2d_squeeze_sub_indexed():
@pytest.mark.parametrize("axis", [[0], [-4]])
def test_conv2d_squeeze_sub_indexed(axis):
@I.ir_module
class Input:
@R.function
Expand All @@ -3345,7 +3393,7 @@ def main(
) -> R.Tensor(None, "float32", ndim=3):
with R.dataflow():
gv: R.Tensor((1, 4, 26, 26), "float32") = R.nn.conv2d(x, w, out_dtype="float32")
gv2: R.Tensor((4, 26, 26), "float32") = R.squeeze(gv, axis=[0])
gv2: R.Tensor((4, 26, 26), "float32") = R.squeeze(gv, axis=axis)
R.output(gv2)
return gv2

Expand Down