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infer old squeeze on known input shape and empty axes #5283

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infer old squeeze on known input shape and empty axes #5283

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8198485
infer old sqz on known input shape and empty axes
daquexian Jun 4, 2023
74f77e9
Merge branch 'main' into improve_old_squz_shape
gramalingam Aug 28, 2023
61f6233
Merge branch 'main' into improve_old_squz_shape
justinchuby Oct 26, 2023
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34 changes: 24 additions & 10 deletions onnx/defs/tensor/old.cc
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Expand Up @@ -2064,18 +2064,25 @@ ONNX_OPERATOR_SET_SCHEMA(
return;
}

std::vector<int64_t> axes;
if (!getRepeatedAttribute(ctx, "axes", axes)) {
return;
}

if (!ctx.getInputType(0)->tensor_type().has_shape()) {
return;
}

ctx.getOutputType(0)->mutable_tensor_type()->mutable_shape();
const auto& input_shape = ctx.getInputType(0)->tensor_type().shape();
const auto input_ndim = input_shape.dim_size();
std::vector<int64_t> axes;
if (!getRepeatedAttribute(ctx, "axes", axes)) {
for (int i = 0; i < input_ndim; ++i) {
if (!input_shape.dim(i).has_dim_value()) {
return;
}
if (input_shape.dim(i).dim_value() == 1) {
axes.push_back(i);
}
}
}

std::transform(axes.begin(), axes.end(), axes.begin(), [&](int64_t axis) -> int64_t {
return axis < 0 ? axis + input_ndim : axis;
});
Expand Down Expand Up @@ -4128,17 +4135,24 @@ ONNX_OPERATOR_SET_SCHEMA(
return;
}

std::vector<int64_t> axes;
if (!getRepeatedAttribute(ctx, "axes", axes)) {
return;
}

if (!ctx.getInputType(0)->tensor_type().has_shape()) {
return;
}

ctx.getOutputType(0)->mutable_tensor_type()->mutable_shape();
const auto& input_shape = ctx.getInputType(0)->tensor_type().shape();
const auto input_ndim = input_shape.dim_size();
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That seems to be the same code than above, could it be moved in one separate function?

std::vector<int64_t> axes;
if (!getRepeatedAttribute(ctx, "axes", axes)) {
for (int i = 0; i < input_ndim; ++i) {
if (!input_shape.dim(i).has_dim_value()) {
return;
}
if (input_shape.dim(i).dim_value() == 1) {
axes.push_back(i);
}
}
}

for (int i = 0, j = 0; i < input_shape.dim_size(); ++i) {
if (static_cast<size_t>(j) < axes.size() && axes[j] == i) {
Expand Down
15 changes: 15 additions & 0 deletions onnx/test/shape_inference_test.py
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Expand Up @@ -1183,6 +1183,21 @@ def test_squeeze(self) -> None:
graph, [make_tensor_value_info("y", TensorProto.FLOAT, (3, 2))]
)

def test_squeeze_no_axes_opset11(self) -> None:
graph = self._make_graph(
[
("x", TensorProto.FLOAT, (1, 3, 1, 1, 2, 1)),
],
[make_node("Squeeze", ["x"], "y")],
[],
)
operatorsetid = OperatorSetIdProto()
operatorsetid.domain = ""
operatorsetid.version = 11
self._assert_inferred(
graph, [make_tensor_value_info("y", TensorProto.FLOAT, (3, 2))]
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I guess that the opset needs to be specified, eg., something like opset_imports=[helper.make_opsetid(ONNX_DOMAIN, 11)]

)

def test_unsqueeze_regular(self) -> None:
graph = self._make_graph(
[("x", TensorProto.FLOAT, (3, 2)), ("axes", TensorProto.INT64, (4,))],
Expand Down