diff --git a/CHANGELOGS.rst b/CHANGELOGS.rst
index 13c81ab..9f22a80 100644
--- a/CHANGELOGS.rst
+++ b/CHANGELOGS.rst
@@ -4,6 +4,7 @@ Change Logs
0.2.0
+++++
+* :pr:`77`: supports ConcatOfShape and Slice with the light API
* :pr:`76`: add a mode to compare models without execution
* :pr:`75`: add QuickGelu to ExtendedReferenceEvaluator
* :pr:`71`: adds tools to compare two onnx graphs
diff --git a/_unittests/ut_light_api/test_light_api.py b/_unittests/ut_light_api/test_light_api.py
index 0483354..e14896a 100644
--- a/_unittests/ut_light_api/test_light_api.py
+++ b/_unittests/ut_light_api/test_light_api.py
@@ -538,7 +538,35 @@ def test_constant_of_shape(self):
got = ref.run(None, {"X": np.array([2, 3], dtype=np.int64)})[0]
self.assertEqualArray(np.zeros((2, 3), dtype=np.float32), got)
+ def test_constant_of_shape_value(self):
+ onx = (
+ start()
+ .vin("X", TensorProto.INT64, shape=[None, None])
+ .ConstantOfShape(value=np.array([1], dtype=np.float32))
+ .vout(shape=[])
+ .to_onnx()
+ )
+ ref = ReferenceEvaluator(onx)
+ got = ref.run(None, {"X": np.array([2, 3], dtype=np.int64)})[0]
+ self.assertEqualArray(np.ones((2, 3), dtype=np.float32), got)
+
+ def test_slice(self):
+ onx = (
+ start(opset=18, ir_version=9)
+ .cst(np.array([1], dtype=np.int64), name="one")
+ .cst(np.array([2], dtype=np.int64), name="two")
+ .vin("X", TensorProto.INT64, shape=[None, None])
+ .ConstantOfShape(value=np.array([1], dtype=np.float32))
+ .rename("CX")
+ .bring("CX", "one", "two", "one")
+ .Slice()
+ .vout(shape=[])
+ .to_onnx()
+ )
+ ref = ReferenceEvaluator(onx)
+ got = ref.run(None, {"X": np.array([2, 3], dtype=np.int64)})[0]
+ self.assertEqualArray(np.ones((2, 1), dtype=np.float32), got)
+
if __name__ == "__main__":
- TestLightApi().test_add()
unittest.main(verbosity=2)
diff --git a/onnx_array_api/light_api/_op_var.py b/onnx_array_api/light_api/_op_var.py
index 3a74ed2..1291594 100644
--- a/onnx_array_api/light_api/_op_var.py
+++ b/onnx_array_api/light_api/_op_var.py
@@ -314,6 +314,13 @@ def Selu(
def Shrink(self, bias: float = 0.0, lambd: float = 0.5) -> "Var":
return self.make_node("Shrink", self, bias=bias, lambd=lambd)
+ def Slice(
+ self, starts: "Var", ends: "Var", axes: "Var", steps: Optional["Var"] = None
+ ) -> "Var":
+ if steps is None:
+ return self.make_node("Slice", self, starts, ends, axes)
+ return self.make_node("Slice", self, starts, ends, axes, steps)
+
def Softmax(self, axis: int = -1) -> "Var":
return self.make_node("Softmax", self, axis=axis)
diff --git a/onnx_array_api/light_api/model.py b/onnx_array_api/light_api/model.py
index 25194ac..6478c4d 100644
--- a/onnx_array_api/light_api/model.py
+++ b/onnx_array_api/light_api/model.py
@@ -406,7 +406,7 @@ def to_onnx(self) -> GRAPH_PROTO:
return graph
model = make_model(graph, opset_imports=opsets)
if self.ir_version:
- model.ir_version = ir_version
+ model.ir_version = self.ir_version
if not is_windows() or not is_azure():
# check_model fails sometimes on Windows
check_model(model)
pFad - Phonifier reborn
Pfad - The Proxy pFad of © 2024 Garber Painting. All rights reserved.
Note: This service is not intended for secure transactions such as banking, social media, email, or purchasing. Use at your own risk. We assume no liability whatsoever for broken pages.
Alternative Proxies:
Alternative Proxy
pFad Proxy
pFad v3 Proxy
pFad v4 Proxy