Documentation (#78)

* update requirements

* Add ConstantOfShape to light API

* add slice

* changelogs

* k

Author: xadupre

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

_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)

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)
 

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)