|
8 | 8 | fromonnx_array_api.ext_test_caseimportExtTestCase |
9 | 9 | fromonnx_array_api.light_apiimportstart |
10 | 10 | fromonnx_array_api.graph_apiimportGraphBuilder |
11 | | -fromonnx_array_api.translate_apiimporttranslate |
| 11 | +fromonnx_array_api.translate_apiimporttranslate,Translater |
| 12 | +fromonnx_array_api.translate_api.builder_emitterimportBuilderEmitter |
12 | 13 |
|
13 | 14 |
|
14 | 15 | OPSET_API=min(19,onnx_opset_version()-1) |
@@ -38,7 +39,7 @@ def light_api( |
38 | 39 | op.Identity(Y, outputs=["Y"]) |
39 | 40 | return Y |
40 | 41 |
|
41 | | - g = GraphBuilder({'': 19}) |
| 42 | + g = GraphBuilder({'': 19}, ir_version=11) |
42 | 43 | g.make_tensor_input("X", TensorProto.FLOAT, ()) |
43 | 44 | light_api(g.op, "X") |
44 | 45 | g.make_tensor_output("Y", TensorProto.FLOAT, ()) |
@@ -89,7 +90,7 @@ def light_api( |
89 | 90 | op.Identity(Y, outputs=["Y"]) |
90 | 91 | return Y |
91 | 92 |
|
92 | | - g = GraphBuilder({'': 19}) |
| 93 | + g = GraphBuilder({'': 19}, ir_version=11) |
93 | 94 | g.make_tensor_input("X", TensorProto.FLOAT, ()) |
94 | 95 | light_api(g.op, "X") |
95 | 96 | g.make_tensor_output("Y", TensorProto.FLOAT, ()) |
@@ -117,6 +118,62 @@ def light_api( |
117 | 118 | self.assertNotEmpty(model) |
118 | 119 | check_model(model) |
119 | 120 |
|
| 121 | +deftest_exp_f(self): |
| 122 | +onx=start(opset=19).vin("X").Exp().rename("Y").vout().to_onnx() |
| 123 | +self.assertIsInstance(onx,ModelProto) |
| 124 | +self.assertIn("Exp",str(onx)) |
| 125 | +ref=ReferenceEvaluator(onx) |
| 126 | +a=np.arange(10).astype(np.float32) |
| 127 | +got=ref.run(None, {"X":a})[0] |
| 128 | +self.assertEqualArray(np.exp(a),got) |
| 129 | + |
| 130 | +tr=Translater(onx,emitter=BuilderEmitter("mm")) |
| 131 | +code=tr.export(as_str=True) |
| 132 | + |
| 133 | +expected=dedent( |
| 134 | +""" |
| 135 | + def light_api( |
| 136 | + op: "GraphBuilder", |
| 137 | + X: "FLOAT[]", |
| 138 | + ): |
| 139 | + Y = op.Exp(X) |
| 140 | + op.Identity(Y, outputs=["Y"]) |
| 141 | + return Y |
| 142 | +
|
| 143 | +
|
| 144 | + def mm() -> "ModelProto": |
| 145 | + g = GraphBuilder({'': 19}, ir_version=11) |
| 146 | + g.make_tensor_input("X", TensorProto.FLOAT, ()) |
| 147 | + light_api(g.op, "X") |
| 148 | + g.make_tensor_output("Y", TensorProto.FLOAT, ()) |
| 149 | + model = g.to_onnx() |
| 150 | + return model |
| 151 | +
|
| 152 | +
|
| 153 | + model = mm() |
| 154 | + """ |
| 155 | + ).strip("\n") |
| 156 | +self.assertEqual(expected,code.strip("\n")) |
| 157 | + |
| 158 | +deflight_api( |
| 159 | +op:"GraphBuilder", |
| 160 | +X:"FLOAT[]",# noqa: F722 |
| 161 | + ): |
| 162 | +Y=op.Exp(X) |
| 163 | +op.Identity(Y,outputs=["Y"]) |
| 164 | +returnY |
| 165 | + |
| 166 | +g2=GraphBuilder({"":19}) |
| 167 | +g2.make_tensor_input("X",TensorProto.FLOAT, ("A",)) |
| 168 | +light_api(g2.op,"X") |
| 169 | +g2.make_tensor_output("Y",TensorProto.FLOAT, ("A",)) |
| 170 | +onx2=g2.to_onnx() |
| 171 | + |
| 172 | +ref=ReferenceEvaluator(onx2) |
| 173 | +a=np.arange(10).astype(np.float32) |
| 174 | +got=ref.run(None, {"X":a})[0] |
| 175 | +self.assertEqualArray(np.exp(a),got) |
| 176 | + |
120 | 177 |
|
121 | 178 | if__name__=="__main__": |
122 | 179 | unittest.main(verbosity=2) |