hFSSKrSSKrSSKrSSKrSSKr"SS\R 5r\S:Xa\R"5 gg)Nc\rSrSrS\S\4SjrSrSrSr Sr S r S\S\ R\4S jrS rS rS rSrSrg)TestModelInference model_textexpectedc[RRU5n[RR U5nUR R n[XR5HzupgURnURURS55 URn URU RS55 U Rn URX5 M| g)zCheck that the model inference infers the expected types for outputs. Restricted to the simple case of tensor types, so expected types specify only the element type (ints corresponding to onnx.TensorProto.DataType). tensor_type elem_typeN)onnxparser parse_modelshape_inference infer_shapesgraphoutputziptype assertTrueHasFieldr r assertEqual) selfrrmodelinferredoutputsrexpected_elem_type inferred_typer r s X/var/www/fran/franai/venv/lib/python3.13/site-packages/onnx/test/model_inference_test.py_checkTestModelInference._check s  '' 3''44U;..''*-g*@ &F"KKM OOM22=A B'33K OOK00= >#--I   Y ; +Ac\SnURU[RR5 g)z3Test that model inference infers model output type.z < ir_version: 7, opset_import: [ "" : 17] > agraph (float[N] x) => (y) { y = Cast (x) } Nrr TensorProtoINT32rrs r test_mi_basic TestModelInference.test_mi_basics%   E4++112r c\SnURU[RR5 g)zTest use of functions.a < ir_version: 7, opset_import: [ "" : 17, "local" : 1] > agraph (float[N] x) => (y) { y = local.cast(x) } < opset_import: [ "" : 17 ], domain: "local" > cast (x) => (y) { y = Cast (x) } Nr"r%s rtest_mi_function#TestModelInference.test_mi_function+% $ E4++112r c\SnURU[RR5 g)z0Test use of functions with attribute parameters.a < ir_version: 7, opset_import: [ "" : 17, "local" : 1] > agraph (float[N] x) => (y) { y = local.cast(x) } < opset_import: [ "" : 17 ], domain: "local" > cast(x) => (y) { y = Cast (x) } Nr"r%s rtest_mi_function_attr(TestModelInference.test_mi_function_attrAr+r c\SnURU[RR5 g)z1Test use of function attributes within subgraphs.a < ir_version: 7, opset_import: [ "" : 17, "local" : 1] > agraph (float[N] x, bool flag) => (y) { y = local.cast(x, flag) } < opset_import: [ "" : 17 ], domain: "local" > cast(x, flag) => (y) { y = If (flag) < then_branch = g1 () => (z_then) { z_then = Cast (x) }, else_branch = g2 () => (z_else) { z_else = Cast (x) } > } Nr"r%s rtest_mi_function_subgraph_attr1TestModelInference.test_mi_function_subgraph_attrWs% * E4++112r cSnURU[RR[RR5 g)z-Test use of multiple invocation of functions.a < ir_version: 7, opset_import: [ "" : 17, "local" : 1] > agraph (float[N] x, bool flag) => (y, z) { y = local.cast(x, flag) z = local.cast(x, flag) } < opset_import: [ "" : 17 ], domain: "local" > cast(x, flag) => (y) { y = If (flag) < then_branch = g1 () => (z_then) { z_then = Cast (x) }, else_branch = g2 () => (z_else) { z_else = Cast (x) } > } N)rr r#r$INT64r%s rtest_mi_function_multiple_calls2TestModelInference.test_mi_function_multiple_callsps3 , E4++1143C3C3I3IJr c[RRU5n[RR USSS5nUR R n[XR5HupgURnURURS55 URn URU RS55 U Rn UR[U R5[U55 [U RU5HAupURU RS55 URU R U 5 MC M g)zCheck that the model inference infers the expected shapes for outputs. Restricted to the simple case of tensor type outputs with completely known shapes. Tr shape dim_valueN)r r r rrrrrrrrr r7rlendimr8) rrrrrrrexpected_shaperr inferred_shape inferred_dim expected_dims r _check_shapeTestModelInference._check_shapes   '' 3''44UD$M..''&)'&< "F"KKM OOM22=A B'33K OOK009 :(..N   S!3!34c.6I J.1.2D2Dn.U*  5 5k BC  !7!7F/V'=r c0SnURU/SQ5 g)Na < ir_version: 7, opset_import: [ "" : 17] > mymodel (float[4, 8, 16] x) => (y) { shape = Constant() y = Reshape(x, shape) } r?r%s rtest_mi_constant#TestModelInference.test_mi_constants  %,r c0SnURU/SQ5 g)Nae < ir_version: 7, opset_import: [ "" : 17] > mymodel (float[4, 8, 16] x) => (y) { shape = Constant() two = Constant() shape2 = Mul(shape, two) y = Reshape(x, shape2) } rBrFr%s rtest_mi_constant_2%TestModelInference.test_mi_constant_2s  %,r c6SnURUSS//SQ5 g)Na: < ir_version: 7, opset_import: [ "" : 17, "local" : 1] > main (float x) => (y, z) { y, z = local.expand(x) } < opset_import: [ "" : 17 ], domain: "local" > expand (x) => (y, z) { shape1 = Constant() shape2 = Constant() z = Expand (x, shape2) y = Expand (x, shape1) } rD)rCrCrCrFr%s rtest_mi_constant_in_function/TestModelInference.test_mi_constant_in_functions!& %!Q3r cSnURU[RR[RR5 g)z2Test use of default values of function attributes.a agraph (float[N] x) => (y, z) { y = local.cast (x) # casts to INT32 type (encoding value 6) z = local.cast (x) # uses default-attribute value of 1 (FLOAT type) } cast (x) => (y) { y = Cast (x) } N)rr r#r$FLOATr%s rtest_mi_function_default_attr0TestModelInference.test_mi_function_default_attrs3   E4++1143C3C3I3IJr N)__name__ __module__ __qualname____firstlineno__strintrr&r)r-r0r4typingSequencer?rGrJrMrQ__static_attributes__rSr rrr sc<<< 33,3,32K4GsGvs7KG& - -4,Kr r__main__) rZunittestr onnx.parseronnx.shape_inferenceTestCaserrTmainrSr rrcsE SK**SKl z MMOr