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| author | Lester Solbakken <lesters@oath.com> | 2020-08-24 15:17:01 +0200 |
|---|---|---|
| committer | Lester Solbakken <lesters@oath.com> | 2020-08-24 15:17:01 +0200 |
| commit | b62953e2d78aa8d25011d3b007f44d7e75bc5bf6 (patch) | |
| tree | 1e20e870576ac6f76f3141561523bd37b2077140 /config-model | |
| parent | ef1f0e04884a31f55011374b4fff0dcbe9fa7e30 (diff) | |
Model eval: handle unambiguous outputs and models converted from tensorflow to onnx
Diffstat (limited to 'config-model')
| -rw-r--r-- | config-model/src/test/java/com/yahoo/vespa/model/ml/ModelEvaluationTest.java | 7 |
1 files changed, 7 insertions, 0 deletions
diff --git a/config-model/src/test/java/com/yahoo/vespa/model/ml/ModelEvaluationTest.java b/config-model/src/test/java/com/yahoo/vespa/model/ml/ModelEvaluationTest.java index 36b11cee067..9a88b2a31f6 100644 --- a/config-model/src/test/java/com/yahoo/vespa/model/ml/ModelEvaluationTest.java +++ b/config-model/src/test/java/com/yahoo/vespa/model/ml/ModelEvaluationTest.java @@ -142,8 +142,15 @@ public class ModelEvaluationTest { assertNotNull(onnx_mnist_softmax.evaluatorOf("default")); assertNotNull(onnx_mnist_softmax.evaluatorOf("default", "add")); assertNotNull(onnx_mnist_softmax.evaluatorOf("default.add")); + assertNotNull(onnx_mnist_softmax.evaluatorOf("add")); + assertNotNull(onnx_mnist_softmax.evaluatorOf("serving_default")); + assertNotNull(onnx_mnist_softmax.evaluatorOf("serving_default", "add")); + assertNotNull(onnx_mnist_softmax.evaluatorOf("serving_default.add")); assertNotNull(evaluator.evaluatorOf("mnist_softmax", "default.add")); assertNotNull(evaluator.evaluatorOf("mnist_softmax", "default", "add")); + assertNotNull(evaluator.evaluatorOf("mnist_softmax", "add")); + assertNotNull(evaluator.evaluatorOf("mnist_softmax", "serving_default.add")); + assertNotNull(evaluator.evaluatorOf("mnist_softmax", "serving_default", "add")); assertEquals(TensorType.fromSpec("tensor<float>(d0[],d1[784])"), onnx_mnist_softmax.functions().get(0).argumentTypes().get("Placeholder")); Model tensorflow_mnist_softmax = evaluator.models().get("mnist_softmax_saved"); |