Add probing of ONNX models for type resolving in Java

2 files changed, 40 insertions, 0 deletions

diff --git a/config-model/src/test/cfg/application/onnx_probe/files/create_dynamic_model.py b/config-model/src/test/cfg/application/onnx_probe/files/create_dynamic_model.py
new file mode 100755
index 00000000000..b493e394ee4
--- /dev/null
+++ b/config-model/src/test/cfg/application/onnx_probe/files/create_dynamic_model.py
@@ -0,0 +1,19 @@
+# Copyright Yahoo. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
+
+import onnx
+import numpy as np
+from onnx import helper, TensorProto
+
+INPUT_1 = helper.make_tensor_value_info('input1', TensorProto.FLOAT, ["batch", 2])
+INPUT_2 = helper.make_tensor_value_info('input2', TensorProto.FLOAT, ["batch", 2])
+OUTPUT = helper.make_tensor_value_info('out', TensorProto.FLOAT, ["batch", "dim1", "dim2"])
+
+SHAPE = helper.make_tensor('shape', TensorProto.INT64, dims=[3], vals=np.array([1,2,2]).astype(np.int64))
+
+nodes = [
+    helper.make_node('Concat', ['input1', 'input2'], ['concat'], axis=1),
+    helper.make_node('Reshape', ['concat', 'shape'], ['out']),
+]
+graph_def = helper.make_graph(nodes, 'simple_scoring', [INPUT_1, INPUT_2], [OUTPUT], [SHAPE])
+model_def = helper.make_model(graph_def, producer_name='create_dynamic_model.py', opset_imports=[onnx.OperatorSetIdProto(version=12)])
+onnx.save(model_def, 'dynamic_model_2.onnx')
diff --git a/config-model/src/test/cfg/application/onnx_probe/files/dynamic_model.onnx b/config-model/src/test/cfg/application/onnx_probe/files/dynamic_model.onnx
new file mode 100644
index 00000000000..28c600e2a09
--- /dev/null
+++ b/config-model/src/test/cfg/application/onnx_probe/files/dynamic_model.onnx
@@ -0,0 +1,21 @@
+create_dynamic_model_2.py:Ö

+-
+input1
+input2concat"Concat*
+axis
 

+
+concat
+shapeout"Reshapesimple_scoring*:
BshapeZ
+input1
+


+batch
+Z
+input2
+


+batch
+b&
+out
+

+batch
+dim1
+dim2B
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