[tools/onnx-subgraph] add onnx inference verification code

tools/onnx_subgraph/CMakeLists.txt

@@ -18,6 +18,7 @@ set(ONNX_SUBGRAPH_FILES
     test_model_download.sh
     extract_onnx.py
     subgraphs_ios.txt
+    single_vs_multiple_onnx.py
 )
 foreach(ONNX_SUBGRAPH IN ITEMS ${ONNX_SUBGRAPH_FILES})
     set(ONNX_SUBGRAPH_FILE ${ONNX_SUBGRAPH})

tools/onnx_subgraph/single_vs_multiple_onnx.py

@@ -0,0 +1,75 @@
+# Copyright (c) 2025 Samsung Electronics Co., Ltd. All Rights Reserved
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import onnxruntime as ort
+import numpy as np
+import os
+import re
+import argparse
+
+
+class ModelInference:
+    """
+    This class is used to infer multiple onnx models.
+    Parameters:
+        model_path: Path to the model files.
+        subgraphsiostxt_path: Path to the txt file that describes the structure of the model graph.
+    Output:
+        outputs[0]: Inference result from the model.
+    Description:
+        Subgraphsiostxt_path is a txt file that describes the structure of the model graph and
+        is used to get input/output node names.The model_path contains paths to multiple onnx files.
+        The load_sessions function will sort the onnx models in the model_path according to the 
+        order specified in subgraphsiostxt_path.
+    """
+    def __init__(self, model_path, subgraphsiostxt_path):
+        self.model_path = model_path
+        self.subgraphsiostxt_path = subgraphsiostxt_path
+
+    def infer_single_onnx_model(model_file, input_data):
+        session = ort.InferenceSession(model_file)
+        outputs = session.run(None, input_data)
+        output_names = [output.name for output in session.get_outputs()]
+        output_dict = {name: output for name, output in zip(output_names, outputs)}
+        return output_dict
+
+
+if __name__ == "__main__":
+    arg_parser = argparse.ArgumentParser()
+    arg_parser.add_argument('-s',
+                            '--single',
+                            default='./resnet-test.onnx',
+                            help="set single ONNX model path")
+    arg_parser.add_argument('-m',
+                            '--multi',
+                            default='./subgraphs/',
+                            help="set split subgraph models path")
+    arg_parser.add_argument('-n',
+                            '--node',
+                            default='./scripts/subgraphs_ios.txt',
+                            help="set subgraphs node i/o information")
+    args = arg_parser.parse_args()
+
+    # Initialize ModelInference instance for inference
+    model_inference = ModelInference(args.multi, args.node)
+
+    # Default input data dictionary
+    default_input_data = {
+        "x": np.random.rand(1, 3, 256, 256).astype(np.float32),
+    }
+
+    # Perform inference using a single ONNX model
+    output_single = ModelInference.infer_single_onnx_model(args.single,
+                                                           default_input_data)
+    print("Single model inference completed!")