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3 changes: 2 additions & 1 deletion tools/onnx_subgraph/CMakeLists.txt
Original file line number Diff line number Diff line change
Expand Up @@ -14,10 +14,11 @@ find_package(Python3 COMPONENTS Interpreter Development REQUIRED)
include_directories(${CMAKE_CURRENT_BINARY_DIR})
include_directories(${Python3_INCLUDE_DIRS})

set(ONNX_SUBGRAPH_FILES
set(ONNX_SUBGRAPH_FILES

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plz split this space deletion, that doesn't seem to be related to this commit, to another PR.

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plz split this space deletion, that doesn't seem to be related to this commit, to another PR.

when I add single_vs_multiple_onnx.py to CMakeLists in line 21, I found there are some white blanks nearby, so I removed them, can you please consider it as the related updating of line 21? thank you :)

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Plz post to another PR.

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ok, I recovered it now, thank you

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})
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74 changes: 74 additions & 0 deletions tools/onnx_subgraph/single_vs_multiple_onnx.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,74 @@
# 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.

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above two line seems to exceed 100 cols. plz split lines.

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yes, I update it now, thank you :)

"""
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),

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Q) input has fixed shape and data type. if the input model requires differnt parameters, can this be valid ?

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yes, you are right, actually, I am considering to have dynamic adaptive input according to onnx input shape, it needs more code, I will post this code in next PR

}

# Perform inference using a single ONNX model
output_single = ModelInference.infer_single_onnx_model(args.single,
default_input_data)
print("Single model inference completed!")