Instructions to use CatSnowdrop/universal_onnxruntime with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TensorRT
How to use CatSnowdrop/universal_onnxruntime with TensorRT:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
File size: 994 Bytes
610d9c2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 | import argparse
import onnx
def get_args():
parser = argparse.ArgumentParser()
parser.add_argument("--input", required=True, help="input model")
parser.add_argument("--output", required=True, help="output model")
args = parser.parse_args()
return args
def remove_initializer_from_input(model: onnx.ModelProto) -> bool:
if model.ir_version < 4:
print("Model with ir_version below 4 requires to include initializer in graph input")
return False
inputs = model.graph.input
name_to_input = {}
for input in inputs:
name_to_input[input.name] = input
modified = False
for initializer in model.graph.initializer:
if initializer.name in name_to_input:
modified = True
inputs.remove(name_to_input[initializer.name])
return modified
if __name__ == "__main__":
args = get_args()
model = onnx.load(args.input)
remove_initializer_from_input(model)
onnx.save(model, args.output)
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