How could I convert output tensor to text generation?

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Question

text/machine_comprehension/gpt-2/dependencies/GPT2-export.py

I succeeded in extracting the output tensor value for the example input text using the above example. Furthermore, I need advice on how to run text generation using output tensor values. Is there a code or a link I can refer to? (Pytorch or python code..)

The code I tried is as follows. But it didn't work.

'ort_outputs_exmodel' above image is same as 'res' link below https://github.com/onnx/models/blob/ad5c181f1646225f034fba1862233ecb4c262e04/text/machine_comprehension/gpt-2/dependencies/GPT2-export.py#L110

My final goal of the project is to load the onnx model using onnx runtime's C/C++ API and write the C/C++ code to generate text using output tensor values.

I'll be waiting for your reply. (looking forward to...)
Thank u very much.

Further information

Relevant Area (e.g. model usage, backend, best practices, pre-/post- processing, converters):

Is this issue related to a specific model?
Model name (e.g. mnist): gpt-2
Model opset (e.g. 7):

Notes

Any additional information, code snippets.

Start with text/machine_comprehension/gpt-2/dependencies/GPT2-export.py, especially the output referenced at line 110, and review the reported output tensor and attempted code. Determine whether the repository can provide a documented path or example for turning GPT-2 output into generated text through the C/C++ API. Done means the expected tensor-to-text workflow and a working reference are documented.