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Will a future update be able to fix the random number seed during inference as well?
Describe scenario use case
Hi, I am making a C++ program for inference with a neural network model.
The neural network model includes a module that generates random numbers (RandomNormalLike).
Therefore, the output values are slightly different even for the same input.
I want to implement a function that turns this randomness on and off.
Example: We would like to store and use the seed of an excellent result.
Looking at the API reference, it seems that the SetSeed() function can be used to fix the random number seed during training (onnxruntime_training_c_api.h), but it is not available during inference (onnxruntime_cxx_api.h). https://onnxruntime.ai/docs/api/c/namespace_ort.html
The text was updated successfully, but these errors were encountered:
Describe the feature request
Will a future update be able to fix the random number seed during inference as well?
Describe scenario use case
Hi, I am making a C++ program for inference with a neural network model.
The neural network model includes a module that generates random numbers (
RandomNormalLike
).Therefore, the output values are slightly different even for the same input.
I want to implement a function that turns this randomness on and off.
Example: We would like to store and use the seed of an excellent result.
Looking at the API reference, it seems that the
SetSeed()
function can be used to fix the random number seed during training (onnxruntime_training_c_api.h
), but it is not available during inference (onnxruntime_cxx_api.h
).https://onnxruntime.ai/docs/api/c/namespace_ort.html
The text was updated successfully, but these errors were encountered: