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- Non determinism problem in TensorFlow 2. 16. 1 - Stack Overflow
Non determinism problem in TensorFlow 2 16 1 Asked 1 year, 2 months ago Modified 1 year, 2 months ago Viewed 227 times
- AssemblyVersion using * fails with error wildcards, which are not . . .
The specified version string contains wildcards, which are not compatible with determinism Either remove wildcards from the version string, or disable determinism for this compilation
- non deterministic - Seeking Assistance on Achieving Determinism in . . .
I’m currently working on a project that requires generating 100% reproducible outputs from OpenAI’s GPT-4 model for the same input prompt Despite experimenting with various parameters like tempera
- Can OpenAI chat completions be fully deterministic?
Can floats that the tensors are made of be fully deterministic? :) For "full determinism" there would have to be a KV cache on their side It might be possible to implement it yourself (depending on your scenario) to achieve what you are looking for
- How to handle non-determinism when training on a GPU?
29 TL;DR Non-determinism for a priori deterministic operations come from concurrent (multi-threaded) implementations Despite constant progress on that front, TensorFlow does not currently guarantee determinism for all of its operations After a quick search on the internet, it seems that the situation is similar to the other major toolkits
- Edit deterministic value in WinForms desktop application project to . . .
2 In C# WinForms desktop application, according The specified version string contains wildcards, which are not compatible with determinism I've to change <Deterministic>True< Deterministic> to false in myproj csproj to increment version with asterisk:
- Unity is showing different physics behaviour while building for . . .
In order to enhance determinism, you can check 'Enable Enhanced Determinism' in Edit -> Project settings -> Physics -> Enable Enhanced Determinism checkbox However, Unity does not use integer-based physics, and so can never be deterministic You will never be able to make a ball bounce the exact same way Your problem stems from the fact that you probably have not set your target framerate of
- Azure OpenAI gpt-35-turbo nondeterministic with temperature 0
I thought the idea with setting temperature to 0 meant consistent (deterministic) responses (given the same model) Is that not the case? It's indeed not the case 2 reasons: GPU non-determinism This blogpost authored by Sherman Chann argues that "Non-determinism in GPT-4 is caused by Sparse MoE [mixture of experts]"
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