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
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.
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:
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...
The maximum value for either of the parts is 65534, as you read here. This is a limit imposed by the operating system, so not even specific to .NET. Windows puts the version numbers into two integers, which together form four unsigned shorts. Adding some metadata to it (for the * option I guess) makes the maximum allowed value UInt16.MaxValue - 1 = 65534 (Thanks to Gary Walker for noticing ...
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.
torch.backends.cudnn.deterministic=True only applies to CUDA convolution operations, and nothing else. Therefore, no, it will not guarantee that your training process is deterministic, since you're also using torch.nn.MaxPool3d, whose backward function is nondeterministic for CUDA. torch.set_deterministic(), on the other hand, affects all the normally-nondeterministic operations listed here ...
When I attempt to publish my package using NuGet Package Explorer, I see the following warning: Deterministic (dll/exe): Non deterministic Ensure that the following property is enabled for CI build...
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.
