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Remove hardcoded value from softmax in flat_pa #280
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looks good, do we have a noticeable throughput loss with this fix?
We had without the workaround to .max() . With it there is a slight drop, but I don't have exact numbers at hand. |
I tested this change on mixtral and accuracy is still fine. Merging then. |
This reverts commit 35a4a98.
This PR removes the hardcoded value used to normalize softmax in flat_pa . Current approach is to use the global maximum as it is very easy to compute, but it has the drawback that other samples in a batch might slightly affect numerical stability. This is a first step to eliminated some of the INF/NaN issues we see in certain configurations and by no means this is a complete solutions. This needs to be revised in the future.
This PR removes the hardcoded value used to normalize softmax in flat_pa . Current approach is to use the global maximum as it is very easy to compute, but it has the drawback that other samples in a batch might slightly affect numerical stability. This is a first step to eliminated some of the INF/NaN issues we see in certain configurations and by no means this is a complete solutions. This needs to be revised in the future.
This PR removes the hardcoded value used to normalize softmax in flat_pa . Current approach is to use the global maximum as it is very easy to compute, but it has the drawback that other samples in a batch might slightly affect numerical stability.
This is a first step to eliminated some of the INF/NaN issues we see in certain configurations and by no means this is a complete solutions. This needs to be revised in the future.