pyannote-pipeline

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Here are a few things the callback function might do: * every time a better set of hyper-parameters is found, run a validation experiment (possibly asynchronously) * log trial details...

hbredin

If `params` does not provide value for frozen hyper-parameters, add them first... https://github.com/pyannote/pyannote-pipeline/blob/ee2217f014a738d63233e3182d97876db671579c/pyannote/pipeline/pipeline.py#L369

hbredin

fix: #52 - should_prune() takes no argument

2

This fixes the mentionned issue by removing the argument passed to `Trial.should_prune()`

arxaqapi

Simply added the missing import back to [optimizer.py#L46](https://github.com/arxaqapi/pyannote-pipeline/blob/fix_scipy_stats/pyannote/pipeline/optimizer.py#L46).

arxaqapi

Error when using a pruner in the Optimizer

1

The following error is encountered `Trial.should_prune() takes 1 positional argument but 2 were given` when running an Optimizer instance created using a pruner like seen below: ```python optimizer = Optimizer(pipeline,...

arxaqapi