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We need a more deterministic way to benchmark the performance, so I'm thinking about adding a tool that runs just the Encoder part of the transformer on random noise input. This has the advantage that one does not require any audio data to run and the number of operations is fixed (as opposed to when running the Decoder).
The text was updated successfully, but these errors were encountered:
Very good idea for testing performance directly of speed up only computation part.
But in some cases steel need check overal model performance - if quality of model somehow dropped, then its can run slowly (bc decoder trying get good answer). But it depends on decoder type, parameters of decoder...
We need a more deterministic way to benchmark the performance, so I'm thinking about adding a tool that runs just the Encoder part of the transformer on random noise input. This has the advantage that one does not require any audio data to run and the number of operations is fixed (as opposed to when running the Decoder).
The text was updated successfully, but these errors were encountered: