The spec does not mandate buffer limits for tee(). And to be fair, the spec allows implementations to implement the actual internal mechanisms for tee()and other APIs in any way they see fit so long as the observable normative requirements of the specification are met. But if an implementation chooses to implement tee() in the specific way described by the streams specification, then tee() will come with a built-in memory management issue that is difficult to work around.
Measured on Apple M3 16GB with simulated audio input (Tensor::randn). Times are per-encoder-forward-pass (Sortformer: full forward pass).
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