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Signed-off-by: quic-xiyushi <[email protected]>
Signed-off-by: quic-xiyushi <[email protected]>
Signed-off-by: quic-sanising <[email protected]> Signed-off-by: sanising <[email protected]>
Signed-off-by: quic-xiyushi <[email protected]>
Signed-off-by: sanising <[email protected]>
Signed-off-by: sanising <[email protected]>
Signed-off-by: sanising <[email protected]>
Signed-off-by: sanising <[email protected]>
Signed-off-by: sanising <[email protected]>
Signed-off-by: sanising <[email protected]>
Signed-off-by: sanising <[email protected]>
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Depends on #597 |
Signed-off-by: sanising <[email protected]>
Signed-off-by: quic-xiyushi <[email protected]>
Signed-off-by: quic-xiyushi <[email protected]>
Signed-off-by: quic-xiyushi <[email protected]>
Signed-off-by: sanising <[email protected]>
Signed-off-by: quic-xiyushi <[email protected]>
Signed-off-by: sanising <[email protected]>
Signed-off-by: sanising <[email protected]>
Signed-off-by: sanising <[email protected]>
Signed-off-by: quic-xiyushi <[email protected]>
Signed-off-by: sanising <[email protected]>
Signed-off-by: sanising <[email protected]>
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Ready for review |
Signed-off-by: sanising <[email protected]>
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✨ Add Support for Guided Decoding to On Device Sampling
📌 Overview
This PR introduces guided decoding capabilities in On Device Sampling for
QEffForCausalLMandQEffCausalLMForTextImageToTextModelmodels.🚀 Motivation
As outlined in this blog on structured decoding, structured decoding represents a fundamental shift in controlling LLM outputs. Instead of relying on post-processing, constraints are enforced during token generation via logits manipulation. This approach ensures:
The constraints are provided through
token_bitmaskswhich is a Boolean matrix of shape(batch_size, vocab_size). Here, each element indicates whether a token should be kept (1) or masked (0). During sampling, this mask is applied to the logits before token selection, ensuring that only allowed tokens are considered.By performing this operation directly on the device, we eliminate host-device transfers, reduce latency, and improve throughput for structured decoding workloads.
🛠️ Implementation Details
The guided decoding logic is injected via
include_guided_decoding=Trueduring model loading. No changes to the model architecture are required.To disable guided decoding, simply set
include_guided_decoding=False.