ggml-org/llama.cpp b10584

on GitHub

fit: also take into account n_streams (#27496)

• fit: also take into account n_streams

• server: make the draft context follow the target context

With a non-unified KV cache the target context now holds n_ctx_train
tokens per sequence, while the draft context was still created with
n_ctx = 0 and fell back to n_ctx_train / n_streams per sequence. A slot
filled beyond that point makes the draft batch fail to decode, and the
server answers 500 on the request.

The draft context now takes its size from the target context, so both
hold the same number of tokens per sequence. Contexts that share their
cells with the target no longer need the kv_size override.

The memory reserved for the draft model before fitting is measured at
the largest context the target can take, since the draft context grows
with the target and a fixed byte margin cannot express that.

• fit: take an optional second model into account

Illustrates the alternative discussed on the draft context fix. The
memory of a draft or MTP context is currently handed to the fit as a
fixed byte margin, which cannot express a memory that grows with the
context the fit is still deciding on.

common_fit_params now takes an optional second model that shares the
devices of the main one. Its context follows the main context and its
memory is measured again whenever that context changes, so the reduce
path stays exact instead of conservative. A model that cannot be
measured on its own, such as a shared cell MTP context, is skipped with
a warning and the main model is fitted alone.

This drops the reservation block in the server, which no longer has to
probe the trained context size of the target to guess an upper bound.

Co-authored-by: Pascal admin@serveurperso.com