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2 Commits

Author SHA1 Message Date
Georgi Gerganov
29acf2cf05 context : move the change to llama_context::encode()
ggml-ci
2025-03-18 11:55:19 +02:00
Georgi Gerganov
a0554c3cdc context : always use non-causal attention for encoder graphs
ggml-ci
2025-03-18 11:14:48 +02:00

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@@ -1057,6 +1057,13 @@ int llama_context::encode(llama_batch & inp_batch) {
ggml_backend_sched_reset(sched.get());
ggml_backend_sched_set_eval_callback(sched.get(), cparams.cb_eval, cparams.cb_eval_user_data);
const auto causal_attn_org = cparams.causal_attn;
// always use non-causal attention for encoder graphs
// TODO: this is a tmp solution until we have a proper way to support enc-dec models
// ref: https://github.com/ggml-org/llama.cpp/pull/12181#issuecomment-2730451223
cparams.causal_attn = false;
auto * gf = graph_init();
auto res = graph_build(ctx_compute.get(), gf, ubatch, LLM_GRAPH_TYPE_ENCODER);
@@ -1064,6 +1071,8 @@ int llama_context::encode(llama_batch & inp_batch) {
res->set_inputs(&ubatch);
cparams.causal_attn = causal_attn_org;
const auto compute_status = graph_compute(gf, n_tokens > 1);
switch (compute_status) {
case GGML_STATUS_SUCCESS: