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Merge commit '2f966b8ed8' into concedo_experimental

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# Conflicts:
#	.github/workflows/release.yml
#	docs/docker.md
#	ggml/src/CMakeLists.txt
#	ggml/src/ggml-cpu/CMakeLists.txt
#	tests/test-backend-ops.cpp
#	tests/test-thread-safety.cpp
#	tools/batched-bench/batched-bench.cpp
#	tools/mtmd/clip.cpp
This commit is contained in:
LostRuins Concedo 2025-11-08 10:34:17 +08:00
commit fdcb281a3a
31 changed files with 655 additions and 165 deletions
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37
src/llama-context.cpp
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@ -112,11 +112,24 @@ llama_context::llama_context(
}
}
const uint32_t n_ctx_per_seq = cparams.n_ctx / cparams.n_seq_max;
if (cparams.kv_unified) {
cparams.n_ctx_seq = cparams.n_ctx;
} else {
cparams.n_ctx_seq = cparams.n_ctx / cparams.n_seq_max;
if (cparams.n_ctx_seq == 0) {
throw std::runtime_error("n_ctx_seq == 0");
}
if (cparams.n_ctx != cparams.n_ctx_seq * cparams.n_seq_max) {
cparams.n_ctx = cparams.n_ctx_seq * cparams.n_seq_max;
LLAMA_LOG_WARN("%s: n_ctx is not divisible by n_seq_max - rounding down to %u\n", __func__, cparams.n_ctx);
}
}
LLAMA_LOG_INFO("%s: n_seq_max = %u\n", __func__, cparams.n_seq_max);
LLAMA_LOG_INFO("%s: n_ctx = %u\n", __func__, cparams.n_ctx);
LLAMA_LOG_INFO("%s: n_ctx_per_seq = %u\n", __func__, n_ctx_per_seq);
LLAMA_LOG_INFO("%s: n_ctx_seq = %u\n", __func__, cparams.n_ctx_seq);
LLAMA_LOG_INFO("%s: n_batch = %u\n", __func__, cparams.n_batch);
LLAMA_LOG_INFO("%s: n_ubatch = %u\n", __func__, cparams.n_ubatch);
LLAMA_LOG_INFO("%s: causal_attn = %d\n", __func__, cparams.causal_attn);
@ -125,14 +138,14 @@ llama_context::llama_context(
LLAMA_LOG_INFO("%s: freq_base = %.1f\n", __func__, cparams.rope_freq_base);
LLAMA_LOG_INFO("%s: freq_scale = %g\n", __func__, cparams.rope_freq_scale);
if (n_ctx_per_seq < hparams.n_ctx_train) {
LLAMA_LOG_WARN("%s: n_ctx_per_seq (%u) < n_ctx_train (%u) -- the full capacity of the model will not be utilized\n",
__func__, n_ctx_per_seq, hparams.n_ctx_train);
if (cparams.n_ctx_seq < hparams.n_ctx_train) {
LLAMA_LOG_WARN("%s: n_ctx_seq (%u) < n_ctx_train (%u) -- the full capacity of the model will not be utilized\n",
__func__, cparams.n_ctx_seq, hparams.n_ctx_train);
}
if (n_ctx_per_seq > hparams.n_ctx_train) {
LLAMA_LOG_WARN("%s: n_ctx_per_seq (%u) > n_ctx_train (%u) -- possible training context overflow\n",
__func__, n_ctx_per_seq, hparams.n_ctx_train);
if (cparams.n_ctx_seq > hparams.n_ctx_train) {
LLAMA_LOG_WARN("%s: n_ctx_seq (%u) > n_ctx_train (%u) -- possible training context overflow\n",
__func__, cparams.n_ctx_seq, hparams.n_ctx_train);
}
if (!hparams.vocab_only) {
@ -455,8 +468,8 @@ uint32_t llama_context::n_ctx() const {
return cparams.n_ctx;
}
uint32_t llama_context::n_ctx_per_seq() const {
return cparams.n_ctx / cparams.n_seq_max;
uint32_t llama_context::n_ctx_seq() const {
return cparams.n_ctx_seq;
}
uint32_t llama_context::n_batch() const {
@ -2385,6 +2398,10 @@ uint32_t llama_n_ctx(const llama_context * ctx) {
return ctx->n_ctx();
}
uint32_t llama_n_ctx_seq(const llama_context * ctx) {
return ctx->n_ctx_seq();
}
uint32_t llama_n_batch(const llama_context * ctx) {
return ctx->n_batch();
}