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llama : move n_vocab from llama_sampler_data to penalty_sampler (#26520)

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This matches how it is done for logit_bias and mirostat samplers, see
https://github.com/ggml-org/llama.cpp/pull/25262#discussion_r3703951151
This commit is contained in:
Oliver Simons
2026-08-04 09:02:49 +03:00
committed by GitHub
parent 22dc605c4e
commit 935cad6497
6 changed files with 16 additions and 13 deletions
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src/llama-graph.cpp
-1
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@@ -3683,7 +3683,6 @@ void llm_graph_context::build_sampling() const {
/*.probs =*/ nullptr,
/*.sampled =*/ nullptr,
/*.candidates =*/ nullptr,
/*.n_vocab =*/ logits_seq->ne[0],
};
assert(sampler->iface->backend_apply);
src/llama-sampler.cpp
+7 -4
View File
@@ -589,7 +589,6 @@ static bool llama_sampler_backend_support(
/*.probs = */ nullptr,
/*.sampled = */ nullptr,
/*.candidates = */ ggml_new_tensor_1d(ctx, GGML_TYPE_I32, n),
/*.n_vocab = */ n,
};
ggml_cgraph * gf = ggml_new_graph(ctx);
@@ -2640,6 +2639,7 @@ struct llama_sampler * llama_sampler_init_grammar_lazy_patterns(
// penalties
struct llama_sampler_penalties : public llama_sampler_backend {
const int32_t n_vocab;
const int32_t penalty_last_n;
const float penalty_repeat;
const float penalty_freq;
@@ -2655,7 +2655,6 @@ struct llama_sampler_penalties : public llama_sampler_backend {
ggml_tensor * inp_counts = nullptr;
// backend helpers
int32_t n_vocab = 0;
int32_t n_max = 0;
bool has_candidates = false;
@@ -2676,11 +2675,13 @@ struct llama_sampler_penalties : public llama_sampler_backend {
}
llama_sampler_penalties(
int32_t n_vocab,
int32_t penalty_last_n,
float penalty_repeat,
float penalty_freq,
float penalty_present)
: llama_sampler_backend("penalties")
, n_vocab (n_vocab)
, penalty_last_n (penalty_last_n)
, penalty_repeat (penalty_repeat)
, penalty_freq (penalty_freq)
@@ -2766,6 +2767,7 @@ static void llama_sampler_penalties_reset(struct llama_sampler * smpl) {
static struct llama_sampler * llama_sampler_penalties_clone(const struct llama_sampler * smpl) {
const auto * ctx = (const llama_sampler_penalties *) smpl->ctx;
auto * result = llama_sampler_init_penalties(
ctx->n_vocab,
ctx->penalty_last_n,
ctx->penalty_repeat,
ctx->penalty_freq,
@@ -2811,10 +2813,9 @@ static void llama_sampler_penalties_backend_apply(
return;
}
GGML_ASSERT(data->n_vocab > 0 && data->n_vocab <= INT32_MAX);
GGML_ASSERT(sctx->n_vocab > 0);
sctx->has_candidates = data->candidates != nullptr;
sctx->n_vocab = (int32_t) data->n_vocab;
sctx->n_max = std::min(sctx->penalty_last_n, sctx->n_vocab);
sctx->inp_token_ids = ggml_new_tensor_1d(ctx, GGML_TYPE_I32, sctx->n_max);
@@ -2965,6 +2966,7 @@ static struct llama_sampler_i llama_sampler_penalties_i = {
};
struct llama_sampler * llama_sampler_init_penalties(
int32_t n_vocab,
int32_t penalty_last_n,
float penalty_repeat,
float penalty_freq,
@@ -2979,6 +2981,7 @@ struct llama_sampler * llama_sampler_init_penalties(
return llama_sampler_init(
/* .iface = */ &llama_sampler_penalties_i,
/* .ctx = */ new llama_sampler_penalties(
n_vocab,
penalty_last_n,
penalty_repeat,
penalty_freq,