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llama.cpp
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graph : clean up t5 input builders (#18795) 

* fix: Remove unnecessary `h` loops where `h` was only ever 0

Branch: CleanUpT5InputBuilders

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* fix: Remove unnecessary padding loop that is never hit anymore

The upper bound used to use GGML_PAD(n_tokens, GGML_KQ_MASK_PAD), but was
removed in https://github.com/ggml-org/llama.cpp/pull/17910 leaving the
loop dead.

Branch: CleanUpT5InputBuilders

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

---------

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
This commit is contained in:
Gabe Goodhart 2026-01-13 01:43:51 -07:00 committed by GitHub
parent db79dc06b1
commit 076b0faf7d
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1 changed files with 33 additions and 45 deletions
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78
src/llama-graph.cpp
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@ -96,11 +96,9 @@ void llm_graph_input_pos_bucket::set_input(const llama_ubatch * ubatch) {
int32_t * data = (int32_t *) pos_bucket->data;
for (int h = 0; h < 1; ++h) {
for (int j = 0; j < n_tokens; ++j) {
for (int i = 0; i < n_tokens; ++i) {
data[h*(n_tokens*n_tokens) + j*n_tokens + i] = llama_relative_position_bucket(ubatch->pos[i], ubatch->pos[j], hparams.n_rel_attn_bkts, true);
}
for (int j = 0; j < n_tokens; ++j) {
for (int i = 0; i < n_tokens; ++i) {
data[j*n_tokens + i] = llama_relative_position_bucket(ubatch->pos[i], ubatch->pos[j], hparams.n_rel_attn_bkts, true);
}
}
}
@ -323,34 +321,32 @@ void llm_graph_input_attn_no_cache::set_input(const llama_ubatch * ubatch) {
const int64_t n_tokens = ubatch->n_tokens;
const auto fill_mask = [&](float * data, int n_swa, llama_swa_type swa_type) {
for (int h = 0; h < 1; ++h) {
for (int i1 = 0; i1 < n_tokens; ++i1) {
const llama_seq_id s1 = ubatch->seq_id[i1][0];
const llama_pos p1 = ubatch->pos[i1];
for (int i1 = 0; i1 < n_tokens; ++i1) {
const llama_seq_id s1 = ubatch->seq_id[i1][0];
const llama_pos p1 = ubatch->pos[i1];
const uint64_t idst = h*(n_kv*n_tokens) + i1*n_kv;
const uint64_t idst = i1*n_kv;
for (int i0 = 0; i0 < n_tokens; ++i0) {
const llama_seq_id s0 = ubatch->seq_id[i0][0];
const llama_pos p0 = ubatch->pos[i0];
for (int i0 = 0; i0 < n_tokens; ++i0) {
const llama_seq_id s0 = ubatch->seq_id[i0][0];
const llama_pos p0 = ubatch->pos[i0];
// mask different sequences
if (s0 != s1) {
continue;
}
// mask future tokens
if (cparams.causal_attn && p0 > p1) {
continue;
}
// apply SWA if any
if (llama_hparams::is_masked_swa(n_swa, swa_type, p0, p1)) {
continue;
}
data[idst + i0] = hparams.use_alibi ? -std::abs(p0 - p1) : 0.0f;
// mask different sequences
if (s0 != s1) {
continue;
}
// mask future tokens
if (cparams.causal_attn && p0 > p1) {
continue;
}
// apply SWA if any
if (llama_hparams::is_masked_swa(n_swa, swa_type, p0, p1)) {
continue;
}
data[idst + i0] = hparams.use_alibi ? -std::abs(p0 - p1) : 0.0f;
}
}
};
@ -454,27 +450,19 @@ void llm_graph_input_attn_cross::set_input(const llama_ubatch * ubatch) {
float * data = (float *) cross_kq_mask->data;
for (int h = 0; h < 1; ++h) {
for (int i = 0; i < n_tokens; ++i) {
for (int j = 0; j < n_enc; ++j) {
float f = -INFINITY;
for (int i = 0; i < n_tokens; ++i) {
for (int j = 0; j < n_enc; ++j) {
float f = -INFINITY;
for (int s = 0; s < ubatch->n_seq_id[i]; ++s) {
const llama_seq_id seq_id = ubatch->seq_id[i][s];
for (int s = 0; s < ubatch->n_seq_id[i]; ++s) {
const llama_seq_id seq_id = ubatch->seq_id[i][s];
if (cross->seq_ids_enc[j].find(seq_id) != cross->seq_ids_enc[j].end()) {
f = 0.0f;
}
if (cross->seq_ids_enc[j].find(seq_id) != cross->seq_ids_enc[j].end()) {
f = 0.0f;
}
data[h*(n_enc*n_tokens) + i*n_enc + j] = f;
}
}
for (int i = n_tokens; i < n_tokens; ++i) {
for (int j = 0; j < n_enc; ++j) {
data[h*(n_enc*n_tokens) + i*n_enc + j] = -INFINITY;
}
data[i*n_enc + j] = f;
}
}
}