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llama.cpp
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mtp-batch(chore): Remove final MTP debug logs and dead code

This commit is contained in:
samuel 2025-10-11 22:20:54 -03:00
parent 4bcc9e261e
commit 0127c6beeb
3 changed files with 5 additions and 56 deletions
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43
src/llama-context.cpp
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@ -13,7 +13,6 @@
#include <cstring>
#include <limits>
#include <stdexcept>
#include <numeric>
//
// llama_context
@ -738,17 +737,6 @@ bool llama_context::apply_adapter_cvec(
return cvec.apply(model, data, len, n_embd, il_start, il_end);
}
static double calculate_vector_sum(const float* vec, size_t size) {
if (!vec) {
return 0.0;
}
double sum = 0.0;
for (size_t i = 0; i < size; ++i) {
sum += vec[i];
}
return sum;
}
llm_graph_result * llama_context::process_ubatch(const llama_ubatch & ubatch, llm_graph_type gtype, llama_memory_context_i * mctx, ggml_status & ret,
const llama_mtp_params & mtp_params) {
if (mctx && !mctx->apply()) {
@ -995,10 +983,6 @@ int llama_context::decode(const llama_batch & batch_inp) {
GGML_ASSERT((!batch_inp.token && batch_inp.embd) || (batch_inp.token && !batch_inp.embd)); // NOLINT
auto * kvd = static_cast<llama_context_kv_cache_data *>(kv_cache_data);
// LLAMA_LOG_WARN("[DEBUG-DECODE-ENTRY] Entering llama_decode. update_mtp_kv=%s, use_mtp_head=%s\n",
// batch_inp.update_mtp_kv ? "true" : "false",
// batch_inp.use_mtp_head ? "true" : "false"
// );
if (!memory) {
LLAMA_LOG_DEBUG("%s: cannot decode batches with this context (calling encode() instead)\n", __func__);
@ -1074,10 +1058,10 @@ int llama_context::decode(const llama_batch & batch_inp) {
}
case LLAMA_MEMORY_STATUS_FAILED_PREPARE:
{
// if (use_last_main_model_sinfos) {
// LLAMA_LOG_ERROR("%s: Mismatch between ubatches and sinfos during reuse.\n", __func__);
// return -1;
// }
if (kvd->forced_sinfos) {
LLAMA_LOG_ERROR("%s: Mismatch between ubatches and sinfos during reuse.\n", __func__);
return -1;
}
if (!did_optimize) {
did_optimize = true;
@ -1106,9 +1090,6 @@ int llama_context::decode(const llama_batch & batch_inp) {
};
int64_t n_outputs_prev = 0;
// const bool do_mtp_kv_update = batch_inp.update_mtp_kv;
// const bool use_mtp_head = batch_inp.use_mtp_head;
// const bool is_prompt_warmup = batch_inp.is_mtp_prompt_warmup;
do {
const auto & ubatch = mctx->get_ubatch();
@ -1127,14 +1108,6 @@ int llama_context::decode(const llama_batch & batch_inp) {
// needs to happen before the graph is built
n_outputs = n_outputs_new;
}
// if (do_mtp_kv_update) {
// LLAMA_LOG_WARN("[DEBUG-MTP-UPDATE] MTP KV Update ubatch: n_tokens=%d\n", ubatch.n_tokens);
// std::string positions_str;
// for (int i = 0; i < std::min((uint32_t)5, ubatch.n_tokens); ++i) {
// positions_str += std::to_string(ubatch.pos[i]) + " ";
// }
// LLAMA_LOG_WARN("[DEBUG-MTP-UPDATE] Positions: %s...\n", positions_str.c_str());
// }
ggml_status status;
const auto * res = process_ubatch(ubatch, LLM_GRAPH_TYPE_DECODER, mctx.get(), status, batch_inp.mtp_params);
if (!res) {
@ -1195,14 +1168,6 @@ int llama_context::decode(const llama_batch & batch_inp) {
}
}
// if (use_mtp_head) {
// if (t_embd != nullptr) {
// LLAMA_LOG_ERROR("[MTP-GRAPH-BUG] The MTP graph returned an embedding tensor when it shouldn't have! This will cause corruption.\n");
// } else {
// LLAMA_LOG_WARN("[MTP-GRAPH-OK] The MTP graph correctly did not return an embedding tensor.\n");
// }
// }
// extract embeddings
if (t_embd && n_outputs > 0) {
if (batch_inp.mtp_params.op_type == MTP_OP_NONE) {

16
src/llama-model.cpp
View File

@ -13829,11 +13829,6 @@ struct llm_build_glm4_moe : public llm_graph_context {
// Final layer tensors are loaded but not processed in forward pass
const int n_transformer_layers = n_layer - hparams.nextn_predict_layers;
for (int il = 0; il < n_transformer_layers; ++il) {
// if (params.use_mtp_head) {
// LLAMA_LOG_ERROR("[DEBUG-KV-ERROR] MTP path is running the main layer %d!\n", il);
// } else {
// LLAMA_LOG_WARN("[DEBUG-KV] Main Head Path: Accessing layer %d\n", il);
// }
ggml_tensor * inpSA = inpL;
// Pre-attention norm
@ -13976,7 +13971,6 @@ private:
ggml_tensor * embd_copy = ggml_dup(ctx0, prev_embeddings);
const int il = hparams.n_layer - 1;
// LLAMA_LOG_WARN("[DEBUG-KV] MTP Head Path: Accessing layer %d\n", il);
ggml_tensor * sum_node = ggml_sum(ctx0, embd_copy);
ggml_set_name(sum_node, "mtp_input_sum");
@ -18311,12 +18305,8 @@ llama_memory_i * llama_model::create_memory(const llama_memory_params & params,
}
ggml_cgraph * llama_model::build_graph(const llm_graph_params & params) const {
const int64_t t_start_us = ggml_time_us();
std::unique_ptr<llm_graph_context> llm;
const bool build_mtp = params.mtp_params.op_type == MTP_OP_UPDATE_ACCEPTED;
switch (arch) {
case LLM_ARCH_LLAMA:
{
@ -18678,12 +18668,6 @@ ggml_cgraph * llama_model::build_graph(const llm_graph_params & params) const {
// add on pooling layer
llm->build_pooling(cls, cls_b, cls_out, cls_out_b);
}
const int64_t t_end_us = ggml_time_us();
// LLAMA_LOG_INFO(
// "[PERF] Graph build time: %.2f ms (MTP path: %s)\n",
// (t_end_us - t_start_us) / 1000.0,
// params.use_mtp_head ? "yes" : "no"
// );
return llm->res->get_gf();
}

2
tools/server/server.cpp
View File

@ -3520,7 +3520,7 @@ struct server_context {
// Clean up the forced state to not affect subsequent decodes.
llama_mtp_cancel_sinfo_update(ctx);
} else {
LOG_ERR("%s: Failed to prepare the MTP symphony for warmup.", __func__);
LOG_ERR("%s: Failed to prepare the MTP for warmup.", __func__);
}
}