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hparams : refactor hparams.n_layer (#24060)

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* hparams : refactor hparams.n_layer

* cont : remove `n_layer_kv()`, use n_layer_all instead

* cont : type consistency

* pi : update SYSTEM.md

* models : fix Step3.5 MTP

* cont : remove duplicate switch cases

* cont : explicitly set `false` to extra layers for `is_swa` and `is_recr`

* cont : fix nextn layer count handling

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

---------

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
This commit is contained in:
Georgi Gerganov
2026-06-05 11:09:36 +03:00
committed by GitHub
parent 3ecfb150a4
commit 7acb4e8cd2
129 changed files with 412 additions and 431 deletions
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36
src/models/step35.cpp
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@@ -23,16 +23,16 @@ void llama_model_step35::load_arch_hparams(llama_model_loader & ml) {
ml.get_key(LLM_KV_ATTENTION_SLIDING_WINDOW, hparams.n_swa);
ml.get_key(LLM_KV_ROPE_FREQ_BASE_SWA, hparams.rope_freq_base_train_swa, false);
ml.get_key_or_arr(LLM_KV_ATTENTION_SLIDING_WINDOW_PATTERN, hparams.is_swa_impl, hparams.n_layer);
ml.get_key_or_arr(LLM_KV_ATTENTION_SLIDING_WINDOW_PATTERN, hparams.is_swa_impl, hparams.n_layer());
ml.get_key_or_arr(LLM_KV_SWIGLU_CLAMP_EXP, hparams.swiglu_clamp_exp, hparams.n_layer, false);
ml.get_key_or_arr(LLM_KV_SWIGLU_CLAMP_SHEXP, hparams.swiglu_clamp_shexp, hparams.n_layer, false);
ml.get_key_or_arr(LLM_KV_SWIGLU_CLAMP_EXP, hparams.swiglu_clamp_exp, hparams.n_layer(), false);
ml.get_key_or_arr(LLM_KV_SWIGLU_CLAMP_SHEXP, hparams.swiglu_clamp_shexp, hparams.n_layer(), false);
// NextN/MTP (Step3p5): extra decoder block appended beyond the main stack.
ml.get_key(LLM_KV_NEXTN_PREDICT_LAYERS, hparams.nextn_predict_layers, false);
GGML_ASSERT(hparams.nextn_predict_layers < hparams.n_layer && "nextn_predict_layers must be < n_layer");
ml.get_key(LLM_KV_NEXTN_PREDICT_LAYERS, hparams.n_layer_nextn, false);
GGML_ASSERT(hparams.n_layer_nextn < hparams.n_layer_all && "n_layer_nextn must be < n_layer_impl");
switch (hparams.n_layer - hparams.nextn_predict_layers) {
switch (hparams.n_layer()) {
case 45: type = LLM_TYPE_196B_A11B; break;
default: type = LLM_TYPE_UNKNOWN;
}
@@ -41,15 +41,12 @@ void llama_model_step35::load_arch_hparams(llama_model_loader & ml) {
void llama_model_step35::load_arch_tensors(llama_model_loader & ml) {
LLAMA_LOAD_LOCALS;
const uint32_t n_main = n_layer - hparams.nextn_predict_layers;
const bool mtp_only = (hparams.nextn_predict_layers > 0) &&
(ml.get_weight("blk.0.attn_norm.weight") == nullptr);
const bool mtp_only = (hparams.n_layer_nextn > 0) && (ml.get_weight("blk.0.attn_norm.weight") == nullptr);
// Trunk-only: the GGUF declares MTP layers in metadata but the actual MTP
// tensors live in a separate file (e.g. user split target/draft). Mark
// MTP tensors NOT_REQUIRED so the trunk loads cleanly.
const std::string mtp_probe = "blk." + std::to_string(n_main) + ".nextn.eh_proj.weight";
const bool trunk_only = (hparams.nextn_predict_layers > 0) &&
(ml.get_weight(mtp_probe.c_str()) == nullptr);
const std::string mtp_probe = "blk." + std::to_string(n_layer) + ".nextn.eh_proj.weight";
const bool trunk_only = (hparams.n_layer_nextn > 0) && (ml.get_weight(mtp_probe.c_str()) == nullptr);
const int trunk_flags = mtp_only ? TENSOR_NOT_REQUIRED : 0;
const int mtp_flags = trunk_only ? TENSOR_NOT_REQUIRED : 0;
@@ -176,7 +173,7 @@ void llama_model_step35::load_arch_tensors(llama_model_loader & ml) {
layer.nextn.shared_head_norm = create_tensor(tn(LLM_TENSOR_NEXTN_SHARED_HEAD_NORM, "weight", i), { n_embd }, TENSOR_NOT_REQUIRED);
};
for (int i = 0; i < (int) n_main; ++i) {
for (int i = 0; i < n_layer; ++i) {
load_block_trunk(i, trunk_flags);
}
// Only the first MTP block (i == n_main) is required at runtime — the
@@ -184,8 +181,8 @@ void llama_model_step35::load_arch_tensors(llama_model_loader & ml) {
// Trailing MTP blocks are loaded if present (so an un-pruned GGUF with
// all MTP layers still works) but tolerated when absent via the pruning
// path. See scripts/prune_step35_extra_mtp.py for the pruner.
for (int i = (int) n_main; i < n_layer; ++i) {
load_block_mtp(i, /*is_first_mtp=*/ i == (int) n_main);
for (int i = n_layer; i < n_layer_all; ++i) {
load_block_mtp(i, /*is_first_mtp=*/ i == n_layer);
}
}
@@ -206,8 +203,7 @@ llama_model_step35::graph::graph(const llama_model & model, const llm_graph_para
ggml_tensor * inp_out_ids = build_inp_out_ids();
// MTP/NextN layers are loaded as extra decoder blocks but not executed in the main pass.
const int n_transformer_layers = n_layer - (int) hparams.nextn_predict_layers;
for (int il = 0; il < n_transformer_layers; ++il) {
for (int il = 0; il < n_layer; ++il) {
ggml_tensor * inpSA = inpL;
const uint32_t n_head_l = hparams.n_head(il);
@@ -294,7 +290,7 @@ llama_model_step35::graph::graph(const llama_model & model, const llm_graph_para
cb(cur, "attn_proj", il);
}
if (il == n_transformer_layers - 1 && inp_out_ids && cparams.embeddings_nextn_masked) {
if (il == n_layer - 1 && inp_out_ids && cparams.embeddings_nextn_masked) {
cur = ggml_get_rows(ctx0, cur, inp_out_ids);
inpSA = ggml_get_rows(ctx0, inpSA, inp_out_ids);
}
@@ -374,7 +370,7 @@ llama_model_step35::graph::graph(const llama_model & model, const llm_graph_para
// LLM_GRAPH_TYPE_DECODER_MTP draft head for Step3p5 (MoE)
llama_model_step35::graph_mtp::graph_mtp(const llama_model & model, const llm_graph_params & params)
: llm_graph_context(params) {
GGML_ASSERT(hparams.nextn_predict_layers > 0 && "STEP35 MTP requires nextn_predict_layers > 0");
GGML_ASSERT(hparams.n_layer_nextn > 0 && "STEP35 MTP requires n_layer_nextn > 0");
// Single-block MTP only: always run the first trained MTP block (Qwen
// MTP / vLLM single-MTP-layer style). Multi-block round-robin proved to
@@ -382,7 +378,7 @@ llama_model_step35::graph_mtp::graph_mtp(const llama_model & model, const llm_gr
// blocks are loaded with TENSOR_NOT_REQUIRED so pruned GGUFs (with just
// block 0) also work — see load_arch_tensors below and
// scripts/prune_step35_extra_mtp.py.
const int il = (int) hparams.n_layer - (int) hparams.nextn_predict_layers;
const int il = hparams.n_layer();
const auto & layer = model.layers[il];
GGML_ASSERT(layer.nextn.eh_proj && "MTP block missing nextn.eh_proj");