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feat(granitemoe): Add support for "granitemoe" architecture
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This is a port of the work done in llama.cpp directly
ggerganov/llama.cpp#9438

Branch: GraniteThreeSupport

Signed-off-by: Gabe Goodhart <[email protected]>
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gabe-l-hart committed Nov 4, 2024
1 parent 7932412 commit 6a13182
Showing 1 changed file with 27 additions and 2 deletions.
29 changes: 27 additions & 2 deletions llama.cpp/llama.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -179,6 +179,7 @@ enum llm_arch {
LLM_ARCH_NEMOTRON,
LLM_ARCH_EXAONE,
LLM_ARCH_GRANITE,
LLM_ARCH_GRANITE_MOE,
LLM_ARCH_UNKNOWN,
};

Expand Down Expand Up @@ -227,6 +228,7 @@ static const std::map<llm_arch, const char *> LLM_ARCH_NAMES = {
{ LLM_ARCH_NEMOTRON, "nemotron" },
{ LLM_ARCH_EXAONE, "exaone" },
{ LLM_ARCH_GRANITE, "granite" },
{ LLM_ARCH_GRANITE_MOE, "granitemoe" },
{ LLM_ARCH_UNKNOWN, "(unknown)" },
};

Expand Down Expand Up @@ -1328,6 +1330,24 @@ static const std::map<llm_arch, std::map<llm_tensor, std::string>> LLM_TENSOR_NA
{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },
},
},
{
LLM_ARCH_GRANITE_MOE,
{
{ LLM_TENSOR_TOKEN_EMBD, "token_embd" },
{ LLM_TENSOR_OUTPUT_NORM, "output_norm" },
{ LLM_TENSOR_OUTPUT, "output" },
{ LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },
{ LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },
{ LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },
{ LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },
{ LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },
{ LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },
{ LLM_TENSOR_FFN_GATE_INP, "blk.%d.ffn_gate_inp" },
{ LLM_TENSOR_FFN_GATE_EXPS, "blk.%d.ffn_gate_exps" },
{ LLM_TENSOR_FFN_DOWN_EXPS, "blk.%d.ffn_down_exps" },
{ LLM_TENSOR_FFN_UP_EXPS, "blk.%d.ffn_up_exps" },
},
},
{
LLM_ARCH_UNKNOWN,
{
Expand Down Expand Up @@ -1956,7 +1976,7 @@ struct llama_hparams {
float f_max_alibi_bias = 0.0f;
float f_logit_scale = 0.0f;

// Additional scale factors (Granite)
// Additional scale factors (Granite/Granite MoE)
float f_residual_scale = 0.0f;
float f_embedding_scale = 0.0f;
float f_attention_scale = 0.0f;
Expand Down Expand Up @@ -5032,6 +5052,7 @@ static void llm_load_hparams(
}
} break;
case LLM_ARCH_GRANITE:
case LLM_ARCH_GRANITE_MOE:
{
ml.get_key(LLM_KV_ATTENTION_LAYERNORM_RMS_EPS, hparams.f_norm_rms_eps);
ml.get_key(LLM_KV_LOGIT_SCALE, hparams.f_logit_scale);
Expand All @@ -5040,6 +5061,7 @@ static void llm_load_hparams(
ml.get_key(LLM_KV_ATTENTION_SCALE, hparams.f_attention_scale);

switch (hparams.n_layer) {
case 32: model.type = e_model::MODEL_3B; break;
case 40: model.type = e_model::MODEL_3B; break;
// Add additional layer/vocab/etc checks here for other model sizes
default: model.type = e_model::MODEL_UNKNOWN;
Expand Down Expand Up @@ -5713,7 +5735,7 @@ static void llm_load_print_meta(llama_model_loader & ml, llama_model & model) {
LLAMA_LOG_INFO("%s: n_ff_shexp = %d\n", __func__, hparams.n_ff_shexp);
}

if (model.arch == LLM_ARCH_GRANITE) {
if (model.arch == LLM_ARCH_GRANITE || model.arch == LLM_ARCH_GRANITE_MOE) {
LLAMA_LOG_INFO("%s: f_embedding_scale = %f\n", __func__, hparams.f_embedding_scale);
LLAMA_LOG_INFO("%s: f_residual_scale = %f\n", __func__, hparams.f_residual_scale);
LLAMA_LOG_INFO("%s: f_attention_scale = %f\n", __func__, hparams.f_attention_scale);
Expand Down Expand Up @@ -5891,6 +5913,7 @@ static bool llm_load_tensors(
case LLM_ARCH_REFACT:
case LLM_ARCH_MINICPM:
case LLM_ARCH_GRANITE:
case LLM_ARCH_GRANITE_MOE:
{
model.tok_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab});

Expand Down Expand Up @@ -14019,6 +14042,7 @@ static struct ggml_cgraph * llama_build_graph(
switch (model.arch) {
case LLM_ARCH_LLAMA:
case LLM_ARCH_GRANITE:
case LLM_ARCH_GRANITE_MOE:
{
result = llm.build_llama();
} break;
Expand Down Expand Up @@ -17273,6 +17297,7 @@ enum llama_rope_type llama_rope_type(const struct llama_model * model) {
case LLM_ARCH_DEEPSEEK2:
case LLM_ARCH_CHATGLM:
case LLM_ARCH_GRANITE:
case LLM_ARCH_GRANITE_MOE:
return LLAMA_ROPE_TYPE_NORM;

// the pairs of head values are offset by n_rot/2
Expand Down

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