vbatts/llama.cpp
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llama : rename n_expert_ff to n_ff_exp

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Stanisław Szymczyk 2024-05-27 12:54:47 +02:00
parent abef8b2634
commit a654cd992b
1 changed files with 4 additions and 4 deletions
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llama.cpp
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@ -1839,7 +1839,7 @@ struct llama_hparams {
uint32_t n_leading_dense_layer = 0; uint32_t n_leading_dense_layer = 0;
uint32_t n_lora_q = 0; uint32_t n_lora_q = 0;
uint32_t n_lora_kv = 0; uint32_t n_lora_kv = 0;
uint32_t n_expert_ff = 0; uint32_t n_ff_exp = 0;
uint32_t n_expert_shared = 0; uint32_t n_expert_shared = 0;
float expert_weights_scale = 0.0; float expert_weights_scale = 0.0;
@ -1887,7 +1887,7 @@ struct llama_hparams {
if (this->n_leading_dense_layer != other.n_leading_dense_layer) return true; if (this->n_leading_dense_layer != other.n_leading_dense_layer) return true;
if (this->n_lora_q != other.n_lora_q) return true; if (this->n_lora_q != other.n_lora_q) return true;
if (this->n_lora_kv != other.n_lora_kv) return true; if (this->n_lora_kv != other.n_lora_kv) return true;
if (this->n_expert_ff != other.n_expert_ff) return true; if (this->n_ff_exp != other.n_ff_exp) return true;
if (this->n_expert_shared != other.n_expert_shared) return true; if (this->n_expert_shared != other.n_expert_shared) return true;
if (this->rope_finetuned != other.rope_finetuned) return true; if (this->rope_finetuned != other.rope_finetuned) return true;
@ -4470,7 +4470,7 @@ static void llm_load_hparams(
ml.get_key(LLM_KV_ATTENTION_Q_LORA_RANK, hparams.n_lora_q); ml.get_key(LLM_KV_ATTENTION_Q_LORA_RANK, hparams.n_lora_q);
} }
ml.get_key(LLM_KV_ATTENTION_KV_LORA_RANK, hparams.n_lora_kv); ml.get_key(LLM_KV_ATTENTION_KV_LORA_RANK, hparams.n_lora_kv);
ml.get_key(LLM_KV_EXPERT_FEED_FORWARD_LENGTH, hparams.n_expert_ff); ml.get_key(LLM_KV_EXPERT_FEED_FORWARD_LENGTH, hparams.n_ff_exp);
ml.get_key(LLM_KV_EXPERT_SHARED_COUNT, hparams.n_expert_shared); ml.get_key(LLM_KV_EXPERT_SHARED_COUNT, hparams.n_expert_shared);
ml.get_key(LLM_KV_EXPERT_WEIGHTS_SCALE, hparams.expert_weights_scale); ml.get_key(LLM_KV_EXPERT_WEIGHTS_SCALE, hparams.expert_weights_scale);
ml.get_key(LLM_KV_ROPE_SCALING_YARN_LOG_MUL, hparams.rope_yarn_log_mul); ml.get_key(LLM_KV_ROPE_SCALING_YARN_LOG_MUL, hparams.rope_yarn_log_mul);
@ -6314,7 +6314,7 @@ static bool llm_load_tensors(
const uint32_t qk_nope_head_dim = hparams.n_embd_head_k - hparams.n_rot; const uint32_t qk_nope_head_dim = hparams.n_embd_head_k - hparams.n_rot;
const uint32_t q_lora_rank = hparams.n_lora_q; const uint32_t q_lora_rank = hparams.n_lora_q;
const uint32_t kv_lora_rank = hparams.n_lora_kv; const uint32_t kv_lora_rank = hparams.n_lora_kv;
const uint32_t moe_intermediate_size = hparams.n_expert_ff; const uint32_t moe_intermediate_size = hparams.n_ff_exp;
model.tok_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}); model.tok_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab});