vbatts/llama.cpp
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llama : rename moe_intermediate_size variable to n_ff_exp

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Stanisław Szymczyk 2024-05-27 13:17:49 +02:00
parent 20769c0f7f
commit fac1e804a1
1 changed files with 7 additions and 7 deletions
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llama.cpp
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@ -6313,7 +6313,7 @@ static bool llm_load_tensors(
const uint32_t n_embd_head_qk_nope = hparams.n_embd_head_k - hparams.n_rot; const uint32_t n_embd_head_qk_nope = 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_ff_exp; const uint32_t n_ff_exp = 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});
@ -6358,14 +6358,14 @@ static bool llm_load_tensors(
GGML_ASSERT(hparams.n_expert_used > 0); GGML_ASSERT(hparams.n_expert_used > 0);
// MoE branch // MoE branch
layer.ffn_gate_exps = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE_EXPS, "weight", i), { n_embd, moe_intermediate_size, n_expert}); layer.ffn_gate_exps = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE_EXPS, "weight", i), { n_embd, n_ff_exp, n_expert});
layer.ffn_down_exps = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN_EXPS, "weight", i), {moe_intermediate_size, n_embd, n_expert}); layer.ffn_down_exps = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN_EXPS, "weight", i), {n_ff_exp, n_embd, n_expert});
layer.ffn_up_exps = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP_EXPS, "weight", i), { n_embd, moe_intermediate_size, n_expert}); layer.ffn_up_exps = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP_EXPS, "weight", i), { n_embd, n_ff_exp, n_expert});
// Shared expert branch // Shared expert branch
layer.ffn_gate_shexp = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE_SHEXP, "weight", i), {n_embd, moe_intermediate_size * hparams.n_expert_shared}); layer.ffn_gate_shexp = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE_SHEXP, "weight", i), {n_embd, n_ff_exp * hparams.n_expert_shared});
layer.ffn_down_shexp = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN_SHEXP, "weight", i), { moe_intermediate_size * hparams.n_expert_shared, n_embd}); layer.ffn_down_shexp = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN_SHEXP, "weight", i), { n_ff_exp * hparams.n_expert_shared, n_embd});
layer.ffn_up_shexp = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP_SHEXP, "weight", i), {n_embd, moe_intermediate_size * hparams.n_expert_shared}); layer.ffn_up_shexp = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP_SHEXP, "weight", i), {n_embd, n_ff_exp * hparams.n_expert_shared});
} }
} }
} break; } break;