llama : rename moe_intermediate_size variable to n_ff_exp
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1 changed files with 7 additions and 7 deletions
14
llama.cpp
14
llama.cpp
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@ -6313,7 +6313,7 @@ static bool llm_load_tensors(
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const uint32_t n_embd_head_qk_nope = hparams.n_embd_head_k - hparams.n_rot;
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const uint32_t q_lora_rank = hparams.n_lora_q;
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const uint32_t kv_lora_rank = hparams.n_lora_kv;
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const uint32_t moe_intermediate_size = hparams.n_ff_exp;
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const uint32_t n_ff_exp = hparams.n_ff_exp;
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model.tok_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab});
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@ -6358,14 +6358,14 @@ static bool llm_load_tensors(
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GGML_ASSERT(hparams.n_expert_used > 0);
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// MoE branch
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layer.ffn_gate_exps = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE_EXPS, "weight", i), { n_embd, moe_intermediate_size, n_expert});
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layer.ffn_down_exps = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN_EXPS, "weight", i), {moe_intermediate_size, n_embd, n_expert});
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layer.ffn_up_exps = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP_EXPS, "weight", i), { n_embd, moe_intermediate_size, n_expert});
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layer.ffn_gate_exps = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE_EXPS, "weight", i), { n_embd, n_ff_exp, n_expert});
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layer.ffn_down_exps = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN_EXPS, "weight", i), {n_ff_exp, n_embd, n_expert});
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layer.ffn_up_exps = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP_EXPS, "weight", i), { n_embd, n_ff_exp, n_expert});
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// Shared expert branch
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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});
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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});
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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});
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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});
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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});
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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});
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}
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}
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} break;
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