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llama : de-duplicate deepseek2 norm
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bda62d7999
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3dfda05956
@ -12873,12 +12873,12 @@ struct llm_build_context {
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struct ggml_tensor * ffn_inp = ggml_add(ctx0, cur, inpSA);
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struct ggml_tensor * ffn_inp = ggml_add(ctx0, cur, inpSA);
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cb(ffn_inp, "ffn_inp", il);
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cb(ffn_inp, "ffn_inp", il);
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if ((uint32_t) il < hparams.n_layer_dense_lead) {
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cur = llm_build_norm(ctx0, ffn_inp, hparams,
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cur = llm_build_norm(ctx0, ffn_inp, hparams,
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model.layers[il].ffn_norm, NULL,
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model.layers[il].ffn_norm, NULL,
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LLM_NORM_RMS, cb, il);
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LLM_NORM_RMS, cb, il);
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cb(cur, "ffn_norm", il);
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cb(cur, "ffn_norm", il);
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if ((uint32_t) il < hparams.n_layer_dense_lead) {
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cur = llm_build_ffn(ctx0, cur,
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cur = llm_build_ffn(ctx0, cur,
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model.layers[il].ffn_up, NULL, NULL,
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model.layers[il].ffn_up, NULL, NULL,
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model.layers[il].ffn_gate, NULL, NULL,
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model.layers[il].ffn_gate, NULL, NULL,
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@ -12888,11 +12888,6 @@ struct llm_build_context {
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cb(cur, "ffn_out", il);
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cb(cur, "ffn_out", il);
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} else {
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} else {
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// MoE branch
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// MoE branch
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cur = llm_build_norm(ctx0, ffn_inp, hparams,
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model.layers[il].ffn_norm, NULL,
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LLM_NORM_RMS, cb, il);
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cb(cur, "ffn_norm", il);
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ggml_tensor * moe_out =
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ggml_tensor * moe_out =
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llm_build_moe_ffn(ctx0, cur,
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llm_build_moe_ffn(ctx0, cur,
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model.layers[il].ffn_gate_inp,
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model.layers[il].ffn_gate_inp,
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