reshaping so mm on 2d instead of 3d tensor for lfm sc (#30831)
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+4
-5
@@ -22,11 +22,10 @@ ggml_tensor * llm_build_lfm_base::build_lfm_shortconv(const llama_model & model,
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const uint32_t d_conv = hparams.n_shortconv_l_cache - 1;
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const int64_t n_embd = hparams.n_embd;
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// {n_embd, n_tokens} => {n_embd, n_seq_tokens, n_seqs}
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cur = ggml_reshape_3d(ctx0, cur, cur->ne[0], n_seq_tokens, n_seqs);
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auto * bcx = build_lora_mm(model.layers[il].shortconv.in_proj, cur);
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cb(bcx, "model.layers.{}.conv.in_proj", il);
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// {3*n_embd, n_tokens} => {3*n_embd, n_seq_tokens, n_seqs}
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bcx = ggml_reshape_3d(ctx0, bcx, bcx->ne[0], n_seq_tokens, n_seqs);
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constexpr auto n_chunks = 3;
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GGML_ASSERT(bcx->ne[0] % n_chunks == 0);
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@@ -76,10 +75,10 @@ ggml_tensor * llm_build_lfm_base::build_lfm_shortconv(const llama_model & model,
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cb(conv_out, "model.layers.{}.conv.conv", il);
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auto * y = ggml_mul(ctx0, c, conv_out);
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y = build_lora_mm(model.layers[il].shortconv.out_proj, y);
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cb(y, "model.layers.{}.conv.out_proj", il);
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// {n_embd, n_seq_tokens, n_seqs} => {n_embd, n_tokens}
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y = ggml_reshape_2d(ctx0, y, y->ne[0], n_seq_tokens * n_seqs);
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y = build_lora_mm(model.layers[il].shortconv.out_proj, y);
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cb(y, "model.layers.{}.conv.out_proj", il);
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return y;
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}
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