continuing
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@ -3015,6 +3015,10 @@ struct ggml_tensor * ggml_mul_mat(
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struct ggml_context * ctx,
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struct ggml_context * ctx,
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struct ggml_tensor * a,
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struct ggml_tensor * a,
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struct ggml_tensor * b) {
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struct ggml_tensor * b) {
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printf("Up: {%lld, %lld}\n", a->ne[0], a->ne[1]);
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printf("Cur: {%lld, %lld}\n", b->ne[0], b->ne[1]);
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GGML_ASSERT(ggml_can_mul_mat(a, b));
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GGML_ASSERT(ggml_can_mul_mat(a, b));
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GGML_ASSERT(!ggml_is_transposed(a));
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GGML_ASSERT(!ggml_is_transposed(a));
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@ -644,6 +644,8 @@ ggml_tensor * llm_graph_context::build_ffn(
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llm_ffn_op_type type_op,
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llm_ffn_op_type type_op,
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llm_ffn_gate_type type_gate,
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llm_ffn_gate_type type_gate,
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int il) const {
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int il) const {
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ggml_tensor * tmp = up ? build_lora_mm(up, cur) : cur;
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ggml_tensor * tmp = up ? build_lora_mm(up, cur) : cur;
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cb(tmp, "ffn_up", il);
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cb(tmp, "ffn_up", il);
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@ -1377,7 +1379,7 @@ ggml_tensor * llm_graph_context::build_attn(
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// TODO: if ubatch.equal_seqs() == true, we can split the three tensors below into ubatch.n_seqs_unq streams
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// TODO: if ubatch.equal_seqs() == true, we can split the three tensors below into ubatch.n_seqs_unq streams
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LLAMA_LOG_INFO("ubatch.equal_seqs() = %d, n_seqs = %d\n", ubatch.equal_seqs(), ubatch.n_seqs);
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LLAMA_LOG_INFO("ubatch.equal_seqs() = %d, n_seqs = %d\n", ubatch.equal_seqs(), ubatch.n_seqs);
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assert(!ubatch.equal_seqs());
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// sassert(!ubatch.equal_seqs());
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ggml_tensor * q = q_cur;
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ggml_tensor * q = q_cur;
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ggml_tensor * k = k_cur;
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ggml_tensor * k = k_cur;
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