tqcq/llama.cpp
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context : disable encoder embd tensor for now

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ggml-ci
This commit is contained in:
Georgi Gerganov
2025-02-27 15:07:10 +02:00
parent 4efe989886
commit 952feedfca
2 changed files with 18 additions and 12 deletions
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23
src/llama-context.cpp
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@ -4673,6 +4673,7 @@ int llama_context_enc::encode(llama_batch & inp_batch) {
ggml_backend_sched_reset(sched.get()); ggml_backend_sched_reset(sched.get());
cross->t_embd = t_embd; cross->t_embd = t_embd;
cross->v_embd = embd;
// remember the sequence ids used during the encoding - needed for cross attention later // remember the sequence ids used during the encoding - needed for cross attention later
cross->seq_ids_enc.resize(n_tokens); cross->seq_ids_enc.resize(n_tokens);
@ -4701,12 +4702,11 @@ void llama_context_dec::input_set(const llama_ubatch & ubatch) {
// call base functionality // call base functionality
llama_context_kv_self::input_set(ubatch); llama_context_kv_self::input_set(ubatch);
//if (inp.cross_embd && inp.cross_embd->op != GGML_OP_NONE) { if (inp.cross_embd && cross->t_embd) {
// assert(inp.cross_embd->type == GGML_TYPE_F32); assert(inp.cross_embd->type == GGML_TYPE_F32);
// assert(ggml_nelements(inp.cross_embd) == cross->n_outputs*model.hparams.n_embd);
// ggml_backend_tensor_set(inp.cross_embd, cross->embd_enc, 0, ggml_nbytes(inp.cross_embd)); ggml_backend_tensor_set(inp.cross_embd, cross->v_embd, 0, ggml_nbytes(inp.cross_embd));
//} }
if (inp.cross_kq_mask) { if (inp.cross_kq_mask) {
const int64_t n_enc = inp.cross_kq_mask->ne[0]; const int64_t n_enc = inp.cross_kq_mask->ne[0];
@ -4749,16 +4749,17 @@ ggml_cgraph * llama_context_dec::graph_init() {
ggml_tensor * llama_context_dec::build_inp_cross_embd( ggml_tensor * llama_context_dec::build_inp_cross_embd(
ggml_context * ctx0) { ggml_context * ctx0) {
// if we have the output embeddings from the encoder, use them directly // if we have the output embeddings from the encoder, use them directly
if (cross->t_embd) { // TODO: needs more work to be correct, for now just use the tensor shape
inp.cross_embd = ggml_view_tensor(ctx0, cross->t_embd); //if (cross->t_embd) {
// inp.cross_embd = ggml_view_tensor(ctx0, cross->t_embd);
return inp.cross_embd; // return inp.cross_embd;
} //}
const auto & hparams = model.hparams; const auto & hparams = model.hparams;
const auto n_embd = hparams.n_embd; const auto n_embd = cross->t_embd ? cross->t_embd->ne[0] : hparams.n_embd;
const auto n_enc = hparams.n_ctx_train; const auto n_enc = cross->t_embd ? cross->t_embd->ne[1] : hparams.n_ctx_train;
inp.cross_embd = ggml_new_tensor_2d(ctx0, GGML_TYPE_F32, n_embd, n_enc); inp.cross_embd = ggml_new_tensor_2d(ctx0, GGML_TYPE_F32, n_embd, n_enc);
ggml_set_input(inp.cross_embd); ggml_set_input(inp.cross_embd);

7
src/llama-context.h
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@ -750,9 +750,14 @@ private:
// TODO: tmp - need something better to pass the data from the encoder to the decoder // TODO: tmp - need something better to pass the data from the encoder to the decoder
struct llama_cross { struct llama_cross {
// the output embeddings from the encoder // the output embeddings from the encoder as a ggml tensor
// TODO: this needs more work to be correct, for now copy the embeddings data to host memory
// ref: https://github.com/ggml-org/llama.cpp/pull/11213#discussion_r1969892524
ggml_tensor * t_embd = nullptr; ggml_tensor * t_embd = nullptr;
// embeddings data copied to host memory (tmp)
float * v_embd = nullptr;
// needed to construct the cross-attention mask in the decoder // needed to construct the cross-attention mask in the decoder
std::vector<std::set<llama_seq_id>> seq_ids_enc; std::vector<std::set<llama_seq_id>> seq_ids_enc;
}; };