mirror of
https://github.com/likelovewant/ollama-for-amd.git
synced 2025-12-22 14:53:56 +00:00
Update GGML to b6646 (#12245)
Notable EOLs with this change: - MacOS v12 and v13 are no longer supported (v14+ required) - AMD gfx900 and gfx906 are no longer supported
This commit is contained in:
Daniel Hiltgen
83
llama/llama.cpp/src/llama-memory-hybrid.cpp
vendored
83
llama/llama.cpp/src/llama-memory-hybrid.cpp
vendored
@@ -9,32 +9,29 @@
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//
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llama_memory_hybrid::llama_memory_hybrid(
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const llama_model & model,
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/* attn */
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ggml_type type_k,
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ggml_type type_v,
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bool v_trans,
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uint32_t kv_size,
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uint32_t n_pad,
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uint32_t n_swa,
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llama_swa_type swa_type,
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/* recurrent */
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ggml_type type_r,
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ggml_type type_s,
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uint32_t rs_size,
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/* common */
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uint32_t n_seq_max,
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bool offload,
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bool unified,
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/* layer filters */
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layer_filter_cb && filter_attn,
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layer_filter_cb && filter_recr) :
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const llama_model & model,
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/* attn */
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ggml_type type_k,
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ggml_type type_v,
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bool v_trans,
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uint32_t kv_size,
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uint32_t n_pad,
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uint32_t n_swa,
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llama_swa_type swa_type,
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/* recurrent */
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ggml_type type_r,
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ggml_type type_s,
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uint32_t rs_size,
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/* common */
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uint32_t n_seq_max,
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bool offload,
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bool unified,
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/* layer filters */
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const layer_filter_cb & filter_attn,
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const layer_filter_cb & filter_recr) :
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hparams(model.hparams),
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mem_attn(new llama_kv_cache_unified(
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mem_attn(new llama_kv_cache(
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model,
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filter_attn == nullptr ?
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[&](int32_t il) { return !hparams.is_recurrent(il); }
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: filter_attn,
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type_k,
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type_v,
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v_trans,
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@@ -44,18 +41,22 @@ llama_memory_hybrid::llama_memory_hybrid(
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n_seq_max,
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n_pad,
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n_swa,
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swa_type
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swa_type,
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filter_attn == nullptr ?
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[&](int32_t il) { return !hparams.is_recurrent(il); }
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: filter_attn,
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nullptr
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)),
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mem_recr(new llama_memory_recurrent(
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model,
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filter_recr == nullptr ?
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[&](int32_t il) { return hparams.is_recurrent(il); }
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: filter_recr,
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type_r,
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type_s,
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offload,
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rs_size,
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n_seq_max
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n_seq_max,
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filter_recr == nullptr ?
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[&](int32_t il) { return hparams.is_recurrent(il); }
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: filter_recr
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)) {}
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llama_memory_context_ptr llama_memory_hybrid::init_batch(llama_batch_allocr & balloc, uint32_t n_ubatch, bool embd_all) {
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@@ -165,17 +166,29 @@ llama_pos llama_memory_hybrid::seq_pos_max(llama_seq_id seq_id) const {
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return std::min(mem_attn->seq_pos_max(seq_id), mem_recr->seq_pos_max(seq_id));
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}
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void llama_memory_hybrid::state_write(llama_io_write_i & io, llama_seq_id seq_id) const {
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std::map<ggml_backend_buffer_type_t, size_t> llama_memory_hybrid::memory_breakdown() const {
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std::map<ggml_backend_buffer_type_t, size_t> mb = mem_attn->memory_breakdown();
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for (const auto & buft_size : mem_recr->memory_breakdown()) {
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mb[buft_size.first] += buft_size.second;
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}
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return mb;
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}
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void llama_memory_hybrid::state_write(llama_io_write_i & io, llama_seq_id seq_id, llama_state_seq_flags flags) const {
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GGML_UNUSED(flags);
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mem_attn->state_write(io, seq_id);
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mem_recr->state_write(io, seq_id);
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}
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void llama_memory_hybrid::state_read(llama_io_read_i & io, llama_seq_id seq_id) {
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void llama_memory_hybrid::state_read(llama_io_read_i & io, llama_seq_id seq_id, llama_state_seq_flags flags) {
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GGML_UNUSED(flags);
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mem_attn->state_read(io, seq_id);
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mem_recr->state_read(io, seq_id);
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}
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llama_kv_cache_unified * llama_memory_hybrid::get_mem_attn() const {
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llama_kv_cache * llama_memory_hybrid::get_mem_attn() const {
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return mem_attn.get();
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}
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@@ -206,7 +219,7 @@ llama_memory_hybrid_context::llama_memory_hybrid_context(
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std::vector<llama_ubatch> ubatches) :
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ubatches(std::move(ubatches)),
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// note: here we copy the ubatches. not sure if this is ideal
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ctx_attn(new llama_kv_cache_unified_context(mem->get_mem_attn(), std::move(sinfos_attn), this->ubatches)),
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ctx_attn(new llama_kv_cache_context(mem->get_mem_attn(), std::move(sinfos_attn), this->ubatches)),
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ctx_recr(new llama_memory_recurrent_context(mem->get_mem_recr(), this->ubatches)),
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status(llama_memory_status_combine(ctx_attn->get_status(), ctx_recr->get_status())) {
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}
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@@ -244,8 +257,8 @@ const llama_ubatch & llama_memory_hybrid_context::get_ubatch() const {
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return ubatches[i_next];
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}
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const llama_kv_cache_unified_context * llama_memory_hybrid_context::get_attn() const {
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return static_cast<const llama_kv_cache_unified_context *>(ctx_attn.get());
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const llama_kv_cache_context * llama_memory_hybrid_context::get_attn() const {
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return static_cast<const llama_kv_cache_context *>(ctx_attn.get());
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}
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const llama_memory_recurrent_context * llama_memory_hybrid_context::get_recr() const {
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