feat: sync llama.cpp to b9297

cpp/common/build-info.cpp

@@ -3,8 +3,8 @@
 #include <cstdio>
 #include <string>
 
-int LLAMA_BUILD_NUMBER = 9254;
-char const * LLAMA_COMMIT = "e947228";
+int LLAMA_BUILD_NUMBER = 9297;
+char const * LLAMA_COMMIT = "b0df4c0";
 char const * LLAMA_COMPILER = "unknown";
 char const * LLAMA_BUILD_TARGET = "unknown";
 

cpp/common/chat.h

@@ -222,6 +222,7 @@ struct common_chat_parser_params {
     bool                    reasoning_in_content = false;
     std::string             generation_prompt;
     bool                    parse_tool_calls     = true;
+    bool                    is_continuation      = false;
     bool                    echo                 = false;  // Include assistant prefilled msg in output
     bool                    debug                = false;  // Enable debug output for PEG parser
     common_peg_arena        parser               = {};

cpp/common/common.h

@@ -306,6 +306,8 @@ struct common_params_speculative_draft {
     float p_split = 0.1f; // speculative decoding split probability
     float p_min   = 0.0f; // minimum speculative decoding probability (greedy)
 
+    bool backend_sampling = true; // offload draft sampling to the backend (default: on)
+
     common_params_model mparams;
 
     llama_context * ctx_tgt = nullptr;

cpp/common/speculative.cpp

@@ -33,16 +33,15 @@ const std::map<std::string, common_speculative_type> common_speculative_type_fro
 };
 
 static std::string common_speculative_get_devices_str(const std::vector<lm_ggml_backend_dev_t> & devices) {
-    if (devices.empty()) {
-        return "default";
-    }
-
     std::string result;
     for (size_t i = 0; i < devices.size(); i++) {
-        if (i > 0) result += ", ";
+        if (devices[i] == nullptr) {
+            continue;
+        }
+        if (!result.empty()) result += ", ";
         result += lm_ggml_backend_dev_name(devices[i]);
     }
-    return result;
+    return result.empty() ? "default" : result;
 }
 
 struct common_speculative_config {
@@ -414,6 +413,9 @@ struct common_speculative_impl_draft_mtp : public common_speculative_impl {
 
     std::vector<common_sampler_ptr> smpls;
 
+    // backend sampler chain per seq, attached to ctx_dft
+    std::vector<llama_sampler *> backend_chains;
+
     int32_t n_embd = 0;
 
     // Per-sequence cross-batch carryover: pair (h_p, x_{p+1}) at MTP pos p+1.
@@ -445,7 +447,7 @@ struct common_speculative_impl_draft_mtp : public common_speculative_impl {
         n_embd = llama_model_n_embd(llama_get_model(ctx_dft));
 
         LOG_INF("%s: adding speculative implementation 'draft-mtp'\n", __func__);
-        LOG_INF("%s: - n_max=%d, n_min=%d, p_min=%.2f, n_embd=%d\n", __func__, this->params.n_max, this->params.n_min, this->params.p_min, n_embd);
+        LOG_INF("%s: - n_max=%d, n_min=%d, p_min=%.2f, n_embd=%d, backend_sampling=%d\n", __func__, this->params.n_max, this->params.n_min, this->params.p_min, n_embd, (int) this->params.backend_sampling);
         LOG_INF("%s: - gpu_layers=%d, cache_k=%s, cache_v=%s, ctx_tgt=%s, ctx_dft=%s, devices=[%s]\n", __func__,
                 this->params.n_gpu_layers,
                 lm_ggml_type_name(this->params.cache_type_k),
@@ -469,6 +471,22 @@ struct common_speculative_impl_draft_mtp : public common_speculative_impl {
             s.reset(common_sampler_init(llama_get_model(ctx_dft), sparams));
         }
 
+        // offload draft sampling to the backend
+        backend_chains.assign(n_seq, nullptr);
+        if (this->params.backend_sampling) {
+            for (llama_seq_id seq_id = 0; seq_id < (llama_seq_id) n_seq; ++seq_id) {
+                llama_sampler * chain = llama_sampler_chain_init(llama_sampler_chain_default_params());
+                llama_sampler_chain_add(chain, llama_sampler_init_top_k(10));
+
+                if (!llama_set_sampler(ctx_dft, seq_id, chain)) {
+                    LOG_WRN("%s: backend offload failed for seq_id=%d; using CPU sampler\n", __func__, (int) seq_id);
+                    llama_sampler_free(chain);
+                    chain = nullptr;
+                }
+                backend_chains[seq_id] = chain;
+            }
+        }
+
         llama_set_embeddings_pre_norm(ctx_tgt, true, /*masked*/ false);
         llama_set_embeddings_pre_norm(ctx_dft, true, /*masked*/ true);
 
@@ -484,6 +502,18 @@ struct common_speculative_impl_draft_mtp : public common_speculative_impl {
     }
 
     ~common_speculative_impl_draft_mtp() override {
+        auto * ctx_dft = this->params.ctx_dft;
+        for (llama_seq_id seq_id = 0; seq_id < (llama_seq_id) backend_chains.size(); ++seq_id) {
+            if (backend_chains[seq_id] == nullptr) {
+                continue;
+            }
+            if (ctx_dft) {
+                llama_set_sampler(ctx_dft, seq_id, nullptr);
+            }
+            llama_sampler_free(backend_chains[seq_id]);
+        }
+        backend_chains.clear();
+
         if (batch.token != nullptr) {
             free(batch.token);
             batch.token = nullptr;

cpp/ggml-backend.cpp

@@ -306,7 +306,7 @@ void lm_ggml_backend_tensor_get_2d_async(lm_ggml_backend_t backend, const struct
     LM_GGML_ASSERT(tensor);
     LM_GGML_ASSERT(tensor->data != NULL && "tensor not allocated");
 
-    if (n_copies <= 1 || backend->iface.set_tensor_2d_async == NULL) {
+    if (n_copies <= 1 || backend->iface.get_tensor_2d_async == NULL) {
         for (size_t i = 0; i < n_copies; i++) {
             lm_ggml_backend_tensor_get_async(backend, tensor, (char *) data + i*stride_data, offset + i*stride_tensor, size);
         }
@@ -317,7 +317,7 @@ void lm_ggml_backend_tensor_get_2d_async(lm_ggml_backend_t backend, const struct
     }
 
     LM_GGML_ASSERT(tensor->data != NULL && "tensor not allocated");
-    LM_GGML_ASSERT(offset + (n_copies-1)*stride_tensor + size <= lm_ggml_nbytes(tensor) && "tensor write out of bounds");
+    LM_GGML_ASSERT(offset + (n_copies-1)*stride_tensor + size <= lm_ggml_nbytes(tensor) && "tensor read out of bounds");
     backend->iface.get_tensor_2d_async(backend, tensor, data, offset, size, n_copies, stride_tensor, stride_data);
 }
 
@@ -379,7 +379,7 @@ void lm_ggml_backend_tensor_get_2d(const struct lm_ggml_tensor * tensor, void *
     lm_ggml_backend_buffer_t buf = tensor->view_src ? tensor->view_src->buffer : tensor->buffer;
     LM_GGML_ASSERT(buf != NULL && "tensor buffer not set");
 
-    if (n_copies <= 1 || buf->iface.set_tensor_2d == NULL) {
+    if (n_copies <= 1 || buf->iface.get_tensor_2d == NULL) {
         for (size_t i = 0; i < n_copies; i++) {
             lm_ggml_backend_tensor_get(tensor, (char *) data + i*stride_data, offset + i*stride_tensor, size);
         }

cpp/ggml-hexagon/ggml-hexagon.cpp

@@ -2735,9 +2735,10 @@ static bool lm_ggml_hexagon_supported_ssm_conv(const struct lm_ggml_hexagon_sess
     if (dst->ne[0] != d_inner || dst->ne[1] != n_t || dst->ne[2] != n_s) {
         return false;
     }
-
-    // TODO: add support for non-contiguous tensors
-    if (!lm_ggml_is_contiguous(src0) || !lm_ggml_is_contiguous(src1) || !lm_ggml_is_contiguous(dst)) {
+    if (src0->nb[0] != sizeof(float) || src1->nb[0] != sizeof(float) || dst->nb[0] != sizeof(float)) {
+        return false;
+    }
+    if (src0->nb[1] != src0->ne[0] * sizeof(float) || src1->nb[1] != src1->ne[0] * sizeof(float)) {
         return false;
     }