tts: reuse decode scratch buffers across streaming steps

Keep the talker causal mask in each static attention window graph and
reuse positions, KV rows and sliding attention mask buffers in each codec
stream graph class.

This removes the remaining host allocations from the talker and codec
streaming hot loops without changing graph execution.

src/pipeline-codec.cpp

@@ -492,18 +492,17 @@ bool pipeline_codec_decode_stream(PipelineCodec * pc, const int32_t * codes, int
 
     ggml_backend_tensor_set(sg->codes, codes, 0, (size_t) T * (size_t) K * sizeof(int32_t));
 
-    std::vector<int32_t> pos((size_t) T);
-    std::vector<int64_t> rows((size_t) T);
+    sg->pos_buf.resize((size_t) T);
+    sg->rows_buf.resize((size_t) T);
     for (int t = 0; t < T; t++) {
-        pos[(size_t) t]  = pc->stream_pos + t;
-        rows[(size_t) t] = (int64_t) ((pc->stream_pos + t) % ring);
+        sg->pos_buf[(size_t) t]  = pc->stream_pos + t;
+        sg->rows_buf[(size_t) t] = (int64_t) ((pc->stream_pos + t) % ring);
     }
-    ggml_backend_tensor_set(sg->pos, pos.data(), 0, (size_t) T * sizeof(int32_t));
-    ggml_backend_tensor_set(sg->rows, rows.data(), 0, (size_t) T * sizeof(int64_t));
+    ggml_backend_tensor_set(sg->pos, sg->pos_buf.data(), 0, (size_t) T * sizeof(int32_t));
+    ggml_backend_tensor_set(sg->rows, sg->rows_buf.data(), 0, (size_t) T * sizeof(int64_t));
 
-    std::vector<float> mask_buf;
-    tok_trans_build_stream_mask(pc->stream_pos, T, ring, pc->transformer.sliding_window, mask_buf);
-    ggml_backend_tensor_set(sg->mask, mask_buf.data(), 0, mask_buf.size() * sizeof(float));
+    tok_trans_build_stream_mask(pc->stream_pos, T, ring, pc->transformer.sliding_window, sg->mask_buf);
+    ggml_backend_tensor_set(sg->mask, sg->mask_buf.data(), 0, sg->mask_buf.size() * sizeof(float));
 
     enum ggml_status st = ggml_backend_graph_compute(pc->backend, sg->gf);
     if (st != GGML_STATUS_SUCCESS) {

src/pipeline-codec.h

@@ -64,6 +64,9 @@ struct CodecStreamGraph {
     struct ggml_tensor *  rows   = nullptr;
     struct ggml_tensor *  mask   = nullptr;
     struct ggml_tensor *  out    = nullptr;
+    std::vector<int32_t>  pos_buf;
+    std::vector<int64_t>  rows_buf;
+    std::vector<float>    mask_buf;
 };
 
 // One primed stream state snapshot: a mirror of every conv context and

src/talker-decode-graph.h

@@ -9,6 +9,8 @@
 #include "ggml-alloc.h"
 #include "ggml.h"
 
+#include <vector>
+
 struct TalkerDecodeGraph {
     struct ggml_context *    ctx     = nullptr;
     struct ggml_cgraph *     gf      = nullptr;
@@ -19,6 +21,7 @@ struct TalkerDecodeGraph {
     struct ggml_tensor *     rows_in = nullptr;  // [1] i64
     struct ggml_tensor *     mask_in = nullptr;  // [n_kv_pad, 1] f16
     struct ggml_tensor *     logits  = nullptr;  // [vocab, 1] f32
+    std::vector<ggml_fp16_t> mask;               // [n_kv_pad] f16
     int                      n_kv_pad = 0;       // window class width, 0 marks an empty slot
 };
 
@@ -38,5 +41,6 @@ static void talker_decode_graph_free(TalkerDecodeGraph * tg) {
     tg->rows_in = nullptr;
     tg->mask_in = nullptr;
     tg->logits  = nullptr;
+    tg->mask.clear();
     tg->n_kv_pad = 0;
 }

src/talker-forward.h

@@ -571,6 +571,7 @@ static bool talker_decode_graph_build(const TalkerWeights *        tw,
     tg->rows_in = rows_in;
     tg->mask_in = mask_in;
     tg->logits  = logits;
+    tg->mask.resize((size_t) n_kv_pad);
     tg->n_kv_pad = n_kv_pad;
     return true;
 }
@@ -620,7 +621,7 @@ static bool talker_forward_decode(const TalkerWeights *        tw,
 
     // Causal mask: keys [0, n_past] carry 0, the padded tail neg inf.
     {
-        std::vector<ggml_fp16_t> mask((size_t) tg->n_kv_pad);
+        std::vector<ggml_fp16_t> & mask    = tg->mask;
         const ggml_fp16_t          zero    = ggml_fp32_to_fp16(0.0f);
         const ggml_fp16_t          neg_inf = ggml_fp32_to_fp16(-INFINITY);
         for (size_t i = 0; i < mask.size(); i++) {