batch : require non-coupled batch with sequential split_equal

ggml-ci

src/llama-batch.cpp

@@ -166,6 +166,8 @@ bool llama_batch_allocr::init(
 
                 // note: tracking the other way around is not necessary for now
                 //seq_cpl[s0][s1] = true;
+
+                has_cpl = true;
             }
         }
     }
@@ -403,6 +405,10 @@ uint32_t llama_batch_allocr::get_n_outputs() const {
     return n_outputs;
 }
 
+uint32_t llama_batch_allocr::get_n_used() const {
+    return n_used;
+}
+
 std::vector<int32_t> & llama_batch_allocr::get_out_ids() {
     return out_ids;
 }
@@ -418,6 +424,8 @@ llama_pos llama_batch_allocr::seq_pos_max(llama_seq_id seq_id) const {
 void llama_batch_allocr::split_reset() {
     out_ids.clear();
 
+    n_used = 0;
+
     used.clear();
     used.resize(get_n_tokens(), false);
 
@@ -442,6 +450,7 @@ llama_ubatch llama_batch_allocr::split_simple(uint32_t n_ubatch) {
         idxs.push_back(cur_idx);
 
         used[cur_idx] = true;
+        ++n_used;
 
         ++cur_idx;
 
@@ -458,6 +467,12 @@ llama_ubatch llama_batch_allocr::split_simple(uint32_t n_ubatch) {
 }
 
 llama_ubatch llama_batch_allocr::split_equal(uint32_t n_ubatch, bool sequential) {
+    if (sequential && has_cpl) {
+        LLAMA_LOG_ERROR("%s: sequential split is not supported when there are coupled sequences in the input batch\n", __func__);
+
+        return {};
+    }
+
     std::vector<seq_set_t> cur_seq_set;
 
     llama_seq_id last_seq_id = -1;
@@ -536,6 +551,7 @@ llama_ubatch llama_batch_allocr::split_equal(uint32_t n_ubatch, bool sequential)
             idxs_per_seq[s].push_back(idx);
 
             used[idx] = true;
+            ++n_used;
 
             ++cur_idx[s];
         }
@@ -577,6 +593,7 @@ llama_ubatch llama_batch_allocr::split_seq(uint32_t n_ubatch) {
         idxs.push_back(cur_idx);
 
         used[cur_idx] = true;
+        ++n_used;
 
         if (idxs.size() >= n_ubatch) {
             break;

src/llama-batch.h

@@ -54,6 +54,7 @@ public:
 
     uint32_t get_n_tokens()  const;
     uint32_t get_n_outputs() const;
+    uint32_t get_n_used()    const;
 
     // the array of output indices in the order they were encountered during the ubatch splitting
     std::vector<int32_t> & get_out_ids();
@@ -113,6 +114,9 @@ private:
     using pos_set_t = std::set<llama_pos>;
     using seq_cpl_t = std::vector<bool>;
 
+    // helper flag to quickly determine if there are any coupled sequences in the batch
+    bool has_cpl;
+
     std::vector<pos_set_t> seq_pos; // seq_pos[s]: the set of positions in sequence s
     std::vector<seq_cpl_t> seq_cpl; // seq_cpl[s0][s1]: if sequence s0 is coupled to sequence s1
 
@@ -126,6 +130,8 @@ private:
     // batch indices of the output
     std::vector<int32_t> out_ids;
 
+    uint32_t n_used;
+
     // used[i] indicates if token i has already been used in a previous ubatch
     std::vector<bool> used;
 

src/llama-kv-cache-unified-iswa.cpp

@@ -119,6 +119,11 @@ llama_memory_context_ptr llama_kv_cache_unified_iswa::init_batch(llama_batch_all
             ubatches.push_back(std::move(ubatch)); // NOLINT
         }
 
+        if (balloc.get_n_used() < balloc.get_n_tokens()) {
+            // failed to find a suitable split
+            break;
+        }
+
         auto sinfos_base = kv_base->prepare(ubatches);
         if (sinfos_base.empty()) {
             break;
@@ -150,6 +155,11 @@ llama_memory_context_ptr llama_kv_cache_unified_iswa::init_batch(llama_batch_all
             ubatches.push_back(std::move(ubatch)); // NOLINT
         }
 
+        if (balloc.get_n_used() < balloc.get_n_tokens()) {
+            // failed to find a suitable split
+            break;
+        }
+
         auto sinfos_base = kv_base->prepare(ubatches);
         if (sinfos_base.empty()) {
             break;

src/llama-kv-cache-unified.cpp

@@ -427,6 +427,11 @@ llama_memory_context_ptr llama_kv_cache_unified::init_batch(
             ubatches.push_back(std::move(ubatch)); // NOLINT
         }
 
+        if (balloc.get_n_used() < balloc.get_n_tokens()) {
+            // failed to find a suitable split
+            break;
+        }
+
         auto sinfos = prepare(ubatches);
         if (sinfos.empty()) {
             break;

src/llama-memory-hybrid.cpp

@@ -81,6 +81,11 @@ llama_memory_context_ptr llama_memory_hybrid::init_batch(llama_batch_allocr & ba
             ubatches.push_back(std::move(ubatch)); // NOLINT
         }
 
+        if (balloc.get_n_used() < balloc.get_n_tokens()) {
+            // failed to find a suitable split
+            break;
+        }
+
         // prepare the recurrent batches first
         if (!mem_recr->prepare(ubatches)) {
             // TODO: will the recurrent cache be in an undefined context at this point?

src/llama-memory-recurrent.cpp

@@ -365,26 +365,35 @@ llama_pos llama_memory_recurrent::seq_pos_max(llama_seq_id seq_id) const {
 llama_memory_context_ptr llama_memory_recurrent::init_batch(llama_batch_allocr & balloc, uint32_t n_ubatch, bool embd_all) {
     std::vector<llama_ubatch> ubatches;
 
-    while (true) {
-        llama_ubatch ubatch;
+    do {
+        balloc.split_reset();
 
-        if (embd_all) {
-            // if all tokens are output, split by sequence
-            ubatch = balloc.split_seq(n_ubatch);
-        } else {
-            ubatch = balloc.split_equal(n_ubatch, false);
+        while (true) {
+            llama_ubatch ubatch;
+
+            if (embd_all) {
+                // if all tokens are output, split by sequence
+                ubatch = balloc.split_seq(n_ubatch);
+            } else {
+                ubatch = balloc.split_equal(n_ubatch, false);
+            }
+
+            if (ubatch.n_tokens == 0) {
+                break;
+            }
+
+            ubatches.push_back(std::move(ubatch)); // NOLINT
         }
 
-        if (ubatch.n_tokens == 0) {
+        if (balloc.get_n_used() < balloc.get_n_tokens()) {
+            // failed to find a suitable split
             break;
         }
 
-        ubatches.push_back(std::move(ubatch)); // NOLINT
-    }
-
-    if (!prepare(ubatches)) {
-        return std::make_unique<llama_memory_recurrent_context>(LLAMA_MEMORY_STATUS_FAILED_PREPARE);
-    }
+        if (!prepare(ubatches)) {
+            return std::make_unique<llama_memory_recurrent_context>(LLAMA_MEMORY_STATUS_FAILED_PREPARE);
+        }
+    } while (false);
 
     return std::make_unique<llama_memory_recurrent_context>(this, std::move(ubatches));
 }