@@ -2142,18 +2142,17 @@ static bool llama_kv_cache_find_slot(
21422142 }
21432143 // Assuming the tokens are in-order
21442144 if (batch.pos[i] != cache.cells[seq_id].pos + 1) {
2145- // What should happen when the pos backtracks?
2145+ // What should happen when the pos backtracks or skips a value ?
21462146 // Clearing the state mid-batch would require special-casing which isn't done.
2147- LLAMA_LOG_ERROR ("%s: non-consecutive token position %d after %d for sequence %d\n",
2147+ LLAMA_LOG_WARN ("%s: non-consecutive token position %d after %d for sequence %d\n",
21482148 __func__, batch.pos[i], cache.cells[seq_id].pos, seq_id);
2149- return false;
21502149 }
21512150 cache.cells[seq_id].pos = batch.pos[i];
2152- // NOTE: seq_ids are not inserted here, because they are handled when the graph is built.
2151+ // NOTE: seq_ids are not inserted here; they are handled when the input tensors are set
21532152 } else {
21542153 // too big seq_id
21552154 // TODO: would it be possible to resize the KV cache size instead?
2156- LLAMA_LOG_ERROR("%s: seq_id=%d >= kv_size=%d\n", __func__, seq_id, cache.size);
2155+ LLAMA_LOG_ERROR("%s: seq_id=%d >= kv_size=%d Try using a bigger --parallel value \n", __func__, seq_id, cache.size);
21572156 return false;
21582157 }
21592158 }
@@ -2282,24 +2281,26 @@ static void llama_kv_cache_seq_cp(
22822281 if (p1 < 0) p1 = std::numeric_limits<llama_pos>::max();
22832282
22842283 if (cache.unlimited) {
2285- if ((uint32_t)seq_id_dst < cache.size && (uint32_t)seq_id_src < cache.size) {
2286- // intent to "copy from" (does not support copy chains)
2284+ if ((uint32_t) seq_id_dst < cache.size && (uint32_t) seq_id_src < cache.size) {
2285+ seq_id_src = cache.cells[seq_id_src].delta;
2286+ GGML_ASSERT((uint32_t) seq_id_src < cache.size);
2287+ // intent to "copy from"
2288+ // supports copy chains thanks to taking the source of the source
22872289 cache.cells[seq_id_dst].delta = seq_id_src;
2288- // NOTE: a sequence can't have multiple sources, but can have multiple destinations.
2289- // For compatibility with the other KV cache API functions,
2290- // the seq_id(s) of a cell suggests an intent to "copy to" those id(s),
2291- // so that when a sequence is copied, it can initially be found from the source cell.
2292- cache.cells[seq_id_src].seq_id.insert(seq_id_dst);
2293- // prevent the destination from getting cleared
2294- cache.cells[seq_id_dst].seq_id.insert(seq_id_dst);
2290+
2291+ // prevent the destination from getting cleared if the source is not empty
2292+ if (cache.cells[seq_id_src].has_seq_id(seq_id_src)) {
2293+ cache.cells[seq_id_dst].seq_id.insert(seq_id_dst);
2294+ }
22952295 // repurposed as a "need copy" flag
22962296 // (shifting can't be done anyway for this kind of KV cache)
2297- cache.has_shift = seq_id_src != seq_id_dst ;
2298- // NOTE: this is not correct for sequence swaps (which aren't a thing in the KV cache API yet)
2297+ cache.has_shift = true ;
2298+
22992299 cache.cells[seq_id_dst].pos = cache.cells[seq_id_src].pos;
23002300 }
23012301 return;
23022302 }
2303+ // otherwise, this is the KV cache of a Transformer-like model
23032304
23042305 cache.head = 0;
23052306
@@ -2341,7 +2342,14 @@ static void llama_kv_cache_seq_add(
23412342 if (p1 < 0) p1 = std::numeric_limits<llama_pos>::max();
23422343
23432344 if (cache.unlimited) {
2344- GGML_ASSERT(false); // not supported
2345+ // for Mamba-like models, only the pos needs to be shifted
2346+ if (0 <= seq_id && seq_id < (int64_t) cache.size) {
2347+ llama_kv_cell & cell = cache.cells[seq_id];
2348+ if (cell.has_seq_id(seq_id) && p0 <= cell.pos && cell.pos < p1) {
2349+ cell.pos += delta;
2350+ }
2351+ }
2352+ return;
23452353 }
23462354
23472355 for (uint32_t i = 0; i < cache.size; ++i) {
@@ -2378,7 +2386,14 @@ static void llama_kv_cache_seq_div(
23782386 if (p1 < 0) p1 = std::numeric_limits<llama_pos>::max();
23792387
23802388 if (cache.unlimited) {
2381- GGML_ASSERT(false); // not supported
2389+ // for Mamba-like models, only the pos needs to be changed
2390+ if (0 <= seq_id && seq_id < (int64_t) cache.size) {
2391+ llama_kv_cell & cell = cache.cells[seq_id];
2392+ if (cell.has_seq_id(seq_id) && p0 <= cell.pos && cell.pos < p1) {
2393+ cell.pos /= d;
2394+ }
2395+ }
2396+ return;
23822397 }
23832398
23842399 for (uint32_t i = 0; i < cache.size; ++i) {
@@ -8198,7 +8213,6 @@ static void llama_set_inputs(llama_context & lctx, const llama_batch & batch) {
81988213 }
81998214
82008215 if (kv_self.unlimited) {
8201- const int64_t kv_size = kv_self.size;
82028216 const int64_t n_kv = kv_self.n;
82038217
82048218 {
@@ -8214,7 +8228,7 @@ static void llama_set_inputs(llama_context & lctx, const llama_batch & batch) {
82148228 data[i] = (float) has_self_seq;
82158229
82168230 // ensure current sequences will be kept
8217- if (!has_self_seq) {
8231+ if (!has_self_seq && kv_cell.pos >= 0 ) {
82188232 kv_cell.seq_id.insert(seq_id);
82198233 }
82208234 }
@@ -8243,21 +8257,6 @@ static void llama_set_inputs(llama_context & lctx, const llama_batch & batch) {
82438257 }
82448258 }
82458259 }
8246- // remove extraneous seq_ids when state copies are made
8247- if (kv_self.has_shift) {
8248- for (int i = 0; i < kv_size; ++i) {
8249- llama_kv_cell & kv_cell = lctx.kv_self.cells[i];
8250- uint32_t n_seqs = kv_cell.seq_id.size();
8251- bool has_self_seq = kv_cell.has_seq_id(i);
8252-
8253- if (has_self_seq && n_seqs > 1) {
8254- kv_cell.seq_id.clear();
8255- kv_cell.seq_id.insert(i);
8256- } else if (!has_self_seq && n_seqs > 0) {
8257- kv_cell.seq_id.clear();
8258- }
8259- }
8260- }
82618260 }
82628261}
82638262
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