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server : fix context shift (#5195)

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* server : fix context shift + simplify self-extend

* server : take system_tokens into account

* server : more n_past fixes

* server : rever n_past_se changes
This commit is contained in:
Georgi Gerganov 2024-01-30 20:17:30 +02:00 committed by GitHub
parent 4003be0e5f
commit e6f291d158
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2 changed files with 60 additions and 50 deletions
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1
examples/server/chat.sh
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@ -48,6 +48,7 @@ chat_completion() {
top_p: 0.9, top_p: 0.9,
n_keep: $n_keep, n_keep: $n_keep,
n_predict: 256, n_predict: 256,
cache_prompt: true,
stop: ["\n### Human:"], stop: ["\n### Human:"],
stream: true stream: true
}')" }')"

33
examples/server/server.cpp
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@ -220,6 +220,7 @@ struct llama_client_slot
infill = false; infill = false;
ga_i = 0; ga_i = 0;
n_past_se = 0; n_past_se = 0;
generated_token_probs.clear(); generated_token_probs.clear();
for (slot_image & img : images) for (slot_image & img : images)
@ -1227,7 +1228,7 @@ struct llama_server_context
std::vector<llama_token> append_tokens = tokenize(json_prompt, false); // has next image std::vector<llama_token> append_tokens = tokenize(json_prompt, false); // has next image
for (int i = 0; i < (int) append_tokens.size(); ++i) for (int i = 0; i < (int) append_tokens.size(); ++i)
{ {
llama_batch_add(batch, append_tokens[i], slot.n_past, { slot.id }, true); llama_batch_add(batch, append_tokens[i], system_tokens.size() + slot.n_past, { slot.id }, true);
slot.n_past += 1; slot.n_past += 1;
} }
} }
@ -1295,6 +1296,8 @@ struct llama_server_context
for (llama_client_slot &slot : slots) for (llama_client_slot &slot : slots)
{ {
slot.cache_tokens.clear(); slot.cache_tokens.clear();
slot.n_past = 0;
slot.n_past_se = 0;
} }
} }
@ -1364,26 +1367,26 @@ struct llama_server_context
kv_cache_clear(); kv_cache_clear();
} }
return true; return true;
} else { }
task_server task; task_server task;
task.type = TASK_TYPE_NEXT_RESPONSE; task.type = TASK_TYPE_NEXT_RESPONSE;
task.target_id = -1; task.target_id = -1;
queue_tasks.post(task); queue_tasks.post(task);
}
for (llama_client_slot &slot : slots) for (llama_client_slot &slot : slots)
{ {
if (slot.ga_n == 1) if (slot.ga_n == 1)
{ {
if (slot.is_processing() && slot.cache_tokens.size() >= (size_t) slot.n_ctx) if (slot.is_processing() && system_tokens.size() + slot.cache_tokens.size() >= (size_t) slot.n_ctx)
{ {
// Shift context // Shift context
const int n_left = slot.n_past - slot.params.n_keep - 1; const int n_left = system_tokens.size() + slot.n_past - slot.params.n_keep - 1;
const int n_discard = n_left / 2; const int n_discard = n_left / 2;
LOG_TEE("slot %d: context shift - n_keep = %d, n_left = %d, n_discard = %d\n", slot.id, slot.params.n_keep, n_left, n_discard); LOG_TEE("slot %d: context shift - n_keep = %d, n_left = %d, n_discard = %d\n", slot.id, slot.params.n_keep, n_left, n_discard);
llama_kv_cache_seq_rm (ctx, slot.id, slot.params.n_keep + 1 , slot.params.n_keep + n_discard + 1); llama_kv_cache_seq_rm (ctx, slot.id, slot.params.n_keep + 1 , slot.params.n_keep + n_discard + 1);
llama_kv_cache_seq_shift(ctx, slot.id, slot.params.n_keep + 1 + n_discard, slot.n_past, -n_discard); llama_kv_cache_seq_shift(ctx, slot.id, slot.params.n_keep + 1 + n_discard, system_tokens.size() + slot.n_past, -n_discard);
for (size_t i = slot.params.n_keep + 1 + n_discard; i < slot.cache_tokens.size(); i++) for (size_t i = slot.params.n_keep + 1 + n_discard; i < slot.cache_tokens.size(); i++)
{ {
@ -1429,8 +1432,10 @@ struct llama_server_context
slot.i_batch = batch.n_tokens; slot.i_batch = batch.n_tokens;
const int32_t slot_npast = slot.n_past_se > 0 ? slot.n_past_se : slot.n_past; const int32_t slot_npast = slot.n_past_se > 0 ? slot.n_past_se : slot.n_past;
llama_batch_add(batch, slot.sampled, system_tokens.size() + slot_npast, { slot.id }, true);
// TODO: we always have to take into account the "system_tokens"
// this is not great and needs to be improved somehow
llama_batch_add(batch, slot.sampled, system_tokens.size() + slot_npast, { slot.id }, true);
slot.n_past += 1; slot.n_past += 1;
} }
@ -1591,10 +1596,13 @@ struct llama_server_context
// process the prefix of first image // process the prefix of first image
std::vector<llama_token> prefix_tokens = has_images ? tokenize(slot.images[0].prefix_prompt, add_bos_token) : prompt_tokens; std::vector<llama_token> prefix_tokens = has_images ? tokenize(slot.images[0].prefix_prompt, add_bos_token) : prompt_tokens;
int32_t slot_npast = slot.n_past_se > 0 ? slot.n_past_se : slot.n_past; int32_t slot_npast = slot.n_past_se > 0 ? slot.n_past_se : slot.n_past;
int ga_i = slot.ga_i;
int32_t ga_i = slot.ga_i;
int32_t ga_n = slot.ga_n; int32_t ga_n = slot.ga_n;
int32_t ga_w = slot.ga_w; int32_t ga_w = slot.ga_w;
for (; slot.n_past < (int) prefix_tokens.size(); ++slot.n_past) for (; slot.n_past < (int) prefix_tokens.size(); ++slot.n_past)
{ {
if (slot.ga_n != 1) if (slot.ga_n != 1)
@ -1606,7 +1614,7 @@ struct llama_server_context
} }
} }
llama_batch_add(batch, prefix_tokens[slot.n_past], system_tokens.size() + slot_npast, {slot.id }, false); llama_batch_add(batch, prefix_tokens[slot.n_past], system_tokens.size() + slot_npast, {slot.id }, false);
slot_npast += 1; slot_npast++;
} }
if (has_images && !ingest_images(slot, n_batch)) if (has_images && !ingest_images(slot, n_batch))
@ -1666,6 +1674,7 @@ struct llama_server_context
slot.n_past_se += n_tokens; slot.n_past_se += n_tokens;
} }
} }
llama_batch batch_view = llama_batch batch_view =
{ {
n_tokens, n_tokens,
@ -1818,15 +1827,15 @@ static void server_print_usage(const char *argv0, const gpt_params &params,
printf(" -np N, --parallel N number of slots for process requests (default: %d)\n", params.n_parallel); printf(" -np N, --parallel N number of slots for process requests (default: %d)\n", params.n_parallel);
printf(" -cb, --cont-batching enable continuous batching (a.k.a dynamic batching) (default: disabled)\n"); printf(" -cb, --cont-batching enable continuous batching (a.k.a dynamic batching) (default: disabled)\n");
printf(" -spf FNAME, --system-prompt-file FNAME\n"); printf(" -spf FNAME, --system-prompt-file FNAME\n");
printf(" Set a file to load a system prompt (initial prompt of all slots), this is useful for chat applications.\n"); printf(" set a file to load a system prompt (initial prompt of all slots), this is useful for chat applications.\n");
printf(" --mmproj MMPROJ_FILE path to a multimodal projector file for LLaVA.\n"); printf(" --mmproj MMPROJ_FILE path to a multimodal projector file for LLaVA.\n");
printf(" --log-disable disables logging to a file.\n"); printf(" --log-disable disables logging to a file.\n");
printf("\n"); printf("\n");
printf(" --override-kv KEY=TYPE:VALUE\n"); printf(" --override-kv KEY=TYPE:VALUE\n");
printf(" advanced option to override model metadata by key. may be specified multiple times.\n"); printf(" advanced option to override model metadata by key. may be specified multiple times.\n");
printf(" types: int, float, bool. example: --override-kv tokenizer.ggml.add_bos_token=bool:false\n"); printf(" types: int, float, bool. example: --override-kv tokenizer.ggml.add_bos_token=bool:false\n");
printf(" -gan N, --grp-attn-n N Set the group attention factor to extend context size through self-extend(default: 1=disabled), used together with group attention width `--grp-attn-w`"); printf(" -gan N, --grp-attn-n N set the group attention factor to extend context size through self-extend(default: 1=disabled), used together with group attention width `--grp-attn-w`");
printf(" -gaw N, --grp-attn-w N Set the group attention width to extend context size through self-extend(default: 512), used together with group attention factor `--grp-attn-n`"); printf(" -gaw N, --grp-attn-w N set the group attention width to extend context size through self-extend(default: 512), used together with group attention factor `--grp-attn-n`");
printf("\n"); printf("\n");
} }