vbatts/llama.cpp
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fixes to smartcontextpro

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Concedo 2023-10-29 10:42:37 +08:00
parent 20ef442c2a
commit 338d6c265d
2 changed files with 25 additions and 13 deletions
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34
gpttype_adapter.cpp
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@ -247,7 +247,7 @@ static std::string RemoveBell(const std::string & input) //removes the bell char
return word2; return word2;
} }
static std::string print_tok_vec_str(std::vector<int> &embd) static std::string get_tok_vec_str(std::vector<int> &embd)
{ {
std::string tmp = ""; std::string tmp = "";
for (auto id : embd) for (auto id : embd)
@ -257,6 +257,10 @@ static std::string print_tok_vec_str(std::vector<int> &embd)
::utreplace(tmp, "\n", "\\n"); ::utreplace(tmp, "\n", "\\n");
return tmp; return tmp;
} }
static void print_tok_vec_str(std::vector<int> &vec)
{
printf("\n%s", get_tok_vec_str(vec).c_str());
}
llama_token sample_token(llama_token_data_array * candidates, std::mt19937 & rng) llama_token sample_token(llama_token_data_array * candidates, std::mt19937 & rng)
@ -583,7 +587,7 @@ static void load_grammar(const std::string & gammarstr)
//given an old GGUF context and a new context that has some middle portion removed, //given an old GGUF context and a new context that has some middle portion removed,
//find and remove the middle portion from the old context from the KV. Does not fast forward after this destructive action //find and remove the middle portion from the old context from the KV. Does not fast forward after this destructive action
void PurgeMissingTokens(llama_context * ctx, std::vector<int> &current_context_tokens, std::vector<int> &new_context_tokens, const int genamt) void PurgeMissingTokens(llama_context * ctx, std::vector<int> &current_context_tokens, std::vector<int> &new_context_tokens, const int genamt, const int nctx)
{ {
//scan from start old and new ctx, until first mismatch found, save as p0 //scan from start old and new ctx, until first mismatch found, save as p0
//check remaining old and new ctx for longest common subseq, which needs to be at 256 tokens //check remaining old and new ctx for longest common subseq, which needs to be at 256 tokens
@ -591,8 +595,8 @@ void PurgeMissingTokens(llama_context * ctx, std::vector<int> &current_context_t
//if passed, save beginning of LCQ from old ctx as p1 //if passed, save beginning of LCQ from old ctx as p1
//remove all tokens from old ctx between p0 and p1, updating both arrays and kv, then continue as normal //remove all tokens from old ctx between p0 and p1, updating both arrays and kv, then continue as normal
const int ShortfallThreshold = 256; //dont trigger shifting if the distance between trimstart and currhead < this const int ShortfallThreshold = 200; //dont trigger shifting if the distance between trimstart and currhead < this
const int SlackAllowance = 64; //in case the end text is slightly modified, be forgiving const int SlackAllowance = 50; //in case the end text is slightly modified, be forgiving
int trimstart = 0; int trimstart = 0;
int new_tokens_len = new_context_tokens.size(); int new_tokens_len = new_context_tokens.size();
@ -621,7 +625,7 @@ void PurgeMissingTokens(llama_context * ctx, std::vector<int> &current_context_t
} }
//at least this many tokens need to match, otherwise don't bother trimming //at least this many tokens need to match, otherwise don't bother trimming
const int LCSTokThreshold = std::max((new_tokens_len - trimstart) - (genamt+SlackAllowance), ShortfallThreshold-SlackAllowance); const int LCSTokThreshold = std::max(std::min((new_tokens_len - trimstart) - (genamt+SlackAllowance), (int)(nctx*0.55)), ShortfallThreshold-SlackAllowance);
auto curr_ctx_without_memory = std::vector<int>(current_context_tokens.begin() + trimstart, current_context_tokens.end()); auto curr_ctx_without_memory = std::vector<int>(current_context_tokens.begin() + trimstart, current_context_tokens.end());
auto new_ctx_without_memory = std::vector<int>(new_context_tokens.begin() + trimstart, new_context_tokens.end()); auto new_ctx_without_memory = std::vector<int>(new_context_tokens.begin() + trimstart, new_context_tokens.end());
@ -956,7 +960,8 @@ ModelLoadResult gpttype_load_model(const load_model_inputs inputs, FileFormat in
//determine mem per token //determine mem per token
std::vector<int> tmp = {1, 2, 3, 4}; std::vector<int> tmp = {1, 2, 3, 4};
auto er = llama_eval(llama_ctx_v4, tmp.data(), tmp.size(), 0); llama_kv_cache_tokens_rm(llama_ctx_v4, -1, -1);
auto er = llama_decode(llama_ctx_v4, llama_batch_get_one(tmp.data(), tmp.size(), 0, 0));
if(er!=0) if(er!=0)
{ {
printf("\nLLAMA EVAL returned nonzero!\n"); printf("\nLLAMA EVAL returned nonzero!\n");
@ -1459,12 +1464,19 @@ generation_outputs gpttype_generate(const generation_inputs inputs, generation_o
else else
{ {
bool triggersc = useSmartContext; bool triggersc = useSmartContext;
if(useSmartContext && file_format == FileFormat::GGUF_LLAMA || file_format==FileFormat::GGUF_FALCON) if(file_format == FileFormat::GGUF_LLAMA || file_format==FileFormat::GGUF_FALCON)
{ {
PurgeMissingTokens(llama_ctx_v4, current_context_tokens, embd_inp, inputs.max_length); if(useSmartContext)
{
PurgeMissingTokens(llama_ctx_v4, current_context_tokens, embd_inp, inputs.max_length, nctx);
triggersc = false; triggersc = false;
} }
}
ContextFastForward(current_context_tokens, embd_inp, n_past, last_n_tokens, nctx, smartcontext, triggersc, false); ContextFastForward(current_context_tokens, embd_inp, n_past, last_n_tokens, nctx, smartcontext, triggersc, false);
if(file_format == FileFormat::GGUF_LLAMA || file_format==FileFormat::GGUF_FALCON)
{
llama_kv_cache_seq_rm(llama_ctx_v4, 0, n_past, -1);
}
} }
//if using BLAS and prompt is big enough, switch to single thread and use a huge batch //if using BLAS and prompt is big enough, switch to single thread and use a huge batch
@ -1603,9 +1615,9 @@ generation_outputs gpttype_generate(const generation_inputs inputs, generation_o
{ {
std::string outstr = ""; std::string outstr = "";
printf("\n[Debug: Dump Input Tokens, format: %d]\n", file_format); printf("\n[Debug: Dump Input Tokens, format: %d]\n", file_format);
outstr += print_tok_vec_str(embd_inp); outstr += get_tok_vec_str(embd_inp);
outstr += "\n\n[Debug: n_past="+std::to_string(n_past)+" Context Size = " + std::to_string(current_context_tokens.size()) + "]\n"; outstr += "\n\n[Debug: n_past="+std::to_string(n_past)+" Context Size = " + std::to_string(current_context_tokens.size()) + "]\n";
outstr += print_tok_vec_str(current_context_tokens); outstr += get_tok_vec_str(current_context_tokens);
printf("%s\n\n", RemoveBell(outstr).c_str()); printf("%s\n\n", RemoveBell(outstr).c_str());
} }
@ -1636,7 +1648,7 @@ generation_outputs gpttype_generate(const generation_inputs inputs, generation_o
} }
else if(file_format == FileFormat::GGUF_LLAMA || file_format==FileFormat::GGUF_FALCON) else if(file_format == FileFormat::GGUF_LLAMA || file_format==FileFormat::GGUF_FALCON)
{ {
evalres = (llama_eval(llama_ctx_v4, embd.data(), embdsize, n_past)==0); evalres = (llama_decode(llama_ctx_v4, llama_batch_get_one(embd.data(), embdsize, n_past, 0))==0);
} }
else if(file_format==FileFormat::RWKV_1 || file_format==FileFormat::RWKV_2) else if(file_format==FileFormat::RWKV_1 || file_format==FileFormat::RWKV_2)
{ {

2
llama.cpp
View file

@ -9836,7 +9836,7 @@ int llama_eval(
llama_token * tokens, llama_token * tokens,
int32_t n_tokens, int32_t n_tokens,
int n_past) { int n_past) {
llama_kv_cache_seq_rm(ctx->kv_self, 0, n_past, -1); llama_kv_cache_tokens_rm(ctx->kv_self, n_past, -1);
const int ret = llama_decode_internal(*ctx, llama_batch_get_one(tokens, n_tokens, n_past, 0)); const int ret = llama_decode_internal(*ctx, llama_batch_get_one(tokens, n_tokens, n_past, 0));
if (ret < 0) { if (ret < 0) {