vbatts/llama.cpp
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Merge branch 'concedo_experimental' into concedo

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Concedo 2023-04-19 15:35:48 +08:00
commit 65bfcdb1cc
8 changed files with 70 additions and 46 deletions
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22
gpttype_adapter.cpp
View file

@ -251,9 +251,13 @@ generation_outputs gpttype_generate(const generation_inputs inputs, generation_o
std::fill(last_n_tokens.begin(), last_n_tokens.end(), 0);
n_past = 0;
if(file_format!=FileFormat::RWKV_1)
if (file_format == FileFormat::RWKV_1)
{
ContextFastForward(current_context_tokens, embd_inp, n_past, last_n_tokens, nctx, smartcontext, useSmartContext);
ContextFastForward(current_context_tokens, embd_inp, n_past, last_n_tokens, nctx, smartcontext, false, true);
}
else
{
ContextFastForward(current_context_tokens, embd_inp, n_past, last_n_tokens, nctx, smartcontext, useSmartContext, false);
}
//if using BLAS and prompt is big enough, switch to single thread and use a huge batch
@ -303,7 +307,19 @@ generation_outputs gpttype_generate(const generation_inputs inputs, generation_o
else if(file_format == FileFormat::RWKV_1)
{
n_vocab = vocab.id_to_token.size(); //handled seperately
rwkv_context_v1->state_in = nullptr;
if(n_past==0)
{
rwkv_context_v1->state_in = nullptr;
}
else
{
rwkv_context_v1->state_in = rwkv_context_v1->state_out;
//if it's empty, push in the final previous token
if(embd_inp.size()==0 && current_context_tokens.size()>0)
{
embd_inp.push_back(current_context_tokens[current_context_tokens.size()-1]);
}
}
}
else
{

11
koboldcpp.py
View file

@ -1,7 +1,6 @@
# A hacky little script from Concedo that exposes llama.cpp function bindings
# allowing it to be used via a simulated kobold api endpoint
# it's not very usable as there is a fundamental flaw with llama.cpp
# which causes generation delay to scale linearly with original prompt length.
# generation delay scales linearly with original prompt length.
import ctypes
import os
@ -399,17 +398,17 @@ def main(args):
root.destroy()
if not ggml_selected_file:
print("\nNo ggml model file was selected. Exiting.")
time.sleep(1)
time.sleep(2)
sys.exit(2)
except Exception as ex:
print("File selection GUI unsupported. Please check command line: script.py --help")
time.sleep(1)
time.sleep(2)
sys.exit(2)
if not os.path.exists(ggml_selected_file):
print(f"Cannot find model file: {ggml_selected_file}")
time.sleep(1)
time.sleep(2)
sys.exit(2)
mdl_nparts = sum(1 for n in range(1, 9) if os.path.exists(f"{ggml_selected_file}.{n}")) + 1
@ -420,7 +419,7 @@ def main(args):
if not loadok:
print("Could not load model: " + modelname)
time.sleep(1)
time.sleep(2)
sys.exit(3)
try:
basepath = os.path.abspath(os.path.dirname(__file__))

2
llama_adapter.cpp
View file

@ -145,7 +145,7 @@ generation_outputs llama_generate(const generation_inputs inputs, generation_out
std::fill(last_n_tokens.begin(), last_n_tokens.end(), 0);
n_past = 0;
ContextFastForward(current_context_tokens, embd_inp, n_past, last_n_tokens, nctx, smartcontext, useSmartContext);
ContextFastForward(current_context_tokens, embd_inp, n_past, last_n_tokens, nctx, smartcontext, useSmartContext,false);
//if using BLAS and prompt is big enough, switch to single thread and use a huge batch
bool blasmode = (embd_inp.size() >= 32 && ggml_cpu_has_blas());

71
model_adapter.cpp
View file

@ -236,7 +236,8 @@ void print_tok_vec(std::vector<float> &embd)
}
void ContextFastForward(std::vector<int> &current_context_tokens, std::vector<int> &embd_inp,
int &n_past, std::vector<int> &last_n_tokens, const int nctx, std::vector<int> &smartcontext, bool useSmartContext)
int &n_past, std::vector<int> &last_n_tokens, const int nctx, std::vector<int> &smartcontext,
bool useSmartContext, const bool requireFullSubset)
{
const int SCCtxLenThreshold = nctx * 0.8; //how much context length must be reach to trigger smartcontext
const int SCInpLenThreshold = nctx * 0.6; //how big must the input array be to trigger smartcontext
@ -244,13 +245,11 @@ void print_tok_vec(std::vector<float> &embd)
const float SCTruncationRatio = 0.5; //ratio for how many tokens to fast forward
const int SCTokThreshold = 32 + (nctx*0.05); //how many tokens of similarity triggers smartcontext
// printf("\nORIGINAL CTX:\n");
// print_tok_vec(current_context_tokens);
// printf("\nORIGINAL EMBD:\n");
// print_tok_vec(embd_inp);
//fast forward the past based on identical tokens, stop once a divergence is noted
int embd_inp_len = embd_inp.size();
bool fastforwardok = true;
for (int i = 0; i < current_context_tokens.size(); ++i)
{
if (current_context_tokens[i] == embd_inp[i])
@ -260,37 +259,48 @@ void print_tok_vec(std::vector<float> &embd)
}
else
{
if(requireFullSubset) //RWKV can only do this if embd_inp contains everything in current context
{
last_n_tokens.erase(last_n_tokens.end() - n_past, last_n_tokens.end());
n_past = 0;
fastforwardok = false;
}
break;
}
if ((i + 2) >= embd_inp_len)
if (requireFullSubset) //RWKV can only do this if embd_inp contains everything in current context
{
break;
if (i >= embd_inp_len)
{
last_n_tokens.erase(last_n_tokens.end() - n_past, last_n_tokens.end());
n_past = 0;
fastforwardok = false;
break;
}
}
else
{
if ((i + 2) >= embd_inp_len)
{
break;
}
}
}
last_n_tokens.erase(last_n_tokens.begin(), last_n_tokens.begin() + n_past);
embd_inp.erase(embd_inp.begin(), embd_inp.begin() + n_past);
embd_inp_len = embd_inp.size();
if(fastforwardok)
{
last_n_tokens.erase(last_n_tokens.begin(), last_n_tokens.begin() + n_past);
embd_inp.erase(embd_inp.begin(), embd_inp.begin() + n_past);
embd_inp_len = embd_inp.size();
}
//smart context mode, detect if we have a shifted context at max length
//requirement: previous context was at least nctx/2 longer than current,
//mode is on, and current context already maxed.
// printf("\nconds: %d %d %d\n",current_context_tokens.size() >= nctx*0.8
// ,embd_inp_len >= nctx*0.6 ,current_context_tokens.size() - n_past > nctx*0.5);
// printf("csiz:%d par:%d eilen:%d np:%d",current_context_tokens.size(), (int)(nctx*0.8),embd_inp_len,n_past);
if (useSmartContext && smartcontext.size() > 0 && embd_inp_len >= SCInpLenThreshold)
if (fastforwardok && useSmartContext && smartcontext.size() > 0 && embd_inp_len >= SCInpLenThreshold)
{
// printf("curfullcontext:\n");
// print_tok_vec(current_context_tokens);
//see if smartcontext is still usable
// printf("smartctx:\n");
// print_tok_vec(smartcontext);
// printf("embinp:\n");
// print_tok_vec(embd_inp);
//see if smartcontext is still usable
auto shared = LongestCommonSubseq(smartcontext, embd_inp);
if (shared.size() > SCTokThreshold && ArrStartWith(smartcontext, shared)) //at least 32 tokens in common
{
@ -300,8 +310,6 @@ void print_tok_vec(std::vector<float> &embd)
auto trimmed = std::vector<int>(embd_inp.begin() + found, embd_inp.end());
embd_inp = trimmed;
embd_inp_len = embd_inp.size();
// printf("trimmed:\n");
// print_tok_vec(embd_inp,&vocab.id_to_token);
printf("\n[Reusing Smart Context: %d allowance remaining]", found);
int old_n_past = n_past;
@ -313,7 +321,6 @@ void print_tok_vec(std::vector<float> &embd)
for (int i = n_past; i < current_context_tokens.size(); ++i)
{
//printf("\n%s and %s\n",vocab.id_to_token[current_context_tokens[i]].c_str(), vocab.id_to_token[embd_inp[i-offset_fix]].c_str());
if (current_context_tokens[i] == embd_inp[i-offset_fix])
{
n_past += 1;
@ -331,8 +338,7 @@ void print_tok_vec(std::vector<float> &embd)
last_n_tokens.erase(last_n_tokens.begin(), last_n_tokens.begin() + (n_past-old_n_past));
embd_inp.erase(embd_inp.begin(), embd_inp.begin() + (n_past-old_n_past));
// printf("np:%d newembinp: \n",n_past);
// print_tok_vec(embd_inp);
}else{
smartcontext.clear();
}
@ -347,17 +353,16 @@ void print_tok_vec(std::vector<float> &embd)
smartcontext.clear();
}
if(useSmartContext
if(fastforwardok && useSmartContext
&& smartcontext.size()==0 && current_context_tokens.size() >= SCCtxLenThreshold
&& embd_inp_len >= SCInpLenThreshold
&& current_context_tokens.size() - n_past > SCPastLenThreshold)
{
{
//determine longest common substring after removing start part
int shiftamt = embd_inp.size() * SCTruncationRatio;
smartcontext = std::vector<int>(embd_inp.begin() + shiftamt, embd_inp.end());
printf("\n[New Smart Context Triggered! Buffered Token Allowance: %d]",shiftamt);
// printf("smartctx:\n");
// print_tok_vec(smartcontext,&vocab.id_to_token);
embd_inp = smartcontext;
//if max ctx length is exceeded, chop the prompt in half after the start part, and memorize it. The memorized part becomes LCS marker.
//when a future prompt comes in, find the LCS again. If LCS > a length and LCS starts with memorized LCS

3
model_adapter.h
View file

@ -54,4 +54,5 @@ int ArrFindIndexOf(const std::vector<int> targetArray, const std::vector<int> se
FileFormat check_file_format(const std::string & fname);
void ContextFastForward(std::vector<int> &current_context_tokens, std::vector<int> &embd_inp,
int &n_past, std::vector<int> &last_n_tokens, const int nctx, std::vector<int> &smartcontext, const bool useSmartContext);
int &n_past, std::vector<int> &last_n_tokens, const int nctx, std::vector<int> &smartcontext,
const bool useSmartContext, const bool requireFullSubset);

2
otherarch/gpt2_v2.cpp
View file

@ -371,7 +371,7 @@ bool gpt2_eval(
const int n_vocab = hparams.n_vocab;
//todo: there is a bug that causes the buffer to oom and I cannot figure it out, hack to increase size for now
static size_t buf_size = 1024u*1024*1024;
static size_t buf_size = 1280u*1024*1024;
static void * buf = malloc(buf_size);
if (mem_per_token > 0 && mem_per_token*N > buf_size) {

2
otherarch/gptj_v2.cpp
View file

@ -382,7 +382,7 @@ bool gptj_eval(
const int d_key = n_embd/n_head;
//todo: there is a bug that causes the buffer to oom and I cannot figure it out, hack to increase size for now
static size_t buf_size = 1024u*1024*1024;
static size_t buf_size = 1280u*1024*1024;
static void * buf = malloc(buf_size);
if (mem_per_token > 0 && mem_per_token*N > buf_size) {

3
otherarch/rwkv.cpp
View file

@ -1,3 +1,6 @@
//adapted from RWKV.cpp repo under MIT license
// https://github.com/saharNooby/rwkv.cpp
#include "rwkv.h"
#include "ggml_rwkv.h"
#include "otherarch.h"