mirror of
https://github.com/LostRuins/koboldcpp.git
synced 2025-09-09 16:44:35 +00:00
277 lines
10 KiB
C++
277 lines
10 KiB
C++
//This is Concedo's shitty adapter for adding python bindings for llama
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//Considerations:
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//Don't want to use pybind11 due to dependencies on MSVCC
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//ZERO or MINIMAL changes as possible to main.cpp - do not move their function declarations here!
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//Leave main.cpp UNTOUCHED, We want to be able to update the repo and pull any changes automatically.
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//No dynamic memory allocation! Setup structs with FIXED (known) shapes and sizes for ALL output fields
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//Python will ALWAYS provide the memory, we just write to it.
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#include <cassert>
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#include <cstring>
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#include <fstream>
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#include <regex>
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#include <iostream>
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#include <iterator>
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#include <queue>
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#include <string>
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#include <math.h>
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#include <cstdint>
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#include "expose.h"
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#include "model_adapter.cpp"
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extern "C"
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{
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std::string platformenv, deviceenv, vulkandeviceenv;
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//return val: 0=fail, 1=(original ggml, alpaca), 2=(ggmf), 3=(ggjt)
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static FileFormat file_format = FileFormat::BADFORMAT;
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static FileFormatExtraMeta file_format_meta;
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bool load_model(const load_model_inputs inputs)
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{
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std::string model = inputs.model_filename;
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lora_filename = inputs.lora_filename;
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lora_base = inputs.lora_base;
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int forceversion = inputs.forceversion;
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file_format = check_file_format(model.c_str(),&file_format_meta);
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if(forceversion!=0)
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{
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printf("\nWARNING: FILE FORMAT FORCED TO VER %d\nIf incorrect, loading may fail or crash.\n",forceversion);
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file_format = (FileFormat)forceversion;
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}
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//first digit is whether configured, second is platform, third is devices
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int cl_parseinfo = inputs.clblast_info;
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std::string usingclblast = "GGML_OPENCL_CONFIGURED="+std::to_string(cl_parseinfo>0?1:0);
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putenv((char*)usingclblast.c_str());
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cl_parseinfo = cl_parseinfo%100; //keep last 2 digits
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int platform = cl_parseinfo/10;
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int devices = cl_parseinfo%10;
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platformenv = "GGML_OPENCL_PLATFORM="+std::to_string(platform);
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deviceenv = "GGML_OPENCL_DEVICE="+std::to_string(devices);
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putenv((char*)platformenv.c_str());
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putenv((char*)deviceenv.c_str());
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std::string vulkan_info_raw = inputs.vulkan_info;
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std::string vulkan_info_str = "";
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for (size_t i = 0; i < vulkan_info_raw.length(); ++i) {
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vulkan_info_str += vulkan_info_raw[i];
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if (i < vulkan_info_raw.length() - 1) {
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vulkan_info_str += ",";
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}
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}
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if(vulkan_info_str=="")
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{
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vulkan_info_str = "0";
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}
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vulkandeviceenv = "GGML_VK_VISIBLE_DEVICES="+vulkan_info_str;
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putenv((char*)vulkandeviceenv.c_str());
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executable_path = inputs.executable_path;
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if(file_format==FileFormat::GPTJ_1 || file_format==FileFormat::GPTJ_2 || file_format==FileFormat::GPTJ_3 || file_format==FileFormat::GPTJ_4 || file_format==FileFormat::GPTJ_5)
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{
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printf("\n---\nIdentified as GPT-J model: (ver %d)\nAttempting to Load...\n---\n", file_format);
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ModelLoadResult lr = gpttype_load_model(inputs, file_format, file_format_meta);
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if (lr == ModelLoadResult::RETRY_LOAD)
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{
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if(file_format==FileFormat::GPTJ_1)
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{
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//if we tried 1 first, then try 3 and lastly 2
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//otherwise if we tried 3 first, then try 2
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file_format = FileFormat::GPTJ_4;
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printf("\n---\nRetrying as GPT-J model: (ver %d)\nAttempting to Load...\n---\n", file_format);
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lr = gpttype_load_model(inputs, file_format, file_format_meta);
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}
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if (lr == ModelLoadResult::RETRY_LOAD)
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{
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file_format = FileFormat::GPTJ_3;
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printf("\n---\nRetrying as GPT-J model: (ver %d)\nAttempting to Load...\n---\n", file_format);
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lr = gpttype_load_model(inputs, file_format, file_format_meta);
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}
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//lastly try format 2
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if (lr == ModelLoadResult::RETRY_LOAD)
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{
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file_format = FileFormat::GPTJ_2;
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printf("\n---\nRetrying as GPT-J model: (ver %d)\nAttempting to Load...\n---\n", file_format);
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lr = gpttype_load_model(inputs, file_format, file_format_meta);
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}
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}
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if (lr == ModelLoadResult::FAIL || lr == ModelLoadResult::RETRY_LOAD)
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{
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return false;
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}
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else
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{
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return true;
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}
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}
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else if(file_format==FileFormat::GPT2_1||file_format==FileFormat::GPT2_2||file_format==FileFormat::GPT2_3||file_format==FileFormat::GPT2_4)
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{
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printf("\n---\nIdentified as GPT-2 model: (ver %d)\nAttempting to Load...\n---\n", file_format);
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ModelLoadResult lr = gpttype_load_model(inputs, file_format, file_format_meta);
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if (lr == ModelLoadResult::RETRY_LOAD)
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{
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file_format = FileFormat::GPT2_3;
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printf("\n---\nRetrying as GPT-2 model: (ver %d)\nAttempting to Load...\n---\n", file_format);
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lr = gpttype_load_model(inputs, file_format, file_format_meta);
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}
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if (lr == ModelLoadResult::RETRY_LOAD)
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{
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file_format = FileFormat::GPT2_2;
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printf("\n---\nRetrying as GPT-2 model: (ver %d)\nAttempting to Load...\n---\n", file_format);
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lr = gpttype_load_model(inputs, file_format, file_format_meta);
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}
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if (lr == ModelLoadResult::FAIL || lr == ModelLoadResult::RETRY_LOAD)
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{
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return false;
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}
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else
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{
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return true;
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}
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}
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else if(file_format==FileFormat::NEOX_1 || file_format==FileFormat::NEOX_2 || file_format==FileFormat::NEOX_3 || file_format==FileFormat::NEOX_4 || file_format==FileFormat::NEOX_5 || file_format==FileFormat::NEOX_6 || file_format==FileFormat::NEOX_7)
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{
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printf("\n---\nIdentified as GPT-NEO-X model: (ver %d)\nAttempting to Load...\n---\n", file_format);
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ModelLoadResult lr = gpttype_load_model(inputs, file_format, file_format_meta);
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if (lr == ModelLoadResult::RETRY_LOAD)
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{
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if(file_format==FileFormat::NEOX_2)
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{
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file_format = FileFormat::NEOX_3;
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printf("\n---\nRetrying as GPT-NEO-X model: (ver %d)\nAttempting to Load...\n---\n", file_format);
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lr = gpttype_load_model(inputs, file_format, file_format_meta);
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}
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else
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{
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file_format = FileFormat::NEOX_5;
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printf("\n---\nRetrying as GPT-NEO-X model: (ver %d)\nAttempting to Load...\n---\n", file_format);
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lr = gpttype_load_model(inputs, file_format, file_format_meta);
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}
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}
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if (lr == ModelLoadResult::RETRY_LOAD)
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{
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file_format = FileFormat::NEOX_1;
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printf("\n---\nRetrying as GPT-NEO-X model: (ver %d)\nAttempting to Load...\n---\n", file_format);
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lr = gpttype_load_model(inputs, file_format, file_format_meta);
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}
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if (lr == ModelLoadResult::FAIL || lr == ModelLoadResult::RETRY_LOAD)
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{
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return false;
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}
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else
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{
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return true;
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}
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}
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else
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{
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if(file_format==FileFormat::MPT_1)
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{
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printf("\n---\nIdentified as MPT model: (ver %d)\nAttempting to Load...\n---\n", file_format);
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}
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else if(file_format==FileFormat::RWKV_1 || file_format==FileFormat::RWKV_2)
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{
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printf("\n---\nIdentified as RWKV model: (ver %d)\nAttempting to Load...\n---\n", file_format);
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}
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else if(file_format==FileFormat::GGUF_GENERIC)
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{
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printf("\n---\nIdentified as GGUF model: (ver %d)\nAttempting to Load...\n---\n", file_format);
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}
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else
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{
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printf("\n---\nUnidentified Model Encountered: (ver %d)\n---\n", file_format);
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}
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ModelLoadResult lr = gpttype_load_model(inputs, file_format, file_format_meta);
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if (lr == ModelLoadResult::FAIL || lr == ModelLoadResult::RETRY_LOAD)
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{
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return false;
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}
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else
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{
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return true;
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}
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}
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}
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generation_outputs generate(const generation_inputs inputs)
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{
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return gpttype_generate(inputs);
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}
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bool sd_load_model(const sd_load_model_inputs inputs)
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{
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return sdtype_load_model(inputs);
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}
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sd_generation_outputs sd_generate(const sd_generation_inputs inputs)
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{
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return sdtype_generate(inputs);
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}
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const char * new_token(int idx) {
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if (generated_tokens.size() <= idx || idx < 0) return nullptr;
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return generated_tokens[idx].c_str();
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}
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int get_stream_count() {
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return generated_tokens.size();
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}
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bool has_finished() {
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return generation_finished;
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}
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float get_last_eval_time() {
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return last_eval_time;
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}
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float get_last_process_time() {
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return last_process_time;
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}
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int get_last_token_count() {
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return last_token_count;
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}
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int get_last_seed()
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{
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return last_seed;
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}
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int get_total_gens() {
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return total_gens;
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}
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int get_last_stop_reason() {
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return (int)last_stop_reason;
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}
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const char* get_pending_output() {
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return gpttype_get_pending_output().c_str();
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}
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bool abort_generate() {
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return gpttype_generate_abort();
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}
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static std::vector<int> toks; //just share a static object for token counting
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token_count_outputs token_count(const char * input)
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{
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std::string inputstr = input;
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token_count_outputs output;
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toks = gpttype_get_token_arr(inputstr);
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output.count = toks.size();
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output.ids = toks.data(); //this may be slightly unsafe
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return output;
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}
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}
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