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gemma.cpp/gemma/run.cc

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// Copyright 2024 Google LLC
// SPDX-License-Identifier: Apache-2.0
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// https://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// Command line text interface to gemma.
#include <ctime>
#include <iostream>
#include <random>
#include <string>
#include <string_view>
#include <thread> // NOLINT
#include <vector>
// Placeholder for internal header, do not modify.
#include "compression/compress.h"
#include "gemma/common.h"
#include "gemma/configs.h"
#include "gemma/gemma.h" // Gemma
#include "util/app.h"
#include "util/args.h" // HasHelp
#include "hwy/base.h"
#include "hwy/contrib/thread_pool/thread_pool.h"
#include "hwy/highway.h"
#include "hwy/per_target.h"
#include "hwy/profiler.h"
#include "hwy/timer.h"
#if (!defined(HWY_VERSION_LT) || HWY_VERSION_LT(1, 2)) && !HWY_IDE
#error "Please update to version 1.2 of github.com/google/highway."
#endif
#if HWY_CXX_LANG < 201703L
#error "Gemma.cpp requires C++17, please pass -std=c++17."
#endif
static constexpr bool kVerboseLogTokens = false;
namespace gcpp {
static constexpr std::string_view kAsciiArtBanner = R""(
__ _ ___ _ __ ___ _ __ ___ __ _ ___ _ __ _ __
/ _` |/ _ \ '_ ` _ \| '_ ` _ \ / _` | / __| '_ \| '_ \
| (_| | __/ | | | | | | | | | | (_| || (__| |_) | |_) |
\__, |\___|_| |_| |_|_| |_| |_|\__,_(_)___| .__/| .__/
__/ | | | | |
|___/ |_| |_|
)"";
void ShowConfig(LoaderArgs& loader, InferenceArgs& inference, AppArgs& app) {
loader.Print(app.verbosity);
inference.Print(app.verbosity);
app.Print(app.verbosity);
if (app.verbosity >= 2) {
time_t now = time(nullptr);
char* dt = ctime(&now); // NOLINT
std::cout << "Date & Time : " << dt
<< "Prefill Token Batch Size : " << gcpp::kPrefillBatchSize
<< "\n"
<< "Hardware concurrency : "
<< std::thread::hardware_concurrency() << "\n"
<< "Instruction set : "
<< hwy::TargetName(hwy::DispatchedTarget()) << " ("
<< hwy::VectorBytes() * 8 << " bits)" << "\n";
char cpu100[100];
if (hwy::platform::GetCpuString(cpu100)) {
std::cout << "CPU : " << cpu100 << "\n";
}
std::cout << "Compiled config : " << CompiledConfig() << "\n"
<< "Weight Type : "
<< gcpp::StringFromType(loader.WeightType()) << "\n"
<< "EmbedderInput Type : "
<< gcpp::TypeName(gcpp::EmbedderInputT()) << "\n";
}
}
void ShowHelp(gcpp::LoaderArgs& loader, gcpp::InferenceArgs& inference,
gcpp::AppArgs& app) {
std::cerr
<< kAsciiArtBanner
<< "\n\ngemma.cpp : a lightweight, standalone C++ inference engine\n"
"==========================================================\n\n"
"To run gemma.cpp, you need to "
"specify 3 required model loading arguments:\n"
" --tokenizer\n"
" --weights\n"
" --model.\n";
std::cerr << "\n*Example Usage*\n\n./gemma --tokenizer tokenizer.spm "
"--weights 2b-it-sfp.sbs --model 2b-it\n";
std::cerr << "\n*Model Loading Arguments*\n\n";
loader.Help();
std::cerr << "\n*Inference Arguments*\n\n";
inference.Help();
std::cerr << "\n*Application Arguments*\n\n";
app.Help();
std::cerr << "\n";
}
// The main Read-Eval-Print Loop.
void ReplGemma(gcpp::Gemma& model, ModelTraining training,
gcpp::KVCache& kv_cache, hwy::ThreadPool& pool,
const InferenceArgs& args, int verbosity,
const gcpp::AcceptFunc& accept_token, std::string& eot_line) {
PROFILER_ZONE("Gen.misc");
size_t abs_pos = 0; // absolute token index over all turns
int current_pos = 0; // token index within the current turn
int prompt_size{};
std::mt19937 gen;
if (args.deterministic) {
gen.seed(42);
} else {
std::random_device rd;
gen.seed(rd());
}
// callback function invoked for each generated token.
auto stream_token = [&abs_pos, &current_pos, &args, &gen, &prompt_size,
&model, verbosity](int token, float) {
++abs_pos;
++current_pos;
// <= since position is incremented before
if (current_pos <= prompt_size) {
std::cerr << "." << std::flush;
} else if (token == gcpp::EOS_ID) {
if (!args.multiturn) {
abs_pos = 0;
if (args.deterministic) {
gen.seed(42);
}
}
if (verbosity >= 2) {
std::cout << "\n[ End ]\n";
}
} else {
std::string token_text;
HWY_ASSERT(
model.Tokenizer().Decode(std::vector<int>{token}, &token_text));
// +1 since position is incremented above
if (current_pos == prompt_size + 1) {
// first token of response
token_text.erase(0, token_text.find_first_not_of(" \t\n"));
if (verbosity >= 1) {
std::cout << "\n\n";
}
}
std::cout << token_text << std::flush;
}
return true;
};
while (abs_pos < args.max_tokens) {
std::string prompt_string;
std::vector<int> prompt;
current_pos = 0;
{
PROFILER_ZONE("Gen.input");
if (verbosity >= 1) {
std::cout << "> " << std::flush;
}
if (eot_line.empty()) {
std::getline(std::cin, prompt_string);
} else {
std::string line;
while (std::getline(std::cin, line)) {
if (line == eot_line) {
break;
}
prompt_string += line + "\n";
}
}
}
if (std::cin.fail() || prompt_string == "%q" || prompt_string == "%Q") {
return;
}
if (prompt_string == "%c" || prompt_string == "%C") {
abs_pos = 0;
continue;
}
if (training == ModelTraining::GEMMA_IT) {
// For instruction-tuned models: add control tokens.
prompt_string = "<start_of_turn>user\n" + prompt_string +
"<end_of_turn>\n<start_of_turn>model\n";
if (abs_pos != 0) {
// Prepend "<end_of_turn>" token if this is a multi-turn dialogue
// continuation.
prompt_string = "<end_of_turn>\n" + prompt_string;
}
}
HWY_ASSERT(model.Tokenizer().Encode(prompt_string, &prompt));
// For both pre-trained and instruction-tuned models: prepend "<bos>" token
// if needed.
if (abs_pos == 0) {
prompt.insert(prompt.begin(), gcpp::BOS_ID);
}
prompt_size = prompt.size();
std::cerr << "\n"
<< "[ Reading prompt ] " << std::flush;
if constexpr (kVerboseLogTokens) {
for (int i = 0; i < prompt_size; ++i) {
fprintf(stderr, "DDD TOKEN %3d: %6d\n", i, prompt[i]);
}
}
TimingInfo timing_info;
gcpp::RuntimeConfig runtime_config = {
.max_tokens = args.max_tokens,
.max_generated_tokens = args.max_generated_tokens,
.temperature = args.temperature,
.verbosity = verbosity,
.gen = &gen,
.stream_token = stream_token,
.accept_token = accept_token,
};
model.Generate(runtime_config, prompt, abs_pos, kv_cache, timing_info);
if (verbosity >= 2) {
std::cout << current_pos << " tokens (" << abs_pos << " total tokens)"
<< "\n"
<< timing_info.prefill_tok_sec << " prefill tokens / sec"
<< "\n"
<< timing_info.gen_tok_sec << " tokens / sec" << "\n"
<< static_cast<int>(timing_info.time_to_first_token * 1000)
<< " milliseconds time to first token" << "\n";
}
std::cout << "\n\n";
}
std::cout
<< "max_tokens (" << args.max_tokens
<< ") exceeded. Use a larger value if desired using the --max_tokens "
<< "command line flag.\n";
}
void Run(LoaderArgs& loader, InferenceArgs& inference, AppArgs& app) {
PROFILER_ZONE("Run.misc");
hwy::ThreadPool pool(app.num_threads);
// For many-core, pinning workers to cores helps.
if (app.num_threads > 10) {
PinWorkersToCores(pool);
}
gcpp::Gemma model = gcpp::CreateGemma(loader, pool);
KVCache kv_cache = KVCache::Create(loader.ModelType());
if (app.verbosity >= 1) {
const std::string instructions =
"*Usage*\n"
" Enter an instruction and press enter (%C resets conversation, "
"%Q quits).\n" +
(inference.multiturn == 0
? std::string(" Since multiturn is set to 0, conversation will "
"automatically reset every turn.\n\n")
: "\n") +
"*Examples*\n"
" - Write an email to grandma thanking her for the cookies.\n"
" - What are some historical attractions to visit around "
"Massachusetts?\n"
" - Compute the nth fibonacci number in javascript.\n"
" - Write a standup comedy bit about GPU programming.\n";
std::cout << "\033[2J\033[1;1H" // clear screen
<< kAsciiArtBanner << "\n\n";
ShowConfig(loader, inference, app);
std::cout << "\n" << instructions << "\n";
}
ReplGemma(model, loader.ModelTrainingType(), kv_cache, pool, inference,
app.verbosity, AcceptFunc(), app.eot_line);
}
} // namespace gcpp
int main(int argc, char** argv) {
{
PROFILER_ZONE("Startup.misc");
// Placeholder for internal init, do not modify.
gcpp::LoaderArgs loader(argc, argv);
gcpp::InferenceArgs inference(argc, argv);
gcpp::AppArgs app(argc, argv);
if (gcpp::HasHelp(argc, argv)) {
ShowHelp(loader, inference, app);
return 0;
}
if (const char* error = loader.Validate()) {
ShowHelp(loader, inference, app);
HWY_ABORT("\nInvalid args: %s", error);
}
if (const char* error = inference.Validate()) {
ShowHelp(loader, inference, app);
HWY_ABORT("\nInvalid args: %s", error);
}
gcpp::Run(loader, inference, app);
}
PROFILER_PRINT_RESULTS(); // Must call outside the zone above.
return 0;
}
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