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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 <thread> // NOLINT
#include <vector>
// copybara:import_next_line:gemma_cpp
#include "compression/compress.h"
// copybara:end
// copybara:import_next_line:gemma_cpp
#include "gemma.h" // Gemma
// copybara:end
// copybara:import_next_line:gemma_cpp
#include "util/app.h"
// copybara:end
// copybara:import_next_line:gemma_cpp
#include "util/args.h" // HasHelp
// copybara:end
#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"
namespace gcpp {
static constexpr std::string_view kAsciiArtBanner =
" __ _ ___ _ __ ___ _ __ ___ __ _ ___ _ __ _ __\n"
" / _` |/ _ \\ '_ ` _ \\| '_ ` _ \\ / _` | / __| '_ \\| '_ \\\n"
"| (_| | __/ | | | | | | | | | | (_| || (__| |_) | |_) |\n"
" \\__, |\\___|_| |_| |_|_| |_| |_|\\__,_(_)___| .__/| .__/\n"
" __/ | | | | |\n"
" |___/ |_| |_|";
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() << std::endl
<< "Instruction set : "
<< hwy::TargetName(hwy::DispatchedTarget()) << " ("
<< hwy::VectorBytes() * 8 << " bits)" << "\n"
<< "Compiled config : " << CompiledConfig() << "\n"
<< "Weight Type : "
<< gcpp::TypeName(gcpp::WeightT()) << "\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 "
"--compressed_weights\n"
" --model.\n";
std::cerr << "\n*Example Usage*\n\n./gemma --tokenizer tokenizer.spm "
"--compressed_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";
}
void ReplGemma(gcpp::Gemma& model, gcpp::KVCache& kv_cache,
hwy::ThreadPool& pool, hwy::ThreadPool& inner_pool,
const InferenceArgs& args, int verbosity,
const gcpp::AcceptFunc& accept_token, std::string& eot_line) {
PROFILER_ZONE("Gen.misc");
int 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,
tokenizer = model.Tokenizer(),
verbosity](int token, float) {
++abs_pos;
++current_pos;
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(tokenizer->Decode(std::vector<int>{token}, &token_text).ok());
// +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 << std::endl << std::endl;
}
}
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.size() == 0) {
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 (model.model_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).ok());
// For both pre-trained and instruction-tuned models: prepend "<bos>" token
// if needed.
if (abs_pos == 0) {
prompt.insert(prompt.begin(), 2);
}
prompt_size = prompt.size();
std::cerr << std::endl << "[ Reading prompt ] " << std::flush;
const double time_start = hwy::platform::Now();
GenerateGemma(model, args.max_tokens, args.max_generated_tokens,
args.temperature, prompt, abs_pos, kv_cache, pool, inner_pool,
stream_token, accept_token, gen, verbosity);
const double time_end = hwy::platform::Now();
const double tok_sec = current_pos / (time_end - time_start);
if (verbosity >= 2) {
std::cout << current_pos << " tokens (" << abs_pos << " total tokens)"
<< std::endl
<< tok_sec << " tokens / sec" << std::endl;
}
std::cout << std::endl << std::endl;
}
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 inner_pool(0);
hwy::ThreadPool pool(app.num_threads);
// For many-core, pinning threads to cores helps.
if (app.num_threads > 10) {
PinThreadToCore(app.num_threads - 1); // Main thread
pool.Run(0, pool.NumThreads(),
[](uint64_t /*task*/, size_t thread) { PinThreadToCore(thread); });
}
gcpp::Gemma model(loader.tokenizer, loader.compressed_weights, loader.weights,
loader.ModelType(), loader.ModelTraining(), pool);
auto kv_cache = CreateKVCache(loader.ModelType());
if (const char* error = inference.Validate()) {
ShowHelp(loader, inference, app);
HWY_ABORT("\nInvalid args: %s", error);
}
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, kv_cache, pool, inner_pool, inference, app.verbosity,
/*accept_token=*/[](int) { return true; }, app.eot_line);
}
} // namespace gcpp
int main(int argc, char** argv) {
{
PROFILER_ZONE("Startup.misc");
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);
}
gcpp::Run(loader, inference, app);
}
PROFILER_PRINT_RESULTS(); // Must call outside the zone above.
return 0;
}
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