mirror of https://github.com/google/gemma.cpp.git
138 lines
3.8 KiB
C++
138 lines
3.8 KiB
C++
// Copyright 2024 Google LLC
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// SPDX-License-Identifier: Apache-2.0
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// https://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include <fstream>
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#include <iostream>
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#include <random>
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#include <sstream>
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#include <string>
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#include <vector>
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#include "third_party/benchmark/include/benchmark/benchmark.h"
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#include "gemma/gemma.h"
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#include "util/app.h"
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#include "hwy/base.h"
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#include "hwy/contrib/thread_pool/thread_pool.h"
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gcpp::LoaderArgs* loader = nullptr;
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gcpp::InferenceArgs* inference = nullptr;
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gcpp::Gemma* model = nullptr;
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hwy::ThreadPool* pool = nullptr;
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hwy::ThreadPool* inner_pool = nullptr;
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void run_gemma_prompt(const std::string& prompt_string,
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benchmark::State& state) {
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std::mt19937 gen;
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std::vector<int> prompt;
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if (prompt_string.empty()) return;
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HWY_ASSERT(model->Tokenizer().Encode(prompt_string, &prompt).ok());
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int token_counter = 0;
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auto stream_token = [&token_counter](int, float) {
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token_counter++;
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return true;
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};
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for (auto s : state) {
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GenerateGemma(
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*model, *inference, prompt, /*start_token=*/0, *pool, *inner_pool,
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stream_token,
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/*accept=*/[](int) { return true; }, gen, /*verbosity=*/0);
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}
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state.SetItemsProcessed(token_counter);
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}
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static void BM_short_prompt(benchmark::State& state) {
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run_gemma_prompt("What is the capital of Spain?<ctrl23> ", state);
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}
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static void BM_factuality_prompt(benchmark::State& state) {
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run_gemma_prompt("How does an inkjet printer work?<ctrl23> ", state);
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}
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static void BM_creative_prompt(benchmark::State& state) {
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run_gemma_prompt(
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"Tell me a story about a magical bunny and their TRS-80.<ctrl23> ",
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state);
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}
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static void BM_coding_prompt(benchmark::State& state) {
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run_gemma_prompt(
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"Write a python program to generate a fibonacci sequence.<ctrl23> ",
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state);
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}
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static void BM_long_coding_prompt(benchmark::State& state) {
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std::ifstream t("benchmarks.cc", std::ios_base::in);
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std::stringstream buffer;
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buffer << t.rdbuf();
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std::string prompt_string = buffer.str();
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t.close();
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run_gemma_prompt("Make improvements to the following code:\n " +
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prompt_string + "<ctrl23> ",
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state);
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}
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int main(int argc, char** argv) {
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loader = new gcpp::LoaderArgs(argc, argv);
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inference = new gcpp::InferenceArgs(argc, argv);
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gcpp::AppArgs app(argc, argv);
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pool = new ::hwy::ThreadPool(app.num_threads);
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inner_pool = new ::hwy::ThreadPool(0);
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model = new gcpp::Gemma(*loader, *pool);
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inference->max_tokens = 128;
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BENCHMARK(BM_short_prompt)
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->Iterations(3)
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->Unit(benchmark::kMillisecond)
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->UseRealTime();
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inference->max_tokens = 256;
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BENCHMARK(BM_factuality_prompt)
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->Iterations(3)
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->Unit(benchmark::kMillisecond)
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->UseRealTime();
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BENCHMARK(BM_creative_prompt)
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->Iterations(3)
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->Unit(benchmark::kMillisecond)
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->UseRealTime();
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BENCHMARK(BM_coding_prompt)
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->Iterations(3)
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->Unit(benchmark::kMillisecond)
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->UseRealTime();
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inference->max_tokens = 1024;
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BENCHMARK(BM_long_coding_prompt)
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->Iterations(3)
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->Unit(benchmark::kMillisecond)
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->UseRealTime();
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::benchmark ::RunSpecifiedBenchmarks();
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::benchmark ::Shutdown();
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delete loader;
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delete inference;
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delete model;
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delete pool;
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return 0;
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}
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