From 7a98e96a908b8a3a0339915e868b6a780b3dd2fd Mon Sep 17 00:00:00 2001 From: mamu Date: Thu, 16 May 2024 19:41:37 +0900 Subject: [PATCH] Add Evolutionary Model Merge sampler --- package/samplers/evo_merge/LICENSE | 21 +++ package/samplers/evo_merge/README.md | 46 +++++++ package/samplers/evo_merge/__init__.py | 8 ++ package/samplers/evo_merge/config.yml | 16 +++ package/samplers/evo_merge/example.py | 87 +++++++++++++ package/samplers/evo_merge/images/history.png | Bin 0 -> 96945 bytes .../evo_merge/images/parallel_coordinate.png | Bin 0 -> 2362447 bytes package/samplers/evo_merge/sampler.py | 121 ++++++++++++++++++ package/samplers/evo_merge/simple.jsonl | 100 +++++++++++++++ package/samplers/evo_merge/trial.py | 12 ++ pyproject.toml | 2 +- 11 files changed, 412 insertions(+), 1 deletion(-) create mode 100644 package/samplers/evo_merge/LICENSE create mode 100644 package/samplers/evo_merge/README.md create mode 100644 package/samplers/evo_merge/__init__.py create mode 100644 package/samplers/evo_merge/config.yml create mode 100644 package/samplers/evo_merge/example.py create mode 100644 package/samplers/evo_merge/images/history.png create mode 100644 package/samplers/evo_merge/images/parallel_coordinate.png create mode 100644 package/samplers/evo_merge/sampler.py create mode 100644 package/samplers/evo_merge/simple.jsonl create mode 100644 package/samplers/evo_merge/trial.py diff --git a/package/samplers/evo_merge/LICENSE b/package/samplers/evo_merge/LICENSE new file mode 100644 index 00000000..4e2b34c1 --- /dev/null +++ b/package/samplers/evo_merge/LICENSE @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) 2024 Preferred Networks, Inc. + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. diff --git a/package/samplers/evo_merge/README.md b/package/samplers/evo_merge/README.md new file mode 100644 index 00000000..47cfaa7d --- /dev/null +++ b/package/samplers/evo_merge/README.md @@ -0,0 +1,46 @@ +--- +author: 'Optuna team' +title: 'Evolutionary LLM Merge Sampler' +description: 'A sampler for evolutionary LLM merge.' +tags: ['sampler', 'LLM'] +optuna_versions: [3.6.1] +license: 'MIT License' +--- + +## Class or Function Names +- EvoMergeSampler +- EvoMergeTrial + +## Installation +```bash +pip install git+https://github.com/arcee-ai/mergekit.git +pip install sentencepiece accelerate protobuf bitsandbytes langchain langchain-community datasets +pip install pandas cmaes +export HF_TOKEN=xxx +``` + +## Example +```python +sampler = EvoMergeSampler(base_config="path/to/config/yml/file") +study = optuna.create_study(sampler=sampler) + +for _ in range(100): + trial = study.ask() + evo_merge_trial = EvoMergeTrial(study, trial._trial_id) + model = evo_merge_trial.suggest_model() + + acc = try_model(model) + + study.tell(trial, acc) + +print(study.trials_dataframe(attrs=("number", "value"))) +``` +See `example.py` for a full example. You need GPU with 16G VLAM to run this example. +The following figures are obtained from the analysis of the optimization. +![History Plot](images/history.png "History Plot") +![Parallel Coordinate Plot](images/parallel_coordinate.png "Parallel Coordinate Plot") + +## Others + +### Reference +Akiba, T., Shing, M., Tang, Y., Sun, Q., & Ha, D. (2024). Evolutionary Optimization of Model Merging Recipes. arXiv preprint arXiv:2403.13187. diff --git a/package/samplers/evo_merge/__init__.py b/package/samplers/evo_merge/__init__.py new file mode 100644 index 00000000..2cb334c3 --- /dev/null +++ b/package/samplers/evo_merge/__init__.py @@ -0,0 +1,8 @@ +from .sampler import EvoMergeSampler +from .trial import EvoMergeTrial + + +__all__ = [ + "EvoMergeSampler", + "EvoMergeTrial", +] diff --git a/package/samplers/evo_merge/config.yml b/package/samplers/evo_merge/config.yml new file mode 100644 index 00000000..448a61cc --- /dev/null +++ b/package/samplers/evo_merge/config.yml @@ -0,0 +1,16 @@ +models: + - model: augmxnt/shisa-gamma-7b-v1 + # No parameters necessary for base model + - model: GAIR/Abel-7B-002 + parameters: + density: 0.5 + weight: 0.5 + - model: WizardLM/WizardMath-7B-V1.1 + parameters: + density: 0.5 + weight: 0.5 +merge_method: dare_ties +base_model: augmxnt/shisa-gamma-7b-v1 +parameters: + int8_mask: true +dtype: float16 diff --git a/package/samplers/evo_merge/example.py b/package/samplers/evo_merge/example.py new file mode 100644 index 00000000..e98163df --- /dev/null +++ b/package/samplers/evo_merge/example.py @@ -0,0 +1,87 @@ +from __future__ import annotations + +import argparse +import datetime +import json +import os + +from datasets import load_dataset +from langchain.chains import LLMChain +from langchain.llms.base import BaseLLM +from langchain.prompts import PromptTemplate +import optuna + +from package.samplers.evo_merge.sampler import EvoMergeSampler +from package.samplers.evo_merge.trial import EvoMergeTrial + + +# EvoMergeSampler = optunahub.load_module("samplers/evo_merge").EvoMergeSampler +# EvoMergeTrial = optunahub.load_module("samplers/evo_merge").EvoMergeTrial + +TEMPLATE = "質問に答えなさい。質問: {question} 回答: " + + +if not os.path.exists("./simple.jsonl"): + dataset = load_dataset("SakanaAI/gsm8k-ja-test_250-1319", split="test") + with open("./simple.jsonl", "w") as fout: + for q, a in zip(dataset["question"][:100], dataset["answer_number"][:100]): + fout.write(json.dumps({"question": q, "answer_number": a}) + "\n") + +dataset = [] +with open("./simple.jsonl") as fin: + for line in fin: + dataset.append(json.loads(line.strip())) + + +def eval_jaqket(llm_chain: LLMChain) -> int: + correct = 0 + for problem in dataset: + out = llm_chain.run(question=problem["question"]) + if len(out.strip()) != 0: + out = out.strip().split()[0].strip() + if problem["answer_number"] in out: + correct += 1 + + return correct + + +def try_model(llm: BaseLLM) -> float: + ptemplate = PromptTemplate.from_template(TEMPLATE) + llm_chain = LLMChain(prompt=ptemplate, llm=llm) + + correct = eval_jaqket(llm_chain) + + return correct / len(dataset) + + +def main() -> None: + parser = argparse.ArgumentParser() + parser.add_argument("--study-name", help="Optuna study name") + args = parser.parse_args() + + if args.study_name: + study_name = args.study_name + else: + study_name = f"optuna-merge-ja-{datetime.datetime.now().isoformat(timespec='minutes')}" + + sampler = EvoMergeSampler(base_config="./config.yml") + study = optuna.create_study( + direction="maximize", + study_name=study_name, + sampler=sampler, + ) + + for _ in range(100): + trial = study.ask() + evo_merge_trial = EvoMergeTrial(study, trial._trial_id) + model = evo_merge_trial.suggest_model() + + acc = try_model(model) + + study.tell(trial, acc) + + print(study.trials_dataframe(attrs=("number", "value"))) + + +if __name__ == "__main__": + main() diff --git a/package/samplers/evo_merge/images/history.png b/package/samplers/evo_merge/images/history.png new file mode 100644 index 0000000000000000000000000000000000000000..796e5252425744c8b9d7f5f512ec8181fd324394 GIT binary patch literal 96945 zcmeFZbySt#w=Pb1hjdAUbT<;xAOaE+8wo*>?hffL-J}wNgdm7?Z5kv5q@)|9Lptu- zpE&pXz2|f89q0V_8{_vEV{G=j-nr(Q@yut=wWA(uD&b;LVj&b-he?vOWDs^k%~Mr;`)q-$`;ujukiw*C 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zFCSDW`mk$P4Cv`+XJ-R9ugr-Lp!e>71V-B%K=VBE`*oRY+kf5Ew0Jn~oLou$g72C5 z%@&sKO{6G80j~30LWdnUsk&=E+PB}f+)_>f+8|Code`~Toa6&9)~ z>2U;)`A|R-+yNDaN|%dHiSD(oOPDVnX79_;6R+u}^`XwEBKd0_@&$*7oMFRYDPEB( zY?XGv*`$FMNGO0^*Y;C1urHGlsXTd zVMQfNO{koR5%IgYMNyGUOJx==U$E?h^)P#_rv2xQBx-}^{y14knc~&l&4$T>5`_U| z*mA{@<#b{(X+iB5L3Z&|IaH*QqqBP>KT8yxv@)$fxSKL2=-J6a87HGQZAaYY;*bqG zZH- None: + self.seed = seed + self._cmaes = CmaEsSampler() + + with open(base_config, "r", encoding="utf-8") as fp: + self._merge_config = MergeConfiguration.model_validate(yaml.safe_load(fp)) + + def infer_relative_search_space( + self, study: Study, trial: FrozenTrial + ) -> dict[str, BaseDistribution]: + return {} + + def sample_relative( + self, study: Study, trial: FrozenTrial, search_space: dict[str, BaseDistribution] + ) -> dict[str, Any]: + return {} + + def sample_independent( + self, + study: Study, + trial: FrozenTrial, + param_name: str, + param_distribution: BaseDistribution, + ) -> Any: + return param_distribution._asdict() + + def reseed_rng(self, seed: int) -> None: + self.seed = seed + + def _sample( + self, + study: Study, + trial: FrozenTrial, + param_name: str, + param_distribution: BaseDistribution, + ) -> Any: + return param_distribution._asdict() + + def sample_model(self, study: Study, trial: EvoMergeTrial) -> BaseLLM: + merge_config = copy.deepcopy(self._merge_config) + for i, m in enumerate(merge_config.models): + if i == 0: + # No parameters necessary for base model. + continue + model_name = m.model + search_space = {f"{model_name}-{k}": FloatDistribution(0, 1) for k in m.parameters} + params = self._cmaes.sample_relative(study, trial, search_space) + for name in params: + param_value = params[name] + distribution = search_space[name] + param_value_in_internal_repr = distribution.to_internal_repr(param_value) + study._storage.set_trial_param( + trial._trial_id, name, param_value_in_internal_repr, distribution + ) + + if len(params) == 0: + continue + for k in m.parameters: + m.parameters[k] = params[f"{model_name}-{k}"] + + with tempfile.TemporaryDirectory() as output_path: + run_merge( + merge_config, + out_path=output_path, + options=MergeOptions( + lora_merge_cache="/tmp", + cuda=torch.cuda.is_available(), + copy_tokenizer=True, + lazy_unpickle=False, + low_cpu_memory=False, + ), + ) + llm = load_model(output_path) + + return llm + + +def load_model(model_id: str) -> BaseLLM: + bnbconf = BitsAndBytesConfig(load_in_4bit=True) + tokenizer = AutoTokenizer.from_pretrained(model_id) + model = AutoModelForCausalLM.frm_pretrained(model_id, quantization_config=bnbconf) + llm = HuggingFacePipeline( + pipeline=pipeline( + "text-generation", + model=model, + tokenizer=tokenizer, + max_new_tokens=16, + temperature=0.7, + do_sample=True, + return_full_text=False, + ) + ) + return llm diff --git a/package/samplers/evo_merge/simple.jsonl b/package/samplers/evo_merge/simple.jsonl new file mode 100644 index 00000000..bccfe938 --- /dev/null +++ b/package/samplers/evo_merge/simple.jsonl 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"\u30de\u30c7\u30a3\u30bd\u30f3\u306f\u305d\u308c\u305e\u308c50\u500b\u306e\u30d3\u30fc\u7389\u304c\u5165\u3063\u305f\u7bb1\u30925\u3064\u6301\u3063\u3066\u3044\u307e\u3059\u3002\u305d\u306e\u5f8c\u3001\u53cb\u9054\u304b\u3089\u30d3\u30fc\u7389\u309220\u500b\u3082\u3089\u3044\u307e\u3057\u305f\u3002\u5f7c\u5973\u306f\u4eca\u3001\u4f55\u500b\u306e\u30d3\u30fc\u7389\u3092\u6301\u3063\u3066\u3044\u307e\u3059\u304b\uff1f", "answer_number": 270} +{"question": "\u30af\u30ea\u30b9\u306e\u5ead\u306b\u306f6\u672c\u306e\u6728\u304c\u3042\u308a\u307e\u3059\u3002\u30d5\u30a7\u30eb\u30c7\u30a3\u30ca\u30f3\u30c9\u306f\u30af\u30ea\u30b9\u306e\u6728\u306e\u6570\u306e\u534a\u5206\u3092\u6301\u3063\u3066\u3044\u307e\u3059\u3002\u30cf\u30ea\u30fc\u306f\u30d5\u30a7\u30eb\u30c7\u30a3\u30ca\u30f3\u30c9\u306e\u6728\u306e\u6570\u306e2\u500d\u3088\u308a\u30825\u672c\u591a\u304f\u6301\u3063\u3066\u3044\u307e\u3059\u3002\u30cf\u30ea\u30fc\u306e\u5ead\u306b\u306f\u30d5\u30a7\u30eb\u30c7\u30a3\u30ca\u30f3\u30c9\u306e\u5ead\u3088\u308a\u4f55\u672c\u591a\u304f\u306e\u6728\u304c\u3042\u308a\u307e\u3059\u304b\uff1f", "answer_number": 8} +{"question": "\u30ab\u30eb\u30e1\u30f3\u306f100\u30c9\u30eb\u6301\u3063\u3066\u3044\u307e\u3059\u3002\u30b5\u30de\u30f3\u30b5\u306f\u30ab\u30eb\u30e1\u30f3\u3088\u308a\u308225\u30c9\u30eb\u591a\u304f\u6301\u3063\u3066\u304a\u308a\u3001\u30c7\u30a4\u30b8\u30fc\u306f\u30b5\u30de\u30f3\u30b5\u3088\u308a\u308250\u30c9\u30eb\u591a\u304f\u6301\u3063\u3066\u3044\u307e\u3059\u30023\u4eba\u306e\u5973\u306e\u5b50\u304c\u5408\u308f\u305b\u3066\u6301\u3063\u3066\u3044\u308b\u91d1\u984d\u306f\u3044\u304f\u3089\u3067\u3059\u304b\uff1f", "answer_number": 400} +{"question": "\u30af\u30eb\u30b9\u592b\u4eba\u306f40\u4e07\u30c9\u30eb\u3092\u8d85\u3048\u306a\u3044\u4e88\u7b97\u3067\u5bb6\u3092\u63a2\u3057\u3066\u3044\u307e\u3059\u3002\u5f7c\u5973\u304c\u898b\u3064\u3051\u305f\u7269\u4ef6\u306e\u8ca9\u58f2\u4fa1\u683c\u306f35\u4e07\u30c9\u30eb\u3067\u3059\u3002\u305d\u306e\u4e0a\u3067\u3001\u8cfc\u5165\u8005\u306f\u8ca9\u58f2\u4fa1\u683c\u306e5%\u306e\u4ef2\u4ecb\u624b\u6570\u6599\u3068\u3001\u8ca9\u58f2\u4fa1\u683c\u306e12%\u306e\u8b72\u6e21\u624b\u6570\u6599\u3092\u652f\u6255\u3046\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002\u5bb6\u306e\u7dcf\u4fa1\u683c\u306f\u30af\u30eb\u30b9\u592b\u4eba\u306e\u4e88\u7b97\u3092\u3044\u304f\u3089\u8d85\u3048\u3066\u3044\u307e\u3059\u304b\uff1f", "answer_number": 9500} +{"question": "\u7530\u3055\u3093\u306f\u81ea\u5b85\u309240\u4e07\u30c9\u30eb\u3067\u58f2\u308a\u307e\u3057\u305f\u3002\u5f7c\u306f\u58f2\u5374\u4fa1\u683c\u306e3%\u306b\u3042\u305f\u308b\u8b72\u6e21\u624b\u6570\u6599\u3068\u3001\u58f2\u5374\u4fa1\u683c\u306e5%\u306b\u3042\u305f\u308b\u4ef2\u4ecb\u624b\u6570\u6599\u3092\u652f\u6255\u3044\u307e\u3057\u305f\u3002\u307e\u305f\u3001\u5bb6\u306e\u6b8b\u308a\u306e\u30ed\u30fc\u30f3\u91d1\u984d\u3068\u3057\u306625\u4e07\u30c9\u30eb\u3082\u652f\u6255\u3044\u307e\u3057\u305f\u3002\u7530\u3055\u3093\u304c\u5bb6\u3092\u58f2\u3063\u3066\u5f97\u305f\u7d14\u53ce\u76ca\u306f\u3044\u304f\u3089\u3067\u3059\u304b\uff1f", "answer_number": 118000} +{"question": "\u6cb9\u3092300\u5ea6\u307e\u3067\u52a0\u71b1\u3059\u308b\u306e\u306b20\u5206\u304b\u304b\u308a\u307e\u3059\u3002\u305d\u306e\u5f8c\u3001\u6cb9\u3092\u76ee\u7684\u306e\u6e29\u5ea6\u3067\u3042\u308b400\u5ea6\u307e\u3067\u52a0\u71b1\u3059\u308b\u306e\u306b\u306f40%\u9577\u3044\u6642\u9593\u304c\u304b\u304b\u308a\u307e\u3059\u3002\u6cb9\u3092\u6e29\u3081\u305f\u5f8c\u3001\u305d\u306e\u6cb9\u3067\u9d8f\u8089\u3092\u8abf\u7406\u3059\u308b\u306e\u306b\u306f\u3001\u6cb9\u3092\u6e29\u3081\u308b\u306e\u306b\u304b\u304b\u3063\u305f\u6642\u9593\u3088\u308a\u30825\u5206\u77ed\u3044\u6642\u9593\u304c\u304b\u304b\u308a\u307e\u3059\u3002\u6cb9\u3092\u52a0\u71b1\u3057\u59cb\u3081\u3066\u304b\u3089\u9d8f\u8089\u304c\u8abf\u7406\u3055\u308c\u308b\u307e\u3067\u306b\u3069\u308c\u304f\u3089\u3044\u306e\u6642\u9593\u304c\u7d4c\u904e\u3057\u307e\u3059\u304b\uff1f", "answer_number": 91} +{"question": "\u4e0d\u52d5\u7523\u696d\u8005\u306f\u3001\u65b0\u805e\u5e83\u544a1\u3064\u306b\u3064\u304d5\u30c9\u30eb\u3001\u30c6\u30ec\u30d3\u5e83\u544a1\u3064\u306b\u3064\u304d75\u30c9\u30eb\u3092\u8cbb\u3084\u3057\u307e\u3057\u305f\u3002\u5f7c\u306f\u65b0\u805e\u5e83\u544a\u309250\u500b\u3001\u30c6\u30ec\u30d3\u5e83\u544a\u309215\u500b\u8cfc\u5165\u3057\u307e\u3057\u305f\u3002\u5168\u3066\u306e\u5e83\u544a\u3092\u8cfc\u5165\u3059\u308b\u306e\u306b\u3001\u4e0d\u52d5\u7523\u696d\u8005\u306f\u5408\u8a08\u3067\u3044\u304f\u3089\u8cbb\u3084\u3057\u305f\u3067\u3057\u3087\u3046\u304b\uff1f", "answer_number": 1375} +{"question": "\u30b8\u30e3\u30b0\u30e9\u30fc\u306f16\u500b\u306e\u30dc\u30fc\u30eb\u3092\u30b8\u30e3\u30b0\u30ea\u30f3\u30b0\u3067\u304d\u307e\u3059\u3002\u30dc\u30fc\u30eb\u306e\u534a\u5206\u306f\u30b4\u30eb\u30d5\u30dc\u30fc\u30eb\u3067\u3001\u305d\u306e\u30b4\u30eb\u30d5\u30dc\u30fc\u30eb\u306e\u534a\u5206\u306f\u9752\u8272\u3067\u3059\u3002\u9752\u8272\u306e\u30b4\u30eb\u30d5\u30dc\u30fc\u30eb\u306f\u3044\u304f\u3064\u3042\u308a\u307e\u3059\u304b\uff1f", "answer_number": 4} +{"question": "\u30e1\u30a2\u30ea\u30fc\u306fM&M's\u306e\u888b\u30923\u3064\u8cb7\u3044\u307e\u3057\u305f\u3002\u6700\u521d\u306e\u888b\u306b\u306f300\u500b\u306eM&M's\u304c\u5165\u3063\u3066\u3044\u307e\u3059\u30022\u756a\u76ee\u306e\u888b\u306b\u306f\u6700\u521d\u306e\u888b\u3088\u308a\u308212\u500b\u591a\u304f\u5165\u3063\u3066\u3044\u307e\u3059\u3002\u305d\u3057\u3066\u30013\u756a\u76ee\u306e\u888b\u306b\u306f\u7a74\u304c\u958b\u3044\u3066\u3044\u308b\u305f\u3081\u3001\u6700\u521d\u306e\u888b\u306e\u534a\u5206\u306e\u6570\u306eM&M's\u3057\u304b\u5165\u3063\u3066\u3044\u307e\u305b\u3093\u3002\u30e1\u30a2\u30ea\u30fc\u306f\u5408\u8a08\u3067\u4f55\u500b\u306eM&M's\u3092\u624b\u306b\u5165\u308c\u307e\u3057\u305f\u304b\uff1f", "answer_number": 762} +{"question": "\u30b8\u30e7\u30f3\u306b\u306f\u305d\u308c\u305e\u308c3\u3064\u306e\u5bdd\u5ba4\u304c\u3042\u308b2\u8ed2\u306e\u5bb6\u304c\u3042\u308a\u307e\u3059\u3002\u5404\u5bdd\u5ba4\u306b\u306f\u7a93\u304c2\u3064\u305a\u3064\u3042\u308a\u307e\u3059\u3002\u3055\u3089\u306b\u3001\u5404\u5bb6\u306b\u306f\u5bdd\u5ba4\u4ee5\u5916\u306b4\u3064\u306e\u7a93\u304c\u3042\u308a\u307e\u3059\u3002\u3053\u308c\u3089\u306e\u5bb6\u306b\u306f\u5408\u8a08\u3067\u4f55\u500b\u306e\u7a93\u304c\u3042\u308a\u307e\u3059\u304b\uff1f", "answer_number": 20} +{"question": "\u6bcd\u89aa\u304c\u8cb7\u3044\u7269\u306b\u884c\u304d\u307e\u3057\u305f\u3002\u30b3\u30b3\u30a2\u30924.20\u30c9\u30eb\u3001\u6d17\u6fef\u7528\u54c1\u30929.45\u30c9\u30eb\u3001\u30d1\u30b9\u30bf\u306e\u30d1\u30c3\u30b1\u30fc\u30b8\u30921.35\u30c9\u30eb\u3067\u8cfc\u5165\u3057\u307e\u3057\u305f\u3002\u5f7c\u5973\u306f20\u30c9\u30eb\u3092\u652f\u6255\u3044\u307e\u3059\u3002\u30ec\u30b8\u4fc2\u306f\u3044\u304f\u3089\u304a\u91e3\u308a\u3092\u8fd4\u3057\u307e\u3059\u304b\uff1f", "answer_number": 5} +{"question": "\u30bb\u30fc\u30bf\u30fc\u306e\u672c\u4f53\u3092\u5b8c\u6210\u3055\u305b\u308b\u306b\u306f900\u306e\u30b9\u30c6\u30c3\u30c1\u304c\u5fc5\u8981\u3067\u3001\u895f\u306f\u305d\u306e\u6570\u306e10\u5206\u306e1\u3001\u88c5\u98fe\u7528\u306e\u30ed\u30bc\u30c3\u30c8\u306f\u895f\u306e2\u500d\u306e\u30b9\u30c6\u30c3\u30c1\u304c\u5fc5\u8981\u3067\u3059\u3002\u5168\u4f53\u3067\u30bb\u30fc\u30bf\u30fc\u306f1800\u30b9\u30c6\u30c3\u30c1\u306e\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u3067\u3059\u3002\u5404\u8896\u306b\u306f\u4f55\u30b9\u30c6\u30c3\u30c1\u5fc5\u8981\u3067\u3059\u304b\uff1f", "answer_number": 315} +{"question": "\u30e9\u30a4\u30e9\u30f3\u592b\u4eba\u306f4\u6708\u306b\u8fb2\u5834\u3067\u5fd9\u3057\u304f\u3001\u5b63\u7bc0\u306e\u91ce\u83dc\u3092\u690d\u3048\u3066\u3044\u307e\u3059\u3002\u5f7c\u5973\u306f\u30c8\u30de\u30c8\u306e\u7a2e20\u888b\u3068\u30bb\u30ed\u30ea\u306e\u7a2e80\u888b\u3092\u8cfc\u5165\u3057\u307e\u3057\u305f\u3002\u30c8\u30de\u30c8\u306e\u7a2e1\u888b\u304c40\u30c9\u30eb\u3001\u30bb\u30ed\u30ea\u306e\u7a2e1\u888b\u304c30\u30c9\u30eb\u306e\u5834\u5408\u3001\u7a2e\u3092\u8cfc\u5165\u3059\u308b\u306e\u306b\u3069\u308c\u3060\u3051\u306e\u304a\u91d1\u304c\u304b\u304b\u308a\u307e\u3057\u305f\u304b\uff1f", "answer_number": 3200} +{"question": 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"\u30b7\u30e3\u30ce\u30f3\u306f\u3001\u30db\u30c3\u30c8\u30b3\u30fc\u30d2\u30fc\u3092\u6df9\u308c\u3066\u6c37\u3092\u52a0\u3048\u308b\u3053\u3068\u3067\u30a2\u30a4\u30b9\u30b3\u30fc\u30d2\u30fc\u3092\u4f5c\u308a\u307e\u3059\u3002\u6c371\u500b\u3092\u52a0\u3048\u308b\u3054\u3068\u306b\u30b3\u30fc\u30d2\u30fc\u306f13\u5ea6\u51b7\u3048\u300112\u30df\u30ea\u30ea\u30c3\u30c8\u30eb\u8584\u304f\u306a\u308a\u307e\u3059\u3002\u52a0\u3048\u305f\u6db2\u4f53\u3082\u30b3\u30fc\u30d2\u30fc\u3092\u8584\u304f\u3057\u307e\u3059\u3002\u30b7\u30e3\u30ce\u30f3\u306e\u30a2\u30a4\u30b9\u30b3\u30fc\u30d2\u30fc\u304c65\u5ea6\u51b7\u3048\u300115\u30df\u30ea\u30ea\u30c3\u30c8\u30eb\u306e\u30af\u30ea\u30fc\u30e0\u3092\u52a0\u3048\u305f\u5834\u5408\u3001\u30b3\u30fc\u30d2\u30fc\u306f\u4f55\u30df\u30ea\u30ea\u30c3\u30c8\u30eb\u8584\u304f\u306a\u308a\u307e\u3059\u304b\uff1f", "answer_number": 75} +{"question": "\u30e9\u30eb\u30d5\u306e\u30ec\u30b3\u30fc\u30c9\u5e97\u3067\u306f\u3001\u4eba\u3005\u304c\u81ea\u5206\u306e\u53e4\u3044\u30ec\u30b3\u30fc\u30c9\u3092\u65b0\u3057\u3044\u3082\u306e\u3068\u4ea4\u63db\u3067\u304d\u307e\u3059\u30022\u679a\u306e\u53e4\u3044\u30ec\u30b3\u30fc\u30c9\u30921\u679a\u306e\u65b0\u3057\u3044\u30ec\u30b3\u30fc\u30c9\u3068\u4ea4\u63db\u3067\u304d\u307e\u3059\u30025\u4eba\u306e\u5ba2\u304c\u53e4\u3044\u30ec\u30b3\u30fc\u30c9\u3092\u6301\u3061\u8fbc\u307f\u3001\u5408\u308f\u305b\u30667\u679a\u306e\u65b0\u3057\u3044\u30ec\u30b3\u30fc\u30c9\u3092\u6301\u3061\u5e30\u308a\u307e\u3057\u305f\u3002\u3053\u306e5\u4eba\u306e\u5ba2\u306f\u5408\u8a08\u3067\u4f55\u679a\u306e\u53e4\u3044\u30ec\u30b3\u30fc\u30c9\u3092\u6301\u3061\u8fbc\u3093\u3060\u3067\u3057\u3087\u3046\u304b\uff1f", "answer_number": 14} +{"question": "\u4f1a\u793e\u306b\u306f\u73fe\u5728100\u4eba\u304c\u96c7\u7528\u3055\u308c\u3066\u304a\u308a\u3001\u30b8\u30a7\u30a4\u30df\u30fc\u306f\u305d\u306e\u4e2d\u306e\u30b3\u30f3\u30d4\u30e5\u30fc\u30bf\u30fc\u30d7\u30ed\u30b0\u30e9\u30de\u30fc\u3067\u3059\u3002\u30b7\u30cb\u30a2\u30d7\u30ed\u30b0\u30e9\u30de\u30fc\u306e\u7d66\u4e0e\u306f\u30b8\u30e5\u30cb\u30a2\u30d7\u30ed\u30b0\u30e9\u30de\u30fc\u3088\u308a\u3082\u6708\u306b400\u30c9\u30eb\u591a\u3044\u3067\u3059\u3002\u30b8\u30e5\u30cb\u30a2\u30d7\u30ed\u30b0\u30e9\u30de\u30fc\u306e\u6570\u304c\u5f93\u696d\u54e1\u7dcf\u6570\u306e2/5\u3067\u3042\u308a\u3001\u305d\u308c\u305e\u308c\u304c\u6708\u306b2000\u30c9\u30eb\u652f\u6255\u308f\u308c\u308b\u5834\u5408\u3001\u4f1a\u793e\u304c\u30d7\u30ed\u30b0\u30e9\u30de\u30fc\u5168\u54e1\u306b\u652f\u6255\u3046\u91d1\u984d\u306e\u5408\u8a08\u3092\u8a08\u7b97\u3057\u3066\u304f\u3060\u3055\u3044\u3002", "answer_number": 224000} +{"question": "\u30d0\u30b9\u30bf\u30fc\u30df\u30ca\u30eb\u3067\u3042\u308b\u4eba\u6570\u304c\u30d0\u30b9\u306b\u4e57\u308a\u307e\u3057\u305f\u3002\u6700\u521d\u306e\u30d0\u30b9\u505c\u30675\u4eba\u304c\u4e57\u308a\u8fbc\u307f\u307e\u3057\u305f\u3002\u6b21\u306e\u30d0\u30b9\u505c\u3067\u306f7\u4eba\u304c\u964d\u308a\u3066\u3001\u3055\u3089\u306b8\u4eba\u304c\u4e57\u308a\u8fbc\u307f\u307e\u3057\u305f\u30023\u3064\u76ee\u306e\u505c\u7559\u6240\u306b\u5411\u304b\u3046\u4eba\u6570\u304c\u5408\u8a08\u306720\u4eba\u3060\u3063\u305f\u5834\u5408\u3001\u30d0\u30b9\u30bf\u30fc\u30df\u30ca\u30eb\u3067\u30d0\u30b9\u306b\u4e57\u3063\u305f\u4eba\u6570\u306f\u4f55\u4eba\u3067\u3057\u3087\u3046\u304b\uff1f", "answer_number": 14} +{"question": "\u30aa\u30b9\u30ab\u30fc\u306f24\u500b\u306e\u30ed\u30ea\u30dd\u30c3\u30d7\u3092\u6301\u3063\u3066\u3044\u3066\u3001\u5b66\u6821\u306b\u884c\u304f\u9014\u4e2d\u30672\u500b\u98df\u3079\u307e\u3059\u3002\u53cb\u9054\u306b14\u500b\u914d\u308a\u307e\u3059\u3002\u5e30\u308a\u9053\u3067\u3001\u53cb\u9054\u306b\u3042\u3052\u305f\u6570\u306e2\u500d\u306e\u30ed\u30ea\u30dd\u30c3\u30d7\u3092\u8cb7\u3044\u307e\u3059\u3002\u305d\u306e\u591c\u306b\u3055\u3089\u306b3\u500b\u3001\u7fcc\u671d\u306b2\u500b\u98df\u3079\u307e\u3059\u3002\u30aa\u30b9\u30ab\u30fc\u306f\u4f55\u500b\u306e\u30ed\u30ea\u30dd\u30c3\u30d7\u3092\u6301\u3063\u3066\u3044\u307e\u3059\u304b\uff1f", "answer_number": 31} +{"question": "\u643a\u5e2f\u96fb\u8a71\u306f3\u5206\u306b\u3064\u304d1\u30d1\u30fc\u30bb\u30f3\u30c8\u30dd\u30a4\u30f3\u30c8\u306e\u5272\u5408\u3067\u5145\u96fb\u3055\u308c\u307e\u3059\u3002\u73fe\u5728\u3001\u96fb\u8a71\u306e\u5145\u96fb\u306f60%\u3067\u3059\u3002\u5b8c\u5168\u306b\u5145\u96fb\u3059\u308b\u307e\u3067\u306b\u4f55\u6642\u9593\u304b\u304b\u308a\u307e\u3059\u304b\uff1f", "answer_number": 2} +{"question": "\u30a8\u30ea\u30f3\u306f7\u672c\u306e\u30ed\u30ea\u30dd\u30c3\u30d7\u3092\u6301\u3063\u3066\u3044\u307e\u3059\u3002\u5f7c\u5973\u306e\u6bcd\u89aa\u304c\u3055\u3089\u306b10\u672c\u306e\u30ed\u30ea\u30dd\u30c3\u30d7\u3092\u30a8\u30ea\u30f3\u306b\u4e0e\u3048\u307e\u3057\u305f\u3002\u30a8\u30ea\u30f3\u304c\u30a8\u30e9\u306b3\u672c\u306e\u30ed\u30ea\u30dd\u30c3\u30d7\u3092\u3042\u3052\u305f\u5834\u5408\u3001\u5f7c\u5973\u306b\u306f\u4f55\u672c\u306e\u30ed\u30ea\u30dd\u30c3\u30d7\u304c\u6b8b\u3063\u3066\u3044\u307e\u3059\u304b\uff1f", "answer_number": 14} +{"question": "\u524d\u56de\u306e\u8cb7\u3044\u7269\u3067\u9867\u5ba2\u306f80\u30c9\u30eb\u4f7f\u3044\u307e\u3057\u305f\u3002\u4eca\u56de\u306e\u8cb7\u3044\u7269\u3067\u306f43\u30c9\u30eb\u4f7f\u3044\u3001\u7372\u5f97\u3057\u305f\u30ea\u30ef\u30fc\u30c9\u3092\u4f7f\u7528\u3057\u3001\u3055\u3089\u306b\u30ea\u30ef\u30fc\u30c9\u306e2\u500d\u306e\u984d\u3092\u5272\u5f15\u3059\u308b\u30af\u30fc\u30dd\u30f3\u3092\u9069\u7528\u3057\u307e\u3057\u305f\u3002\u3053\u306e\u8cb7\u3044\u7269\u3067\u9867\u5ba2\u306f\u4f55\u30c9\u30eb\u652f\u6255\u3044\u307e\u3057\u305f\u304b\uff1f", "answer_number": 31} +{"question": "\u30b8\u30e7\u30d6A\u306f\u5e74\u95932000\u6642\u9593\u3067\u6642\u7d6615\u30c9\u30eb\u3001\u7dcf\u7a0e\u738720%\u306e\u5dde\u306b\u3042\u308a\u307e\u3059\u3002\u30b8\u30e7\u30d6B\u306f\u5e74\u53ce42,000\u30c9\u30eb\u3067\u3001\u56fa\u5b9a\u8cc7\u7523\u7a0e6,000\u30c9\u30eb\u3068\u3001\u56fa\u5b9a\u8cc7\u7523\u7a0e\u5f8c\u306e\u7d14\u6240\u5f97\u306b\u5bfe\u3059\u308b\u7a0e\u738710%\u3092\u8ab2\u3059\u5dde\u306b\u3042\u308a\u307e\u3059\u3002\u7d14\u7d66\u4e0e\u304c\u9ad8\u3044\u65b9\u306e\u4ed5\u4e8b\u3067\u3001\u30cb\u30c3\u30af\u306f\u4ed6\u306e\u4ed5\u4e8b\u3068\u6bd4\u3079\u3066\u3069\u308c\u3060\u3051\u591a\u304f\u306e\u304a\u91d1\u3092\u7a3c\u3050\u3053\u3068\u304c\u3067\u304d\u308b\u3067\u3057\u3087\u3046\u304b\uff1f\n\n\u30b8\u30e7\u30d6A\u306e\u8a08\u7b97:\n\u5e74\u53ce = 2000\u6642\u9593 \u00d7 15\u30c9\u30eb/\u6642\u9593 = 30,000\u30c9\u30eb\n\u7a0e\u5f8c\u306e\u53ce\u5165 = 30,000\u30c9\u30eb \u00d7 (1 - 0.20) = 24,000\u30c9\u30eb\n\n\u30b8\u30e7\u30d6B\u306e\u8a08\u7b97:\n\u56fa\u5b9a\u8cc7\u7523\u7a0e\u5f8c\u306e\u7d14\u6240\u5f97 = 42,000\u30c9\u30eb - 6,000\u30c9\u30eb = 36,000\u30c9\u30eb\n\u7a0e\u5f8c\u306e\u53ce\u5165 = 36,000\u30c9\u30eb \u00d7 (1 - 0.10) = 32,400\u30c9\u30eb\n\n\u3057\u305f\u304c\u3063\u3066\u3001\u30b8\u30e7\u30d6B\u3067\u306e\u30cb\u30c3\u30af\u306e\u53ce\u5165\u306f\u30b8\u30e7\u30d6A\u3068\u6bd4\u3079\u3066\u300132,400\u30c9\u30eb - 24,000\u30c9\u30eb = 8,400\u30c9\u30eb\u591a\u304f\u306a\u308a\u307e\u3059\u3002", "answer_number": 8400} +{"question": "\u30b9\u30b3\u30c3\u30c8\u30e9\u30f3\u30c9\u306b\u306f220\u306e\u57ce\u304c\u3042\u308a\u307e\u3059\u3002\u305d\u306e\u3046\u306140\u30d1\u30fc\u30bb\u30f3\u30c8\u304c\u5ec3\u589f\u3067\u3042\u308a\u3001\u5ec3\u589f\u306e\u57ce\u306e\u534a\u5206\u306f\u7121\u4eba\u3067\u3059\u3002\u30b9\u30b3\u30c3\u30c8\u30e9\u30f3\u30c9\u306b\u306f\u4f55\u500b\u306e\u7121\u4eba\u306e\u5ec3\u589f\u304c\u3042\u308a\u307e\u3059\u304b\uff1f", "answer_number": 44} +{"question": "\u30d5\u30a1\u30cb\u30c1\u30e3\u30fc\u30e6\u30ca\u30a4\u30c6\u30c3\u30c9\u306e\u30aa\u30d5\u30a1\u30fc\u306f\u3001\u524d\u6255\u3044\u304c1,350\u30c9\u30eb\u3001\u6708\u3005\u306e\u5206\u5272\u6255\u3044\u304c350\u30c9\u30eb\u30676\u56de\u3067\u3059\u3002\u30b3\u30fc\u30b8\u30fc\u30db\u30fc\u30e0\u30ba\u306e\u30aa\u30d5\u30a1\u30fc\u306f\u3001\u524d\u6255\u3044\u304c1,100\u30c9\u30eb\u3001\u6708\u3005\u306e\u5206\u5272\u6255\u3044\u304c250\u30c9\u30eb\u30679\u56de\u3067\u3059\u3002\u3053\u306e2\u3064\u306e\u30aa\u30d5\u30a1\u30fc\u306e\u30b3\u30b9\u30c8\u306e\u5dee\u306f\u3044\u304f\u3089\u3067\u3059\u304b\uff1f", "answer_number": 100} +{"question": "\u30cb\u30c3\u30af\u3001\u30ea\u30c1\u30e3\u30fc\u30c9\u3001\u30b8\u30a7\u30a4\u30bd\u30f3\u3001\u305d\u3057\u3066DJ\u306f\u305d\u308c\u305e\u308c\u30da\u30a4\u30f3\u30c8\u30dc\u30fc\u30eb\u30ac\u30f3\u3092\u6301\u3063\u3066\u3044\u307e\u3059\u3002DJ\u306f8\u4e01\u3001\u30cb\u30c3\u30af\u306f10\u4e01\u3001RJ\u306f1\u4e01\u3001\u30ea\u30c1\u30e3\u30fc\u30c9\u306f5\u4e01\u6301\u3063\u3066\u3044\u307e\u3059\u3002\u5f7c\u3089\u304c\u305d\u308c\u305e\u308c\u306e\u30ac\u30f3\u3092\u5747\u7b49\u306b\u5206\u3051\u5408\u3063\u305f\u5834\u5408\u3001\u4e00\u4eba\u5f53\u305f\u308a\u4f55\u4e01\u6301\u3064\u3053\u3068\u306b\u306a\u308a\u307e\u3059\u304b\uff1f", "answer_number": 6} +{"question": "\u30e1\u30a4\u30bd\u30f3\u306f\u30011\u30d0\u30c3\u30c1\u306e\u30ad\u30e3\u30f3\u30c7\u30a3\u30fc\u3092\u4f5c\u308b\u306e\u306b\u7802\u7cd630\u30aa\u30f3\u30b9\u30011\u30d0\u30c3\u30c1\u306e\u30d5\u30a1\u30c3\u30b8\u3092\u4f5c\u308b\u306e\u306b\u7802\u7cd670\u30aa\u30f3\u30b9\u5fc5\u8981\u3067\u3059\u3002\u30ad\u30e3\u30f3\u30c7\u30a3\u30fc8\u30d0\u30c3\u30c1\u3068\u30d5\u30a1\u30c3\u30b81\u30d0\u30c3\u30c1\u3092\u4f5c\u308b\u306e\u306b\u5fc5\u8981\u306a\u7802\u7cd6\u306f\u5408\u8a08\u3067\u4f55\u30aa\u30f3\u30b9\u3067\u3057\u3087\u3046\u304b\uff1f", "answer_number": 310} +{"question": "\u30de\u30ea\u30a2\u306f1\u682a8\u30c9\u30eb\u3067\u682a\u30928\u682a\u8cfc\u5165\u3057\u307e\u3057\u305f\u3002\u30de\u30ea\u30a2\u304c\u4fdd\u6709\u3057\u3066\u3044\u308b\u6700\u521d\u306e\u5e74\u306b\u682a\u4fa1\u306f50%\u4e0a\u6607\u3057\u3001\u6b21\u306e\u5e74\u306b25%\u4e0b\u843d\u3057\u307e\u3057\u305f\u3002\u30de\u30ea\u30a2\u306e\u5168\u682a\u306e\u6700\u7d42\u7684\u306a\u4fa1\u5024\u306f\u3044\u304f\u3089\u3067\u3059\u304b\uff1f", "answer_number": 72} +{"question": "\u30eb\u30fc\u30af\u306f\u30db\u30c3\u30c8\u30c9\u30c3\u30b0\u30922\u672c\u98df\u3079\u307e\u3057\u305f\u3002\u30c8\u30fc\u30de\u30b9\u306f\u30eb\u30fc\u30af\u306e3\u500d\u306e\u30db\u30c3\u30c8\u30c9\u30c3\u30b0\u3092\u98df\u3079\u307e\u3057\u305f\u3002\u30b8\u30e7\u30f3\u306f\u30c8\u30fc\u30de\u30b9\u304c\u98df\u3079\u305f\u91cf\u306e\u534a\u5206\u3092\u98df\u3079\u307e\u3057\u305f\u3002\u30b8\u30e7\u30f3\u306f\u30eb\u30fc\u30af\u3088\u308a\u4f55\u672c\u591a\u304f\u30db\u30c3\u30c8\u30c9\u30c3\u30b0\u3092\u98df\u3079\u307e\u3057\u305f\u304b\uff1f", "answer_number": 1} +{"question": "200\u4eba\u306e\u751f\u5f92\u304c\u3044\u308b\u30af\u30e9\u30b9\u30923\u3064\u306e\u30b0\u30eb\u30fc\u30d7\u306b\u5206\u3051\u307e\u3059\u3002\u305d\u306e\u3046\u30612\u3064\u306e\u30b0\u30eb\u30fc\u30d7\u306f\u4eba\u6570\u304c\u7b49\u3057\u304f\u3001\u6700\u5f8c\u306e1\u3064\uff08\u6700\u5c0f\u306e\u30b0\u30eb\u30fc\u30d7\uff09\u306f\u4ed6\u306e\u30b0\u30eb\u30fc\u30d7\u3088\u308a\u308210\u4eba\u5c11\u306a\u3044\u3067\u3059\u3002\u3053\u306e\uff08\u6700\u5c0f\u306e\uff09\u30b0\u30eb\u30fc\u30d7\u306b\u306f\u4f55\u4eba\u306e\u751f\u5f92\u304c\u3044\u307e\u3059\u304b\uff1f", "answer_number": 60} +{"question": "\u30d6\u30e9\u30a6\u30f3\u8fb2\u5834\u4e3b\u306e\u8fb2\u5834\u306b\u306f\u3001\u9d8f\u3068\u725b\u3092\u5408\u308f\u305b\u306660\u5339\u306e\u52d5\u7269\u304c\u3044\u307e\u3059\u3002\u9d8f\u306f\u725b\u306e2\u500d\u3044\u307e\u3059\u3002\u3053\u308c\u3089\u306e\u52d5\u7269\u306e\u8db3\u306f\u5408\u8a08\u3067\u4f55\u672c\u3042\u308a\u307e\u3059\u304b\uff1f", "answer_number": 160} +{"question": 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"\u30de\u30c7\u30ea\u30f3\u306f\u6bce\u6708\u3001\u72ac\u306e\u305f\u3081\u306b\u98df\u6599\u3001\u304a\u3084\u3064\u3001\u85ac\u3092\u8cfc\u5165\u3057\u3066\u3044\u307e\u3059\u3002\u98df\u6599\u306f\u9031\u306b25\u30c9\u30eb\u3001\u304a\u3084\u3064\u306f\u6708\u306b20\u30c9\u30eb\u3001\u85ac\u306f\u6708\u306b100\u30c9\u30eb\u304b\u304b\u308a\u307e\u3059\u30021\u30f6\u6708\u30924\u9031\u9593\u3068\u3057\u305f\u5834\u5408\u3001\u30de\u30c7\u30ea\u30f3\u304c\u72ac\u306b\u304b\u3051\u308b\u8cbb\u7528\u306f1\u5e74\u9593\u3067\u3044\u304f\u3089\u306b\u306a\u308a\u307e\u3059\u304b\uff1f", "answer_number": 2640} diff --git a/package/samplers/evo_merge/trial.py b/package/samplers/evo_merge/trial.py new file mode 100644 index 00000000..714296dc --- /dev/null +++ b/package/samplers/evo_merge/trial.py @@ -0,0 +1,12 @@ +from langchain.llms.base import BaseLLM +from optuna.study import Study +from optuna.trial import Trial + + +class EvoMergeTrial(Trial): + def __init__(self, study: Study, trial_id: int) -> None: + super(EvoMergeTrial, self).__init__(study, trial_id) + self._trial_id = trial_id + + def suggest_model(self) -> BaseLLM: + return self.study.sampler.sample_model(self.study, self) diff --git a/pyproject.toml b/pyproject.toml index c844902e..7364407e 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -41,7 +41,7 @@ documentation = "TBD" bugtracker = "https://github.com/optuna/optunahub-registry/issues" [tool.setuptools.packages.find] -include = ["optunahub-registry*"] +include = ["optunahub-registry*", "package*"] [tool.setuptools.dynamic] version = {attr = "optunahub-registry.version.__version__"}

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