From 89f38595e90070fcc9e5cfb30fa25cd2c85a154e Mon Sep 17 00:00:00 2001 From: boX <442572328@qq.com> Date: Sat, 26 Oct 2024 02:55:59 +0800 Subject: [PATCH] updated smart_coding large model benchmark Signed-off-by: boX <442572328@qq.com> --- .../singletask_learning.py | 5 +- core/testenvmanager/dataset/dataset.py | 68 ++---------------- docs/guides/images/ianvs_arch.png | Bin 121617 -> 144302 bytes .../Smart Coding benchmark suite Proposal.md | 4 +- .../issue/testalgorithms/gen/basemodel.py | 25 ++++--- 5 files changed, 21 insertions(+), 81 deletions(-) diff --git a/core/testcasecontroller/algorithm/paradigm/singletask_learning/singletask_learning.py b/core/testcasecontroller/algorithm/paradigm/singletask_learning/singletask_learning.py index 3194b7cd..19972538 100644 --- a/core/testcasecontroller/algorithm/paradigm/singletask_learning/singletask_learning.py +++ b/core/testcasecontroller/algorithm/paradigm/singletask_learning/singletask_learning.py @@ -84,8 +84,5 @@ def _inference(self, job, trained_model): inference_output_dir = os.path.join(self.workspace, "output/inference/") os.environ["RESULT_SAVED_URL"] = inference_output_dir job.load(trained_model) - if hasattr(inference_dataset, 'need_other_info'): - infer_res = job.predict(inference_dataset) - else: - infer_res = job.predict(inference_dataset.x) + infer_res = job.predict(inference_dataset.x) return infer_res diff --git a/core/testenvmanager/dataset/dataset.py b/core/testenvmanager/dataset/dataset.py index ba795af9..16bd038f 100644 --- a/core/testenvmanager/dataset/dataset.py +++ b/core/testenvmanager/dataset/dataset.py @@ -16,10 +16,9 @@ import os import tempfile -import json import pandas as pd -from sedna.datasources import CSVDataParse, TxtDataParse, JSONDataParse, JsonlDataParse, JSONMetaDataParse +from sedna.datasources import CSVDataParse, TxtDataParse, JSONDataParse from core.common import utils from core.common.constant import DatasetFormat @@ -39,28 +38,12 @@ class Dataset: def __init__(self, config): self.train_url: str = "" self.test_url: str = "" - self.train_index: str = "" - self.test_index: str = "" - self.train_data: str = "" - self.test_data: str = "" - self.train_data_info: str = "" - self.test_data_info: str = "" self.label: str = "" self._parse_config(config) def _check_fields(self): - if self.train_index: - self._check_dataset_url(self.train_index) - if self.test_index: - self._check_dataset_url(self.test_index) - if self.train_data: - self._check_dataset_url(self.train_data) - if self.test_data: - self._check_dataset_url(self.test_data) - if self.train_data_info: - self._check_dataset_url(self.train_data_info) - if self.test_data_info: - self._check_dataset_url(self.test_data_info) + self._check_dataset_url(self.train_url) + self._check_dataset_url(self.test_url) def _parse_config(self, config): for attr, value in config.items(): @@ -120,20 +103,6 @@ def _process_index_file(self, file_url): return None - def _process_data_file(self, file_url): - file_format = utils.get_file_format(file_url) - if file_format == DatasetFormat.JSONL.value: - return file_url - - return None - - def _process_data_info_file(self, file_url): - file_format = utils.get_file_format(file_url) - if file_format == DatasetFormat.JSON.value: - return file_url - - return None - def process_dataset(self): """ process dataset: @@ -142,26 +111,9 @@ def process_dataset(self): in the index file(e.g.: txt index file). """ - if self.train_index: - self.train_url = self._process_index_file(self.train_index) - elif self.train_data: - self.train_url = self._process_data_file(self.train_data) - elif self.train_data_info: - self.train_url = self._process_data_info_file(self.train_data_info) - # raise NotImplementedError('to be done') - else: - raise NotImplementedError('not one of train_index/train_data/train_data_info') - - if self.test_index: - self.test_url = self._process_index_file(self.test_index) - elif self.test_data: - self.test_url = self._process_data_file(self.test_data) - elif self.test_data_info: - self.test_url = self._process_data_info_file(self.test_data_info) - # raise NotImplementedError('to be done') - else: - raise NotImplementedError('not one of test_index/test_data/test_data_info') + self.train_url = self._process_index_file(self.train_url) + self.test_url = self._process_index_file(self.test_url) # pylint: disable=too-many-arguments def split_dataset(self, dataset_url, dataset_format, ratio, method="default", @@ -436,11 +388,6 @@ def load_data(cls, file: str, data_type: str, label=None, use_raw=False, feature e.g.: TxtDataParse, CSVDataParse. """ - if file.split('/')[-1] == "metadata.json": - data = JSONMetaDataParse(data_type=data_type, func=feature_process) - data.parse(file) - return data - data_format = utils.get_file_format(file) data = None @@ -450,14 +397,11 @@ def load_data(cls, file: str, data_type: str, label=None, use_raw=False, feature if data_format == DatasetFormat.TXT.value: data = TxtDataParse(data_type=data_type, func=feature_process) + #print(file) data.parse(file, use_raw=use_raw) if data_format == DatasetFormat.JSON.value: data = JSONDataParse(data_type=data_type, func=feature_process) data.parse(file) - if data_format == DatasetFormat.JSONL.value: - data = JsonlDataParse(data_type=data_type, func=feature_process) - data.parse(file) - return data diff --git a/docs/guides/images/ianvs_arch.png b/docs/guides/images/ianvs_arch.png index 480ffdd6ac276b32ef0cdd3b66af19a167915a88..4b6c4e80a585917707eeb623fc56c054c99260e8 100644 GIT binary patch literal 144302 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a/docs/proposals/scenarios/Smart_Coding/Smart Coding benchmark suite Proposal.md b/docs/proposals/scenarios/Smart_Coding/Smart Coding benchmark suite Proposal.md index 1887c628..b612a1ad 100644 --- a/docs/proposals/scenarios/Smart_Coding/Smart Coding benchmark suite Proposal.md +++ b/docs/proposals/scenarios/Smart_Coding/Smart Coding benchmark suite Proposal.md @@ -75,13 +75,13 @@ The format of the issue test set is as follows: "body":"This is not possible right now afaik :/\r\n\r\nMaybe we could have something like this ? wdyt ?\r\n\r\n```python\r\nds = interleave_datasets(\r\n [shuffled_dataset_a, dataset_b],\r\n probabilities=probabilities,\r\n stopping_strategy='all_exhausted',\r\n reshuffle_each_iteration=True,\r\n)", "answer_1": { "user_login": "name", - "created_at":"time", + "created_at":"time" "updated_at": "time", "body":"This is not possible right now afaik :/\r\n\r\nMaybe we could have something like this ? wdyt ?\r\n\r\n```python\r\nds = interleave_datasets(\r\n [shuffled_dataset_a, dataset_b],\r\n probabilities=probabilities,\r\n stopping_strategy='all_exhausted',\r\n reshuffle_each_iteration=True,\r\n)", }, "answer_2": { "user_login": "name", - "created_at":"time", + "created_at":"time" "updated_at": "time", "body":"XXXX" }, diff --git a/examples/smart_coding/smart_coding_learning_bench/issue/testalgorithms/gen/basemodel.py b/examples/smart_coding/smart_coding_learning_bench/issue/testalgorithms/gen/basemodel.py index 28f9b82a..e6375c8e 100644 --- a/examples/smart_coding/smart_coding_learning_bench/issue/testalgorithms/gen/basemodel.py +++ b/examples/smart_coding/smart_coding_learning_bench/issue/testalgorithms/gen/basemodel.py @@ -12,7 +12,7 @@ # See the License for the specific language governing permissions and # limitations under the License. -from __future__ import absolute_import, division, LOGGER.info_function +from __future__ import absolute_import, division import os import tempfile @@ -44,11 +44,11 @@ class BaseModel: def __init__(self, **kwargs): self.model = AutoModelForCausalLM.from_pretrained( - "/root/autodl-tmp/Qwen2.5-Coder-1.5B-Instruct", + "/home/xiebo/model/Qwen2.5-Coder-1.5B-Instruct", torch_dtype="auto", device_map="auto" ) - self.tokenizer = AutoTokenizer.from_pretrained("/root/autodl-tmp/Qwen2.5-Coder-1.5B-Instruct") + self.tokenizer = AutoTokenizer.from_pretrained("/home/xiebo/model/Qwen2.5-Coder-1.5B-Instruct") def train(self, train_data, valid_data=None, **kwargs): LOGGER.info("BaseModel train") @@ -58,17 +58,15 @@ def save(self, model_path): def predict(self, data, input_shape=None, **kwargs): LOGGER.info("BaseModel predict") - - if 'infer_system_prompt' in data.prompts: - infer_system_prompt = data.prompts['infer_system_prompt'] + LOGGER.info(f"Dataset: {data.dataset_name}") + LOGGER.info(f"Description: {data.description}") + LOGGER.info(f"Data Level 1 Dim: {data.level_1_dim}") + LOGGER.info(f"Data Level 2 Dim: {data.level_2_dim}") answer_list = [] for line in tqdm(data.x, desc="Processing", unit="question"): history = [] - query = line.split('||')[0] - if infer_system_prompt: - history.append({"role": "system", "content": infer_system_prompt}) - history.append({"role": "user", "content": query}) + history.append({"role": "user", "content": line}) response = self._infer(history) answer_list.append(response) @@ -76,8 +74,7 @@ def predict(self, data, input_shape=None, **kwargs): # evaluate by llm for index in tqdm(range(len(answer_list)), desc="Evaluating", ascii=False, ncols=75): - prompt = data.prompts['eval_user_template'].replace('{question}', data.x[index].split('||')[0]).replace( - '{reference}', data.x[index].split('||')[1]).replace('{answer}', answer_list[index]) + prompt = data.judge_prompts[index] + answer_list[index] judgement = self._openai_generate(prompt) judgement_list.append(judgement) @@ -112,6 +109,8 @@ def _infer(self, messages): def _openai_generate(self, user_question, system=None): key = os.getenv("DEEPSEEK_API_KEY") + if not key: + raise ValueError("You should set DEEPSEEK_API_KEY in your env.") client = OpenAI(api_key=key, base_url="https://api.deepseek.com") messages = [] @@ -127,4 +126,4 @@ def _openai_generate(self, user_question, system=None): res = response.choices[0].message.content - return res \ No newline at end of file + return res