[Feat] Add codegeex2 and Humanevalx

configs/datasets/humanevalx/humanevalx_gen.py

@@ -0,0 +1,4 @@
+from mmengine.config import read_base
+
+with read_base():
+    from .humanevalx_gen_fd5822 import humanevalx_datasets  # noqa: F401, F403

configs/datasets/humanevalx/humanevalx_gen_fd5822.py

@@ -0,0 +1,37 @@
+from opencompass.openicl.icl_prompt_template import PromptTemplate
+from opencompass.openicl.icl_retriever import ZeroRetriever
+from opencompass.openicl.icl_inferencer import GenInferencer
+from opencompass.datasets import HumanevalXDataset, HumanevalXEvaluator
+
+humanevalx_reader_cfg = dict(
+    input_columns=['prompt'], output_column='task_id', train_split='test')
+
+humanevalx_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template='{prompt}'),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=GenInferencer, max_out_len=1024))
+
+humanevalx_eval_cfg_dict = {
+    lang : dict(
+            evaluator=dict(
+                type=HumanevalXEvaluator, 
+                language=lang, 
+                ip_address="localhost",    # replace to your code_eval_server ip_address, port
+                port=5000),               # refer to https://github.com/Ezra-Yu/code-evaluator to launch a server
+            pred_role='BOT')
+    for lang in ['python', 'cpp', 'go', 'java', 'js']   # do not support rust now
+}
+
+humanevalx_datasets = [
+    dict(
+        type=HumanevalXDataset,
+        abbr=f'humanevalx-{lang}',
+        language=lang,
+        path='./data/humanevalx',
+        reader_cfg=humanevalx_reader_cfg,
+        infer_cfg=humanevalx_infer_cfg,
+        eval_cfg=humanevalx_eval_cfg_dict[lang])
+    for lang in ['python', 'cpp', 'go', 'java', 'js']
+]

configs/eval_codegeex2.py

@@ -0,0 +1,7 @@
+from mmengine.config import read_base
+
+with read_base():
+    from .datasets.humanevalx.humanevalx_gen import humanevalx_datasets
+    from .models.hf_codegeex2_6b import models
+
+datasets = humanevalx_datasets

configs/models/hf_codegeex2_6b.py

@@ -0,0 +1,25 @@
+from opencompass.models import HuggingFace
+
+# refer to https://github.com/THUDM/CodeGeeX2/tree/main
+# For pass@1   : n=20 , temperature=0.2, top_p=0.95
+# For Pass@10  : n=200, temperature=0.8, top_p=0.95
+# For Pass@100 : n=200, temperature=0.8, top_p=0.95
+
+models = [
+    dict(
+        type=HuggingFace,
+        abbr='codegeex2-6b',
+        path='THUDM/codegeex2-6b',
+        tokenizer_path='THUDM/codegeex2-6b',
+        tokenizer_kwargs=dict(
+           padding_side='left',
+           truncation_side='left',
+           trust_remote_code=True,
+        ),
+        max_out_len=1024,
+        max_seq_len=2048,
+        batch_size=8,
+        model_kwargs=dict(trust_remote_code=True, device_map='auto'),
+        run_cfg=dict(num_gpus=1, num_procs=1),
+    )
+]

docs/en/advanced_guides/code_eval_service.md

@@ -0,0 +1,85 @@
+# Code Evaluation Service
+
+We support evaluating datasets of multiple programming languages, similar to [humaneval-x](https://huggingface.co/datasets/THUDM/humaneval-x). Before starting, make sure that you have started the code evaluation service. You can refer to the [code-evaluator](https://github.com/Ezra-Yu/code-evaluator) project for the code evaluation service.
+
+## Launching the Code Evaluation Service
+
+Make sure you have installed Docker, then build an image and run a container service.
+
+Build the Docker image:
+
+```shell
+git clone https://github.com/Ezra-Yu/code-evaluator.git
+cd code-evaluator/docker
+sudo docker build -t code-eval:latest .
+```
+
+After obtaining the image, create a container with the following commands:
+
+```shell
+# Log output format
+sudo docker run -it -p 5000:5000 code-eval:latest python server.py
+
+# Run the program in the background
+# sudo docker run -itd -p 5000:5000 code-eval:latest python server.py
+
+# Using different ports
+# sudo docker run -itd -p 5001:5001 code-eval:latest python server.py --port 5001
+```
+
+Ensure that you can access the service and check the following commands (skip this step if you are running the service on a local host):
+
+```shell
+ping your_service_ip_address
+telnet your_service_ip_address your_service_port
+```
+
+```note
+If computing nodes cannot connect to the evaluation service, you can directly run `python run.py xxx...`. The resulting code will be saved in the 'outputs' folder. After migration, use [code-evaluator](https://github.com/Ezra-Yu/code-evaluator) directly to get the results (no need to consider the eval_cfg configuration later).
+```
+
+## Configuration File
+
+We have provided the [configuration file](https://github.com/InternLM/opencompass/blob/main/configs/eval_codegeex2.py) for evaluating huamaneval-x on codegeex2 .
+
+The dataset and related post-processing configuration files can be found at this [link](https://github.com/InternLM/opencompass/tree/main/configs/datasets/humanevalx). Note the `evaluator` field in `humanevalx_eval_cfg_dict`.
+
+```python
+from opencompass.openicl.icl_prompt_template import PromptTemplate
+from opencompass.openicl.icl_retriever import ZeroRetriever
+from opencompass.openicl.icl_inferencer import GenInferencer
+from opencompass.datasets import HumanevalXDataset, HumanevalXEvaluator
+
+humanevalx_reader_cfg = dict(
+    input_columns=['prompt'], output_column='task_id', train_split='test')
+
+humanevalx_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template='{prompt}'),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=GenInferencer, max_out_len=1024))
+
+humanevalx_eval_cfg_dict = {
+    lang : dict(
+            evaluator=dict(
+                type=HumanevalXEvaluator,
+                language=lang,
+                ip_address="localhost",    # replace to your code_eval_server ip_address, port
+                port=5000),               # refer to https://github.com/Ezra-Yu/code-evaluator to launch a server
+            pred_role='BOT')
+    for lang in ['python', 'cpp', 'go', 'java', 'js']   # do not support rust now
+}
+
+humanevalx_datasets = [
+    dict(
+        type=HumanevalXDataset,
+        abbr=f'humanevalx-{lang}',
+        language=lang,
+        path='./data/humanevalx',
+        reader_cfg=humanevalx_reader_cfg,
+        infer_cfg=humanevalx_infer_cfg,
+        eval_cfg=humanevalx_eval_cfg_dict[lang])
+    for lang in ['python', 'cpp', 'go', 'java', 'js']
+]
+```

docs/en/index.rst

@@ -37,15 +37,6 @@ We always welcome *PRs* and *Issues* for the betterment of OpenCompass.
    user_guides/experimentation.md
    user_guides/metrics.md
 
-.. _AdvancedGuides:
-.. toctree::
-   :maxdepth: 1
-   :caption: Advanced Guides
-
-   advanced_guides/new_dataset.md
-   advanced_guides/new_model.md
-   advanced_guides/evaluation_turbomind.md
-
 .. _Prompt:
 .. toctree::
    :maxdepth: 1
@@ -56,6 +47,17 @@ We always welcome *PRs* and *Issues* for the betterment of OpenCompass.
    prompt/meta_template.md
    prompt/chain_of_thought.md
 
+
+.. _AdvancedGuides:
+.. toctree::
+   :maxdepth: 1
+   :caption: Advanced Guides
+
+   advanced_guides/new_dataset.md
+   advanced_guides/new_model.md
+   advanced_guides/evaluation_turbomind.md
+   advanced_guides/code_eval_service.md
+
 .. _Tools:
 .. toctree::
    :maxdepth: 1

docs/zh_cn/advanced_guides/code_eval_service.md

@@ -0,0 +1,86 @@
+# 代码评测服务
+
+我们支持评测多编程语言的数据集，类似 [humaneval-x](https://huggingface.co/datasets/THUDM/humaneval-x). 在启动之前需要确保你已经启动了代码评测服务，代码评测服务可参考[code-evaluator](https://github.com/Ezra-Yu/code-evaluator)项目。
+
+## 启动代码评测服务
+
+确保您已经安装了 docker，然后构建一个镜像并运行一个容器服务。
+
+构建 Docker 镜像：
+
+```shell
+git clone https://github.com/Ezra-Yu/code-evaluator.git
+cd code-evaluator/docker
+sudo docker build -t code-eval:latest .
+```
+
+获取镜像后，使用以下命令创建容器：
+
+```shell
+# 输出日志格式
+sudo docker run -it -p 5000:5000 code-eval:latest python server.py
+
+# 在后台运行程序
+# sudo docker run -itd -p 5000:5000 code-eval:latest python server.py
+
+# 使用不同的端口
+# sudo docker run -itd -p 5001:5001 code-eval:latest python server.py --port 5001
+```
+
+确保您能够访问服务，检查以下命令(如果在本地主机中运行服务，就跳过这个操作)：
+
+```shell
+ping your_service_ip_address
+telnet your_service_ip_address your_service_port
+```
+
+```note
+如果运算节点不能连接到评估服务，也可直接运行 `python run.py xxx...`，代码生成结果会保存在 'outputs' 文件夹下，迁移后直接使用 [code-evaluator](https://github.com/Ezra-Yu/code-evaluator) 评测得到结果（不需要考虑后面 eval_cfg 的配置）。
+```
+
+## 配置文件
+
+我么已经给了 huamaneval-x 在 codegeex2 上评估的[配置文件](https://github.com/InternLM/opencompass/blob/main/configs/eval_codegeex2.py)。
+
+其中数据集以及相关后处理的配置文件为这个[链接](https://github.com/InternLM/opencompass/tree/main/configs/datasets/humanevalx)， 需要注意 `humanevalx_eval_cfg_dict` 中的
+`evaluator` 字段。
+
+```python
+from opencompass.openicl.icl_prompt_template import PromptTemplate
+from opencompass.openicl.icl_retriever import ZeroRetriever
+from opencompass.openicl.icl_inferencer import GenInferencer
+from opencompass.datasets import HumanevalXDataset, HumanevalXEvaluator
+
+humanevalx_reader_cfg = dict(
+    input_columns=['prompt'], output_column='task_id', train_split='test')
+
+humanevalx_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template='{prompt}'),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=GenInferencer, max_out_len=1024))
+
+humanevalx_eval_cfg_dict = {
+    lang : dict(
+            evaluator=dict(
+                type=HumanevalXEvaluator,
+                language=lang,
+                ip_address="localhost",    # replace to your code_eval_server ip_address, port
+                port=5000),               # refer to https://github.com/Ezra-Yu/code-evaluator to launch a server
+            pred_role='BOT')
+    for lang in ['python', 'cpp', 'go', 'java', 'js']   # do not support rust now
+}
+
+humanevalx_datasets = [
+    dict(
+        type=HumanevalXDataset,
+        abbr=f'humanevalx-{lang}',
+        language=lang,
+        path='./data/humanevalx',
+        reader_cfg=humanevalx_reader_cfg,
+        infer_cfg=humanevalx_infer_cfg,
+        eval_cfg=humanevalx_eval_cfg_dict[lang])
+    for lang in ['python', 'cpp', 'go', 'java', 'js']
+]
+```

docs/zh_cn/index.rst

@@ -56,6 +56,7 @@ OpenCompass 上手路线
    advanced_guides/new_dataset.md
    advanced_guides/new_model.md
    advanced_guides/evaluation_turbomind.md
+   advanced_guides/code_eval_service.md
 
 .. _工具:
 .. toctree::

opencompass/datasets/__init__.py

@@ -30,6 +30,7 @@
 from .hellaswag import *  # noqa: F401, F403
 from .huggingface import *  # noqa: F401, F403
 from .humaneval import *  # noqa: F401, F403
+from .humanevalx import *  # noqa: F401, F403
 from .iwslt2017 import *  # noqa: F401, F403
 from .jigsawmultilingual import *  # noqa: F401, F403
 from .lambada import *  # noqa: F401, F403