参考：
medium
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:code_x_glue_cc_code_refinement/medium')
- 说明：
CodeXGLUE code-refinement dataset, available at https://github.com/microsoft/CodeXGLUE/tree/main/Code-Code/code-refinement
We use the dataset released by this paper(https://arxiv.org/pdf/1812.08693.pdf). The source side is a Java function with bugs and the target side is the refined one. All the function and variable names are normalized. Their dataset contains two subsets ( i.e.small and medium) based on the function length.
- 许可：无已知许可
- 版本：0.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'test' |
6545 |
'train' |
52364 |
'validation' |
6546 |
- 特征：
{
"id": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"buggy": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"fixed": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
small
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:code_x_glue_cc_code_refinement/small')
- 说明：
CodeXGLUE code-refinement dataset, available at https://github.com/microsoft/CodeXGLUE/tree/main/Code-Code/code-refinement
We use the dataset released by this paper(https://arxiv.org/pdf/1812.08693.pdf). The source side is a Java function with bugs and the target side is the refined one. All the function and variable names are normalized. Their dataset contains two subsets ( i.e.small and medium) based on the function length.
- 许可：无已知许可
- 版本：0.0.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'test' |
5835 |
'train' |
46680 |
'validation' |
5835 |
- 特征：
{
"id": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"buggy": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"fixed": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}