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--- |
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task_categories: |
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- Code Generation |
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- Translation |
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- Text2Text generation |
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--- |
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# CoNaLa Dataset for Code Generation |
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## Table of content |
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- [Dataset Description](#dataset-description) |
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- [Languages](#languages) |
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- [Dataset Structure](#dataset-structure) |
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- [Data Instances](#data-instances) |
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- [Data Fields](#data-fields) |
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- [Data Splits](#data-splits) |
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## Dataset Descritpion |
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This dataset has been processed for Code Generation. CMU CoNaLa, the Code/Natural Language Challenge is a joint project of the Carnegie Mellon University NeuLab and STRUDEL Lab. This dataset was designed to test systems for generating program snippets from natural language. It is avilable at https://conala-corpus.github.io/ , and this is about 13k records from the full corpus of about 600k examples. |
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### Languages |
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English |
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## Dataset Structure |
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### Data Instances |
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A sample from this dataset looks as follows: |
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```json |
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[ |
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{ |
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"intent": "convert a list to a dictionary in python", |
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"snippet": "b = dict(zip(a[0::2], a[1::2]))" |
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}, |
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{ |
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"intent": "python - sort a list of nested lists", |
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"snippet": "l.sort(key=sum_nested)" |
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} |
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] |
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``` |
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### Dataset Fields |
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The dataset has the following fields (also called "features"): |
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```json |
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{ |
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"intent": "Value(dtype='string', id=None)", |
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"snippet": "Value(dtype='string', id=None)" |
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} |
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``` |
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### Dataset Splits |
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This dataset is split into a train, validation and test split. The split sizes are as follow: |
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| Split name | Num samples | |
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| ------------ | ------------------- | |
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| train | 11125 | |
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| valid | 1237 | |
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| test | 500 | |
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