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README.md

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----
-annotations_creators: []
-language_creators:
-- crowdsourced
-- expert-generated
-language:
-- code
-license:
-- cc-by-sa-4.0
-multilinguality:
-- multilingual
-size_categories:
-- unknown
-source_datasets: []
-task_categories:
-- text-generation
-task_ids:
-- language-modeling
-pretty_name: xlcost-text-to-code
----
-
-# XLCost for text-to-code synthesis
-
-## Dataset Description
-This is a subset of [XLCoST benchmark](https://github.com/reddy-lab-code-research/XLCoST), for text-to-code generation at snippet level and program level for **7** programming languages: `Python, C, C#, C++, Java, Javascript and PHP`. 
-
-## Languages
-
-The dataset contains text in English and its corresponding code translation. Each program is divided into several code snippets, so the snipppet-level subsets contain these code snippets with their corresponding comments, for program-level subsets, the comments were concatenated in one long description. Moreover, programs in all the languages are aligned at the snippet level and the comment for a particular snippet is the same across all the languages. 
-
-## Dataset Structure
-To load the dataset you need to specify a subset among the **14 exiting instances**: `LANGUAGE-snippet-level/LANGUAGE-program-level` for `LANGUAGE` in `[Python, C, Csharp, C++, Java, Javascript and PHP]`. By default `Python-snippet-level` is loaded. 
-
-```python
-from datasets import load_dataset
-load_dataset("codeparrot/xlcost-text-to-code", "Python-program-level")
-
-DatasetDict({
-    train: Dataset({
-        features: ['text', 'code'],
-        num_rows: 9263
-    })
-    test: Dataset({
-        features: ['text', 'code'],
-        num_rows: 887
-    })
-    validation: Dataset({
-        features: ['text', 'code'],
-        num_rows: 472
-    })
-})
-```
-
-```python
-next(iter(data["train"]))
-{'text': 'Maximum Prefix Sum possible by merging two given arrays | Python3 implementation of the above approach ; Stores the maximum prefix sum of the array A [ ] ; Traverse the array A [ ] ; Stores the maximum prefix sum of the array B [ ] ; Traverse the array B [ ] ; Driver code',
- 'code': 'def maxPresum ( a , b ) : NEW_LINE INDENT X = max ( a [ 0 ] , 0 ) NEW_LINE for i in range ( 1 , len ( a ) ) : NEW_LINE INDENT a [ i ] += a [ i - 1 ] NEW_LINE X = max ( X , a [ i ] ) NEW_LINE DEDENT Y = max ( b [ 0 ] , 0 ) NEW_LINE for i in range ( 1 , len ( b ) ) : NEW_LINE INDENT b [ i ] += b [ i - 1 ] NEW_LINE Y = max ( Y , b [ i ] ) NEW_LINE DEDENT return X + Y NEW_LINE DEDENT A = [ 2 , - 1 , 4 , - 5 ] NEW_LINE B = [ 4 , - 3 , 12 , 4 , - 3 ] NEW_LINE print ( maxPresum ( A , B ) ) NEW_LINE'}
-```
-Note that the data undergo some tokenization hence the additional whitespaces and the use of NEW_LINE instead of `\n` and INDENT instead of `\t`, DEDENT to cancel indentation...
-
-## Data Fields
-
-* text: natural language description/comment
-* code: code at snippet/program level
-
-## Data Splits
-
-Each subset has three splits: train, test and validation.
-
-## Citation Information
-
-```
-@misc{zhu2022xlcost,
-     title = {XLCoST: A Benchmark Dataset for Cross-lingual Code Intelligence},
-     url = {https://arxiv.org/abs/2206.08474},
-     author = {Zhu, Ming and Jain, Aneesh and Suresh, Karthik and Ravindran, Roshan and Tipirneni, Sindhu and Reddy, Chandan K.},
-     year = {2022},
-     eprint={2206.08474},
-     archivePrefix={arXiv}
-}
-```

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