Datasets:
gabeorlanski
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Update README.md
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README.md
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@@ -55,7 +55,7 @@ BC-Transcoder supports:
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>>> load_dataset("gabeorlanski/bc-transcoder")
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DatasetDict({
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test: Dataset({
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features: ['qid', 'title', 'language', 'signature', 'arguments', 'entry_fn_name', 'entry_cls_name', 'test_code', 'source_py', 'source_cpp'],
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num_rows: 8384
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})
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})
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- `arguments`: The arguments of the problem.
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- `entry_fn_name`: The function's name to use an entry point.
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- `entry_cls_name`: The class name to use an entry point.
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- `test_code`: The raw testing script used in the language. If you want to use this, replace `PLACEHOLDER_FN_NAME` (and `PLACEHOLDER_CLS_NAME` if needed) with the corresponding entry points. Next, replace `PLACEHOLDER_CODE_BODY` with the postprocessed prediction.
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- `source_py`: The source solution in Python.
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- `source_cpp`: The source in C++.
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## Dataset Creation
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See section 2 of the [BabelCode Paper](https://arxiv.org/abs/2302.01973) to learn more about how the datasets are translated.
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>>> load_dataset("gabeorlanski/bc-transcoder")
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DatasetDict({
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test: Dataset({
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features: ['qid', 'title', 'language', 'signature', 'arguments', 'entry_fn_name', 'entry_cls_name', 'test_code', 'source_py', 'source_cpp', 'test_list', 'test_case_ids'],
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num_rows: 8384
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})
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})
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- `arguments`: The arguments of the problem.
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- `entry_fn_name`: The function's name to use an entry point.
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- `entry_cls_name`: The class name to use an entry point.
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- `source_py`: The source solution in Python.
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- `source_cpp`: The source in C++.
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- `test_code`: The raw testing script used in the language. If you want to use this, replace `PLACEHOLDER_FN_NAME` (and `PLACEHOLDER_CLS_NAME` if needed) with the corresponding entry points. Next, replace `PLACEHOLDER_CODE_BODY` with the postprocessed prediction.
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- `test_list`: The raw json line of the list of tests for the problem. To load them, use `json.loads`
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- `test_case_ids`: The list of test case ids for the problem. These are used to determine if a prediction passes or not.
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## Dataset Creation
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See section 2 of the [BabelCode Paper](https://arxiv.org/abs/2302.01973) to learn more about how the datasets are translated.
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