Convert dataset to Parquet (#5)

- Convert dataset to Parquet (4bfc047a7002cc24638f10e8855a20fbbbec630d)
- Delete loading script (ce880554b60b42b24b872c7acd26bfa9fb4e0aa5)
- Delete loading script auxiliary file (6e3bb97cf21cac956cd0511120a420fc490fbd19)
- Delete loading script auxiliary file (9679450cf55e2c7796b46ef46cfb6fd8a6c44671)

README.md

@@ -1,5 +1,4 @@
 ---
-pretty_name: CodeXGlueCcCloneDetectionPoj104
 annotations_creators:
 - found
 language_creators:
@@ -18,6 +17,7 @@ task_categories:
 - text-retrieval
 task_ids:
 - document-retrieval
+pretty_name: CodeXGlueCcCloneDetectionPoj104
 dataset_info:
   features:
   - name: id
@@ -36,8 +36,17 @@ dataset_info:
   - name: test
     num_bytes: 7227506
     num_examples: 12000
-  download_size: 8658581
+  download_size: 13348734
   dataset_size: 33789014
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+  - split: validation
+    path: data/validation-*
+  - split: test
+    path: data/test-*
 ---
 # Dataset Card for "code_x_glue_cc_clone_detection_poj_104"
 

code_x_glue_cc_clone_detection_poj104.py

@@ -1,93 +0,0 @@
-from typing import List
-
-import datasets
-
-from .common import TrainValidTestChild
-from .generated_definitions import DEFINITIONS
-
-
-_DESCRIPTION = """Given a code and a collection of candidates as the input, the task is to return Top K codes with the same semantic. Models are evaluated by MAP score.
-We use POJ-104 dataset on this task."""
-
-_CITATION = """@inproceedings{mou2016convolutional,
-title={Convolutional neural networks over tree structures for programming language processing},
-author={Mou, Lili and Li, Ge and Zhang, Lu and Wang, Tao and Jin, Zhi},
-booktitle={Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence},
-pages={1287--1293},
-year={2016}
-}"""
-
-
-class CodeXGlueCcCloneDetectionPoj104Impl(TrainValidTestChild):
-    _DESCRIPTION = _DESCRIPTION
-    _CITATION = _CITATION
-
-    _FEATURES = {
-        "id": datasets.Value("int32"),  # Index of the sample
-        "code": datasets.Value("string"),  # The full text of the function
-        "label": datasets.Value("string"),  # The id of problem that the source code solves
-    }
-
-    _SUPERVISED_KEYS = ["label"]
-
-    SPLIT_RANGES = {"train": (1, 65), "valid": (65, 81), "test": (81, 195)}
-
-    def _generate_examples(self, files, split_name):
-        cont = 0
-        for path, f in files:
-            # path are in the format ProgramData/{index}/{filename}
-            label = int(path.split("/")[1])
-            if self.SPLIT_RANGES[split_name][0] <= label <= self.SPLIT_RANGES[split_name][1]:
-                js = {}
-                js["label"] = str(label)
-                js["id"] = cont
-                js["code"] = f.read().decode("latin-1")
-                yield cont, js
-                cont += 1
-
-
-CLASS_MAPPING = {
-    "CodeXGlueCcCloneDetectionPoj104": CodeXGlueCcCloneDetectionPoj104Impl,
-}
-
-
-class CodeXGlueCcCloneDetectionPoj104(datasets.GeneratorBasedBuilder):
-    BUILDER_CONFIG_CLASS = datasets.BuilderConfig
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name=name, description=info["description"]) for name, info in DEFINITIONS.items()
-    ]
-
-    def _info(self):
-        name = self.config.name
-        info = DEFINITIONS[name]
-        if info["class_name"] in CLASS_MAPPING:
-            self.child = CLASS_MAPPING[info["class_name"]](info)
-        else:
-            raise RuntimeError(f"Unknown python class for dataset configuration {name}")
-        ret = self.child._info()
-        return ret
-
-    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
-        name = self.config.name
-        info = DEFINITIONS[name]
-        archive = dl_manager.download(info["raw_url"] + "/programs.tar.gz")
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={"files": dl_manager.iter_archive(archive), "split_name": "train"},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={"files": dl_manager.iter_archive(archive), "split_name": "valid"},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={"files": dl_manager.iter_archive(archive), "split_name": "test"},
-            ),
-        ]
-
-    def _generate_examples(self, files, split_name):
-        return self.child._generate_examples(files, split_name)

common.py

@@ -1,75 +0,0 @@
-from typing import List
-
-import datasets
-
-
-# Citation, taken from https://github.com/microsoft/CodeXGLUE
-_DEFAULT_CITATION = """@article{CodeXGLUE,
-         title={CodeXGLUE: A Benchmark Dataset and Open Challenge for Code Intelligence},
-         year={2020},}"""
-
-
-class Child:
-    _DESCRIPTION = None
-    _FEATURES = None
-    _CITATION = None
-    SPLITS = {"train": datasets.Split.TRAIN}
-    _SUPERVISED_KEYS = None
-
-    def __init__(self, info):
-        self.info = info
-
-    def homepage(self):
-        return self.info["project_url"]
-
-    def _info(self):
-        # This is the description that will appear on the datasets page.
-        return datasets.DatasetInfo(
-            description=self.info["description"] + "\n\n" + self._DESCRIPTION,
-            features=datasets.Features(self._FEATURES),
-            homepage=self.homepage(),
-            citation=self._CITATION or _DEFAULT_CITATION,
-            supervised_keys=self._SUPERVISED_KEYS,
-        )
-
-    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
-        SPLITS = self.SPLITS
-        _URL = self.info["raw_url"]
-        urls_to_download = {}
-        for split in SPLITS:
-            if split not in urls_to_download:
-                urls_to_download[split] = {}
-
-            for key, url in self.generate_urls(split):
-                if not url.startswith("http"):
-                    url = _URL + "/" + url
-                urls_to_download[split][key] = url
-
-        downloaded_files = {}
-        for k, v in urls_to_download.items():
-            downloaded_files[k] = dl_manager.download_and_extract(v)
-
-        return [
-            datasets.SplitGenerator(
-                name=SPLITS[k],
-                gen_kwargs={"split_name": k, "file_paths": downloaded_files[k]},
-            )
-            for k in SPLITS
-        ]
-
-    def check_empty(self, entries):
-        all_empty = all([v == "" for v in entries.values()])
-        all_non_empty = all([v != "" for v in entries.values()])
-
-        if not all_non_empty and not all_empty:
-            raise RuntimeError("Parallel data files should have the same number of lines.")
-
-        return all_empty
-
-
-class TrainValidTestChild(Child):
-    SPLITS = {
-        "train": datasets.Split.TRAIN,
-        "valid": datasets.Split.VALIDATION,
-        "test": datasets.Split.TEST,
-    }

data/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
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+oid sha256:4c1d6389d66a68c2b5ad4c345ac264b8f4062258aa870b74a3fd478b7cce4955
+size 2853417

data/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:36403bfcf7933eb40fcdadd543bfece26d18c52a4f1960a96550aa6b15708c03
+size 8031542

data/validation-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:497282b576c408edc2bf4ba0d1b12fda3cdadb102f3cd670a99fa6eeef587ab7
+size 2463775

generated_definitions.py

@@ -1,12 +0,0 @@
-DEFINITIONS = {
-    "default": {
-        "class_name": "CodeXGlueCcCloneDetectionPoj104",
-        "dataset_type": "Code-Code",
-        "description": "CodeXGLUE Clone-detection-POJ-104 dataset, available at https://github.com/microsoft/CodeXGLUE/tree/main/Code-Code/Clone-detection-POJ-104",
-        "dir_name": "Clone-detection-POJ-104",
-        "name": "default",
-        "project_url": "https://github.com/madlag/CodeXGLUE/tree/main/Code-Code/Clone-detection-POJ-104",
-        "raw_url": "https://raw.githubusercontent.com/madlag/CodeXGLUE/main/Code-Code/Clone-detection-POJ-104/dataset",
-        "sizes": {"test": 12000, "train": 32000, "validation": 8000},
-    }
-}