Convert dataset to Parquet (#4)

- Convert dataset to Parquet (712090f03553f75a54d5386ef14d6d7adf4942b0)
- Add lv_en data files (7ab93ab0181ba2dae6373c41e6ab34fda21c8c79)
- Add no_en data files (ef78499927f74772356ebd3ee0b458ea98df57e3)
- Add zh_en data files (987b1d2e23b1ebded170b0552bbfdd378d3e9c9c)
- Delete loading script (05101d34bce800d4a1bd3108b9c4538830e42b3f)
- Delete loading script auxiliary file (7952df52903e0f786eff786b2c50924272eaef0e)
- Delete loading script auxiliary file (9133a08fb4fcdd34b13fabad6ac617c1738f767c)

README.md

@@ -34,16 +34,16 @@ dataset_info:
     dtype: string
   splits:
   - name: train
-    num_bytes: 8163215
+    num_bytes: 8163175
     num_examples: 42701
   - name: validation
-    num_bytes: 190340
+    num_bytes: 190332
     num_examples: 1000
   - name: test
-    num_bytes: 190780
+    num_bytes: 190772
     num_examples: 1000
-  download_size: 8007867
-  dataset_size: 8544335
+  download_size: 4322666
+  dataset_size: 8544279
 - config_name: lv_en
   features:
   - name: id
@@ -54,16 +54,16 @@ dataset_info:
     dtype: string
   splits:
   - name: train
-    num_bytes: 3644127
+    num_bytes: 3644111
     num_examples: 18749
   - name: validation
-    num_bytes: 192519
+    num_bytes: 192511
     num_examples: 1000
   - name: test
-    num_bytes: 190875
+    num_bytes: 190867
     num_examples: 1000
-  download_size: 3778501
-  dataset_size: 4027521
+  download_size: 1997959
+  dataset_size: 4027489
 - config_name: no_en
   features:
   - name: id
@@ -74,16 +74,16 @@ dataset_info:
     dtype: string
   splits:
   - name: train
-    num_bytes: 8761795
+    num_bytes: 8761755
     num_examples: 44322
   - name: validation
-    num_bytes: 203823
+    num_bytes: 203815
     num_examples: 1000
   - name: test
-    num_bytes: 197135
+    num_bytes: 197127
     num_examples: 1000
-  download_size: 8606833
-  dataset_size: 9162753
+  download_size: 4661188
+  dataset_size: 9162697
 - config_name: zh_en
   features:
   - name: id
@@ -94,16 +94,49 @@ dataset_info:
     dtype: string
   splits:
   - name: train
-    num_bytes: 9592196
+    num_bytes: 9592148
     num_examples: 50154
   - name: validation
-    num_bytes: 192155
+    num_bytes: 192147
     num_examples: 1000
   - name: test
-    num_bytes: 195245
+    num_bytes: 195237
     num_examples: 1000
-  download_size: 9353684
-  dataset_size: 9979596
+  download_size: 4733144
+  dataset_size: 9979532
+configs:
+- config_name: da_en
+  data_files:
+  - split: train
+    path: da_en/train-*
+  - split: validation
+    path: da_en/validation-*
+  - split: test
+    path: da_en/test-*
+- config_name: lv_en
+  data_files:
+  - split: train
+    path: lv_en/train-*
+  - split: validation
+    path: lv_en/validation-*
+  - split: test
+    path: lv_en/test-*
+- config_name: no_en
+  data_files:
+  - split: train
+    path: no_en/train-*
+  - split: validation
+    path: no_en/validation-*
+  - split: test
+    path: no_en/test-*
+- config_name: zh_en
+  data_files:
+  - split: train
+    path: zh_en/train-*
+  - split: validation
+    path: zh_en/validation-*
+  - split: test
+    path: zh_en/test-*
 ---
 # Dataset Card for "code_x_glue_tt_text_to_text"
 

code_x_glue_tt_text_to_text.py

@@ -1,106 +0,0 @@
-from typing import List
-
-import datasets
-
-from .common import Child
-from .generated_definitions import DEFINITIONS
-
-
-_DESCRIPTION = """The dataset we use is crawled and filtered from Microsoft Documentation, whose document located at https://github.com/MicrosoftDocs/."""
-_CITATION = """@article{DBLP:journals/corr/abs-2102-04664,
-  author    = {Shuai Lu and
-               Daya Guo and
-               Shuo Ren and
-               Junjie Huang and
-               Alexey Svyatkovskiy and
-               Ambrosio Blanco and
-               Colin B. Clement and
-               Dawn Drain and
-               Daxin Jiang and
-               Duyu Tang and
-               Ge Li and
-               Lidong Zhou and
-               Linjun Shou and
-               Long Zhou and
-               Michele Tufano and
-               Ming Gong and
-               Ming Zhou and
-               Nan Duan and
-               Neel Sundaresan and
-               Shao Kun Deng and
-               Shengyu Fu and
-               Shujie Liu},
-  title     = {CodeXGLUE: {A} Machine Learning Benchmark Dataset for Code Understanding
-               and Generation},
-  journal   = {CoRR},
-  volume    = {abs/2102.04664},
-  year      = {2021}
-}"""
-
-
-class CodeXGlueTtTextToTextImpl(Child):
-    _DESCRIPTION = _DESCRIPTION
-    _CITATION = _CITATION
-
-    _FEATURES = {
-        "id": datasets.Value("int32"),  # The index of the sample
-        "source": datasets.Value("string"),  # The source language version of the text
-        "target": datasets.Value("string"),  # The target language version of the text
-    }
-
-    _SUPERVISED_KEYS = ["target"]
-
-    KEYS = ["source", "target"]
-
-    SPLITS = {"train": datasets.Split.TRAIN, "dev": datasets.Split.VALIDATION, "test": datasets.Split.TEST}
-
-    def generate_urls(self, split_name):
-        lang_pair = self.info["parameters"]["natural_language_pair"]
-        for i, lang in enumerate(lang_pair.split("-")):
-            yield self.KEYS[i], f"{split_name}/{lang_pair}.{split_name}.{lang}"
-
-    def _generate_examples(self, split_name, file_paths):
-        # Open each file (one for source language and the other for target language)
-        files = {k: open(file_paths[k], encoding="utf-8") for k in file_paths}
-
-        id_ = 0
-        while True:
-            # Read a single line from each file
-            entries = {k: files[k].readline() for k in file_paths}
-
-            empty = self.check_empty(entries)
-            if empty:
-                # We are done: end of files
-                return
-
-            entries["id"] = id_
-            yield id_, entries
-            id_ += 1
-
-
-CLASS_MAPPING = {
-    "CodeXGlueTtTextToText": CodeXGlueTtTextToTextImpl,
-}
-
-
-class CodeXGlueTtTextToText(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]:
-        return self.child._split_generators(dl_manager=dl_manager)
-
-    def _generate_examples(self, split_name, file_paths):
-        return self.child._generate_examples(split_name, file_paths)

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(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,
-    }

da_en/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
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+oid sha256:bb6c2ae99827b62791401491ea867e1487697fa4e1d95820995c4df5298accfc
+size 112308

da_en/train-00000-of-00001.parquet

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+size 4098744

da_en/validation-00000-of-00001.parquet

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+size 111614

generated_definitions.py

@@ -1,46 +0,0 @@
-DEFINITIONS = {
-    "da_en": {
-        "class_name": "CodeXGlueTtTextToText",
-        "dataset_type": "Text-Text",
-        "description": "CodeXGLUE text-to-text dataset, available at https://github.com/microsoft/CodeXGLUE/tree/main/Text-Text/text-to-text",
-        "dir_name": "text-to-text",
-        "name": "da_en",
-        "parameters": {"natural_language_pair": "da-en"},
-        "project_url": "https://github.com/madlag/CodeXGLUE/tree/main/Text-Text/text-to-text",
-        "raw_url": "https://raw.githubusercontent.com/madlag/CodeXGLUE/main/Text-Text/text-to-text/data",
-        "sizes": {"test": 1000, "train": 42701, "validation": 1000},
-    },
-    "lv_en": {
-        "class_name": "CodeXGlueTtTextToText",
-        "dataset_type": "Text-Text",
-        "description": "CodeXGLUE text-to-text dataset, available at https://github.com/microsoft/CodeXGLUE/tree/main/Text-Text/text-to-text",
-        "dir_name": "text-to-text",
-        "name": "lv_en",
-        "parameters": {"natural_language_pair": "lv-en"},
-        "project_url": "https://github.com/madlag/CodeXGLUE/tree/main/Text-Text/text-to-text",
-        "raw_url": "https://raw.githubusercontent.com/madlag/CodeXGLUE/main/Text-Text/text-to-text/data",
-        "sizes": {"test": 1000, "train": 18749, "validation": 1000},
-    },
-    "no_en": {
-        "class_name": "CodeXGlueTtTextToText",
-        "dataset_type": "Text-Text",
-        "description": "CodeXGLUE text-to-text dataset, available at https://github.com/microsoft/CodeXGLUE/tree/main/Text-Text/text-to-text",
-        "dir_name": "text-to-text",
-        "name": "no_en",
-        "parameters": {"natural_language_pair": "no-en"},
-        "project_url": "https://github.com/madlag/CodeXGLUE/tree/main/Text-Text/text-to-text",
-        "raw_url": "https://raw.githubusercontent.com/madlag/CodeXGLUE/main/Text-Text/text-to-text/data",
-        "sizes": {"test": 1000, "train": 44322, "validation": 1000},
-    },
-    "zh_en": {
-        "class_name": "CodeXGlueTtTextToText",
-        "dataset_type": "Text-Text",
-        "description": "CodeXGLUE text-to-text dataset, available at https://github.com/microsoft/CodeXGLUE/tree/main/Text-Text/text-to-text",
-        "dir_name": "text-to-text",
-        "name": "zh_en",
-        "parameters": {"natural_language_pair": "zh-en"},
-        "project_url": "https://github.com/madlag/CodeXGLUE/tree/main/Text-Text/text-to-text",
-        "raw_url": "https://raw.githubusercontent.com/madlag/CodeXGLUE/main/Text-Text/text-to-text/data",
-        "sizes": {"test": 1000, "train": 50154, "validation": 1000},
-    },
-}

lv_en/test-00000-of-00001.parquet

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lv_en/train-00000-of-00001.parquet

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lv_en/validation-00000-of-00001.parquet

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no_en/test-00000-of-00001.parquet

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no_en/train-00000-of-00001.parquet

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zh_en/test-00000-of-00001.parquet

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zh_en/train-00000-of-00001.parquet

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