Convert dataset to Parquet

README.md

@@ -0,0 +1,40 @@
+---
+dataset_info:
+  features:
+  - name: query_id
+    dtype: string
+  - name: query
+    dtype: string
+  - name: positive_passages
+    list:
+    - name: docid
+      dtype: string
+    - name: text
+      dtype: string
+    - name: title
+      dtype: string
+  - name: negative_passages
+    list:
+    - name: docid
+      dtype: string
+    - name: text
+      dtype: string
+    - name: title
+      dtype: string
+  splits:
+  - name: train
+    num_bytes: 29193126
+    num_examples: 3292
+  - name: dev
+    num_bytes: 7114857
+    num_examples: 860
+  download_size: 21188455
+  dataset_size: 36307983
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+  - split: dev
+    path: data/dev-*
+---

create_miracl_japanese_small.py

@@ -1,16 +0,0 @@
-import json
-from tqdm import tqdm
-from datasets import load_dataset
-
-OUTPUT_FILEPATHS = {
-    "train": "./topics.miracl-v1.0-ja-train.jsonl",
-    "dev": "./topics.miracl-v1.0-ja-dev.jsonl"
-}
-
-if __name__ == '__main__':
-    dataset = load_dataset("miracl/miracl", "ja")
-    for split in OUTPUT_FILEPATHS:
-        with open(OUTPUT_FILEPATHS[split], 'w', encoding='utf-8') as f:
-            for data in tqdm(dataset[split]):
-                if not split == 'train' or len(data['negative_passages']) > 0:
-                    f.write(json.dumps(data) + '\n')

topics.miracl-v1.0-ja-dev.jsonl.gz → data/dev-00000-of-00001.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:27c571e461fccd9b90b7abe69c2d04b7d9de3d25bbc80cc92327ec076e17c786
-size 3027623
+oid sha256:475a231ea2ddc7a5ed4af25f2e1dd789b9330ec7cc08caa2a89e62b529530eb8
+size 4135567

topics.miracl-v1.0-ja-train.jsonl.gz → data/train-00000-of-00001.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:a6124e784fd0ffdffcf1689d5090dc6961a8be889791bc04ec438aafcaf58276
-size 12469053
+oid sha256:d088f9e33dd3fbc936400abc39a5fd4f2f9c50b00fbc58838b108a5eb71f6039
+size 17052888

miracl-japanese-small.py

@@ -1,95 +0,0 @@
-# coding=utf-8
-# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-# Lint as: python3
-
-import json
-import datasets
-
-_CITATION = """
-"""
-
-_DESCRIPTION = "dataset load script for MIRACL Japanese Small"
-
-_DATASET_URLS = {
-    'train': 'https://huggingface.co/datasets/mpkato/miracl-japanese-small/resolve/main/topics.miracl-v1.0-ja-train.jsonl.gz',
-    'dev': 'https://huggingface.co/datasets/mpkato/miracl-japanese-small/resolve/main/topics.miracl-v1.0-ja-dev.jsonl.gz',
-}
-
-
-class MIRACLJapaneseSmall(datasets.GeneratorBasedBuilder):
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(
-            version=datasets.Version('1.0.0'),
-            description=f'MIRACL Japanese Small dataset.'
-        )
-    ]
-
-    def _info(self):
-        features = datasets.Features({
-            'query_id': datasets.Value('string'),
-            'query': datasets.Value('string'),
-            'positive_passages': [
-                {'docid': datasets.Value('string'), 'text': datasets.Value('string'),
-                 'title': datasets.Value('string')}
-            ],
-            'negative_passages': [
-                {'docid': datasets.Value('string'), 'text': datasets.Value('string'),
-                 'title': datasets.Value('string')}
-            ],
-        })
-
-        return datasets.DatasetInfo(
-            # This is the description that will appear on the datasets page.
-            description=_DESCRIPTION,
-            # This defines the different columns of the dataset and their types
-            features=features,  # Here we define them above because they are different between the two configurations
-            supervised_keys=None,
-            # Homepage of the dataset for documentation
-            homepage="",
-            # License for the dataset if available
-            license="",
-            # Citation for the dataset
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        downloaded_files = dl_manager.download_and_extract(_DATASET_URLS)
-        splits = [
-            datasets.SplitGenerator(
-                name="train",
-                gen_kwargs={
-                    "filepath": downloaded_files["train"],
-                },
-            ),
-            datasets.SplitGenerator(
-                name='dev',
-                gen_kwargs={
-                    "filepath": downloaded_files["dev"],
-                },
-            ),
-        ]
-        return splits
-
-    def _generate_examples(self, filepath):
-        """Yields examples."""
-        with open(filepath, encoding="utf-8") as f:
-            for line in f:
-                data = json.loads(line)
-                if data.get('negative_passages') is None:
-                    data['negative_passages'] = []
-                if data.get('positive_passages') is None:
-                    data['positive_passages'] = []
-                yield data['query_id'], data