Creating custom loading script.

README.md

@@ -6,19 +6,6 @@ language:
 - pt
 size_categories:
 - 1M<n<10M
-configs:
-- config_name: quati_10M_passages
-  data_files: quati_10M_part_*.tsv
-  sep: "\t"
-- config_name: quati_1M_passages
-  data_files: quati_1M.tsv
-  sep: "\t"
-- config_name: topics
-  data_files: topics/*.tsv
-  sep: "\t"
-- config_name: qrels
-  data_files: qrels/*
-  sep: " "
 ---
 
 # Quati Information Retrieval Dataset

quati.py

@@ -0,0 +1,202 @@
+# coding=utf-8
+# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
+#
+# 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
+"""Quati dataset."""
+
+import datasets
+
+
+_CITATION = """
+place holder
+"""
+
+_URL = "https://github.com/unicamp-dl/quati"
+
+_DESCRIPTION = """
+Quati ― Portuguese Native Information Retrieval dataset.
+"""
+
+
+
+QUATI_10M_DATASET_PARTS=["part_00", "part_01", "part_02", "part_03", "part_04"]
+
+
+
+_URLS = {
+    "quati_1M_passages": "https://huggingface.co/datasets/unicamp-dl/quati/resolve/main/quati_1M_passages.tsv",
+    "quati_10M_passages_part_00": "https://huggingface.co/datasets/unicamp-dl/quati/resolve/main/quati_10M_part_00.tsv",
+    "quati_10M_passages_part_01": "https://huggingface.co/datasets/unicamp-dl/quati/resolve/main/quati_10M_part_01.tsv",
+    "quati_10M_passages_part_02": "https://huggingface.co/datasets/unicamp-dl/quati/resolve/main/quati_10M_part_02.tsv",
+    "quati_10M_passages_part_03": "https://huggingface.co/datasets/unicamp-dl/quati/resolve/main/quati_10M_part_03.tsv",
+    "quati_10M_passages_part_04": "https://huggingface.co/datasets/unicamp-dl/quati/resolve/main/quati_10M_part_04.tsv",
+    "quati_1M_qrels": "https://huggingface.co/datasets/unicamp-dl/quati/resolve/main/qrels/quati_1M_qrels.txt",
+    "quati_10M_qrels": "https://huggingface.co/datasets/unicamp-dl/quati/resolve/main/qrels/quati_10M_qrels.txt",
+    "quati_test_topics": "https://huggingface.co/datasets/unicamp-dl/quati/resolve/main/topics/quati_test_topics.txt",
+    "quati_all_topics": "https://huggingface.co/datasets/unicamp-dl/quati/resolve/main/topics/quati_all_topics.txt"
+}
+
+
+
+def generate_examples_passages(filepath):
+
+    with open(filepath, encoding="utf-8") as input_file:
+        for (idx, line) in enumerate(input_file):
+            
+            passage_id, passage = line.rstrip().split("\t")
+            
+            features = {"passage_id": passage_id,
+                        "passage": passage}
+
+            yield idx, features
+
+
+
+def generate_examples_qrels(filepath):
+
+    with open(filepath, encoding="utf-8") as input_file:
+        for (idx, line) in enumerate(input_file):
+            query_id, _, passage_id, score = line.rstrip().split(" ")
+
+            features = {"query_id": int(query_id),
+                        "passage_id": passage_id,
+                        "score": int(score)}
+
+            yield idx, features
+
+
+def generate_examples_topics(filepath):
+
+    with open(filepath, encoding="utf-8") as input_file:
+        for (idx, line) in enumerate(input_file):
+            query_id, query = line.rstrip().split("\t")
+
+            features = {"query_id": int(query_id),
+                        "query": query}
+
+            yield idx, features
+
+
+
+class Quati(datasets.GeneratorBasedBuilder):
+
+    BUILDER_CONFIGS = (
+        [
+            datasets.BuilderConfig(
+                name="quati_10M_passages",
+                description="Portugues Brazilian passages, composing the complete Quati 10M dataset.",
+                version=datasets.Version("1.0.0"),
+            ),
+
+            datasets.BuilderConfig(
+                name="quati_1M_passages",
+                description="Portugues Brazilian passages, composing the Quati 1M dataset.",
+                version=datasets.Version("1.0.0"),
+            ),
+
+            datasets.BuilderConfig(
+                name="quati_10M_qrels",
+                description="Qrels for the annotated passages from the Quati 10M dataset.",
+                version=datasets.Version("1.0.0"),
+            ),
+
+            datasets.BuilderConfig(
+                name="quati_1M_qrels",
+                description="Qrels for the annotated passages from the Quati 1M dataset.",
+                version=datasets.Version("1.0.0"),
+            ),
+
+            datasets.BuilderConfig(
+                name="quati_test_topics",
+                description="50 test topics, corresponding to Quati dataset qrels.",
+                version=datasets.Version("1.0.0"),
+            ),
+
+            datasets.BuilderConfig(
+                name="quati_all_topics",
+                description="All 200 topics created for the Quati dataset, including the 50 ones corresponding to Quati dataset qrels.",
+                version=datasets.Version("1.0.0"),
+            )
+        ]
+        + [
+            datasets.BuilderConfig(
+                name="quati_10M_passages_{}".format(which_part),
+                description="Portugues Brazilian passages, composing the Quati 10M dataset {}.".format(which_part),
+                version=datasets.Version("1.0.0"),
+            )
+            for which_part in QUATI_10M_DATASET_PARTS
+        ]
+    )
+
+    DEFAULT_CONFIG_NAME = "quati_1M_passages"
+
+
+    def _info(self):
+        name = self.config.name
+        if "passages" in name:
+            features = {
+                "passage_id": datasets.Value("string"),
+                "passage": datasets.Value("string"),
+            }
+        elif name.endswith("qrels"):
+            features = {
+                "query_id": datasets.Value("int32"),
+                "passage_id": datasets.Value("string"),
+                "score": datasets.Value("int32"),
+            }
+        else:
+            features = {
+                "query_id": datasets.Value("int32"),
+                "query": datasets.Value("string"),
+            }
+
+        return datasets.DatasetInfo(
+            description=f"{_DESCRIPTION}\n{self.config.description}",
+            features=datasets.Features(features),
+            supervised_keys=None,
+            homepage=_URL,
+            citation=_CITATION,
+        )
+
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+
+        if self.config.name == "quati_10M_passages":
+
+            urls = {which_part: _URLS["quati_10M_passages_{}".format(which_part)] for which_part in QUATI_10M_DATASET_PARTS}
+
+            dl_path = dl_manager.download_and_extract(urls)
+
+            return [datasets.SplitGenerator(name="quati_10M_passages_{}".format(which_part), gen_kwargs={"filepath": dl_path[which_part]}) for which_part in QUATI_10M_DATASET_PARTS]
+
+        else:
+            url = _URLS[self.config.name]
+            dl_path = dl_manager.download_and_extract(url)
+
+            return (datasets.SplitGenerator(name=self.config.name, gen_kwargs={"filepath": dl_path}),)
+
+
+    def _generate_examples(self, filepath, args=None):
+        """Yields examples."""
+
+        if "passages" in self.config.name:
+            return generate_examples_passages(filepath)
+        
+        if self.config.name.endswith("qrels"):
+            return generate_examples_qrels(filepath)
+        
+        else:
+            return generate_examples_topics(filepath)