Update fiqa_pt.py

fiqa_pt.py

@@ -1,43 +1,68 @@
-import json
 import csv
+import json
 import os
+
 import datasets
 
-logger = datasets.logging.get_logger(__name__)
+_DESCRIPTION = """\
+FIQA translated dataset to portuguese
+"""
+
+_URLS = {
+    "corpus": "https://huggingface.co/datasets/leonardo-avila/fiqa_pt/blob/main/corpus_pt.tsv",
+    "topics": "https://huggingface.co/datasets/leonardo-avila/fiqa_pt/blob/main/topics_pt.tsv",
+    "qrel": "https://huggingface.co/qrel.tsv",
+}
 
-_DESCRIPTION = "FIQA translated dataset"
-_SPLITS = ["corpus", "topics"]
 
-URL = ""
-_URLs = {subset: URL + f"{subset}_pt.tsv" for subset in _SPLITS}
+# TODO: Name of the dataset usually matches the script name with CamelCase instead of snake_case
+class BeirPT(datasets.GeneratorBasedBuilder):
+    """BEIR BenchmarkDataset."""
 
-class BEIR_PT(datasets.GeneratorBasedBuilder):
-    """BEIR-PT BenchmarkDataset."""
+    VERSION = datasets.Version("1.1.0")
 
+    # You will be able to load one or the other configurations in the following list with
+    # data = datasets.load_dataset('my_dataset', 'first_domain')
+    # data = datasets.load_dataset('my_dataset', 'second_domain')
     BUILDER_CONFIGS = [
-        datasets.BuilderConfig(
-            name=name,
-            description=f"This is the {name} in the FiQA-PT dataset.",
-        ) for name in _SPLITS
+        datasets.BuilderConfig(name="corpus", version=VERSION, description="Load corpus"),
+        datasets.BuilderConfig(name="topics", version=VERSION, description="Load topics"),
+        datasets.BuilderConfig(name="qrel", version=VERSION, description="Load qrel"),
     ]
-    
+
+    DEFAULT_CONFIG_NAME = "corpus"  # It's not mandatory to have a default configuration. Just use one if it make sense.
+
     def _info(self):
 
+        if self.config.name in ["corpus", "topics"]:
+            features = datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "text": datasets.Value("string"),
+                }
+            )
+        else:  # This is an example to show how to have different features for "first_domain" and "second_domain"
+            features = datasets.Features(
+                {
+                    "query_id": datasets.Value("string"),
+                    "doc_id": datasets.Value("string"),
+                    "rel": datasets.Value("string"),
+                }
+            )
         return datasets.DatasetInfo(
             description=_DESCRIPTION,
-             features=datasets.Features({
-                "_id": datasets.Value("string"),
-                "text": datasets.Value("string"),
-             }),
-            supervised_keys=None,
+            features=features
         )
 
     def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-
-        my_urls = _URLs[self.config.name]
-        data_dir = dl_manager.download_and_extract(my_urls)
+        # TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration
+        # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name
 
+        # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS
+        # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
+        # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
+        urls = _URLS[self.config.name]
+        data_dir = dl_manager.download_and_extract(urls)
         return [
             datasets.SplitGenerator(
                 name=self.config.name,
@@ -46,11 +71,20 @@ class BEIR_PT(datasets.GeneratorBasedBuilder):
             ),
         ]
 
-    def _generate_examples(self, filepath):
-        """Yields examples."""
+    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
+    def _generate_examples(self, filepath, split):
         with open(filepath, encoding="utf-8") as f:
-            for line in f:
-                fields = line.strip().split("\t")
-                idx = fields[0]
-                text = fields[1]
-                yield idx, text
+            if self.config.name in ["corpus", "topics"]:
+                for line in f:
+                    fields = line.strip().split("\t")
+                    idx = fields[0]
+                    text = fields[1]
+                    yield idx, text
+            else:
+                for line in f:
+                    if "query-id" not in line:
+                        fields = line.strip().split("\t")
+                            query_id = fields[0]
+                            doc_id = fields[1]
+                            rel = int(fields[2])
+                            yield query_id, doc_id, rel