Upload GUE.py

GUE.py

@@ -0,0 +1,107 @@
+"""Script for the dataset containing the 28 downstream tasks from the DNABertv2 paper."""
+
+from typing import List
+import csv
+import datasets
+
+
+# This function is a basic reimplementation of SeqIO's parse method. This allows the
+# dataset viewer to work as it does not require an external package.
+
+# Find for instance the citation on arxiv or on the dataset repo/website
+_CITATION = ''
+
+# You can copy an official description
+_DESCRIPTION = ''
+
+_HOMEPAGE = ""
+
+_LICENSE = ""
+
+_TASKS = [
+    "splice/reconstructed",
+    "mouse/0",
+    "mouse/1"
+]
+
+
+class GUEConfig(datasets.BuilderConfig):
+    """BuilderConfig for GUE taks dataset."""
+
+    def __init__(self, *args, task: str, **kwargs):
+        """BuilderConfig downstream tasks dataset.
+        Args:
+            task (:obj:`str`): Task name.
+            **kwargs: keyword arguments forwarded to super.
+        """
+        super().__init__(
+            *args,
+            name=f"{task}",
+            **kwargs,
+        )
+        self.task = task
+
+
+class GUEDownstreamTasks(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("1.1.0")
+    BUILDER_CONFIG_CLASS = GUEConfig
+    BUILDER_CONFIGS = [
+        GUEConfig(task=task) for task in _TASKS
+    ]
+    DEFAULT_CONFIG_NAME = "reconstructed"
+
+    def _info(self):
+
+        features = datasets.Features(
+            {
+                "sequence": datasets.Value("string"),
+                "label": datasets.Value("int32"),
+            }
+        )
+        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,
+            # Homepage of the dataset for documentation
+            homepage=_HOMEPAGE,
+            # License for the dataset if available
+            license=_LICENSE,
+            # Citation for the dataset
+            citation=_CITATION,
+        )
+
+    def _split_generators(
+        self, dl_manager: datasets.DownloadManager
+    ) -> List[datasets.SplitGenerator]:
+
+        train_file = dl_manager.download_and_extract(self.config.task + "/train.csv")
+        valid_file = dl_manager.download_and_extract(self.config.task + "/dev.csv")
+        test_file = dl_manager.download_and_extract(self.config.task + "/test.csv")
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN, gen_kwargs={"file": train_file}
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION, gen_kwargs={"file": valid_file}
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST, gen_kwargs={"file": test_file}
+            ),
+        ]
+
+    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
+    def _generate_examples(self, file):
+        key = 0
+        with open(file, "rt") as f:
+            csv_reader = csv.reader(f)
+            head = next(csv_reader)
+            for sequence, label in csv_reader:
+                # yield example
+                yield key, {
+                    "sequence": sequence,
+                    "label": label,
+                }
+                key += 1
+