feat: Add deepstarr dataset

nucleotide_transformer_downstream_tasks_multilabel.py

@@ -41,15 +41,13 @@ _HOMEPAGE = "https://github.com/instadeepai/nucleotide-transformer"
 
 _LICENSE = "https://github.com/instadeepai/nucleotide-transformer/LICENSE.md"
 
-_TASKS = [
-    "deepstarr",
-]
+_TASKS = [("deepstarr", 6)]
 
 
 class NucleotideTransformerDownstreamTasksConfig(datasets.BuilderConfig):
     """BuilderConfig for The Nucleotide Transformer downstream taks dataset."""
 
-    def __init__(self, *args, task: str, **kwargs):
+    def __init__(self, *args, task: str, num_labels=int, **kwargs):
         """BuilderConfig downstream tasks dataset.
         Args:
             task (:obj:`str`): Task name.
@@ -61,30 +59,29 @@ class NucleotideTransformerDownstreamTasksConfig(datasets.BuilderConfig):
             **kwargs,
         )
         self.task = task
+        self.num_labels = num_labels
 
 
 class NucleotideTransformerDownstreamTasks(datasets.GeneratorBasedBuilder):
     VERSION = datasets.Version("1.1.0")
     BUILDER_CONFIG_CLASS = NucleotideTransformerDownstreamTasksConfig
     BUILDER_CONFIGS = [
-        NucleotideTransformerDownstreamTasksConfig(task=task) for task in _TASKS
+        NucleotideTransformerDownstreamTasksConfig(task=task, num_labels=num_labels)
+        for (task, num_labels) in _TASKS
     ]
     DEFAULT_CONFIG_NAME = "deepstarr"
 
     def _info(self):
+        features_dict = {
+            "sequence": datasets.Value("string"),
+            "name": datasets.Value("string"),
+        }
+        labels_dict = {
+            f"label_{i}": datasets.Value("float32")
+            for i in range(self.config.num_labels)
+        }
+        features = datasets.Features(dict(features_dict.items() + labels_dict.items()))
 
-        features = datasets.Features(
-            {
-                "sequence": datasets.Value("string"),
-                "name": datasets.Value("string"),
-                "label_0": datasets.Value("float32"),
-                "label_1": datasets.Value("float32"),
-                "label_2": datasets.Value("float32"),
-                "label_3": datasets.Value("float32"),
-                "label_4": datasets.Value("float32"),
-                "label_5": datasets.Value("float32"),
-            }
-        )
         return datasets.DatasetInfo(
             # This is the description that will appear on the datasets page.
             description=_DESCRIPTION,
@@ -101,7 +98,6 @@ class NucleotideTransformerDownstreamTasks(datasets.GeneratorBasedBuilder):
     def _split_generators(
         self, dl_manager: datasets.DownloadManager
     ) -> List[datasets.SplitGenerator]:
-
         train_file = dl_manager.download_and_extract(self.config.task + "/train.fna")
         test_file = dl_manager.download_and_extract(self.config.task + "/test.fna")
 
@@ -126,15 +122,15 @@ class NucleotideTransformerDownstreamTasks(datasets.GeneratorBasedBuilder):
                 sequence, name = str(record.seq), str(record.name)
                 labels = [float(label) for label in name.split("|")[1:]]
 
-                # yield example
-                yield key, {
+                sequence_name_dict = {
                     "sequence": sequence,
                     "name": name,
-                    "label_0": labels[0],
-                    "label_1": labels[1],
-                    "label_2": labels[2],
-                    "label_3": labels[3],
-                    "label_4": labels[4],
-                    "label_5": labels[5],
                 }
+
+                labels_dict = {
+                    f"label_{i}": labels[i] for i in range(self.config.num_labels)
+                }
+                final_dict = dict(sequence_name_dict.items() + labels_dict.items())
+                # yield example
+                yield key, final_dict
                 key += 1