feat: try other way for labels

nucleotide_transformer_downstream_tasks_multilabel.py

@@ -44,19 +44,17 @@ _LICENSE = "https://github.com/instadeepai/nucleotide-transformer/LICENSE.md"
 # The toy_classification and toy_regression are two manually created configurations
 # with 5 samples in both the train and test fasta files. It is notably used in order to
 # test the scripts.
-_TASKS_NUM_LABELS_DTYPE = [
-    ("deepstarr", 6, "float32"),
-    ("toy_classification", 2, "int32"),
-    ("toy_regression", 2, "float32"),
+_TASKS_DTYPE = [
+    ("deepstarr", "float32"),
+    ("toy_classification", "int32"),
+    ("toy_regression", "float32"),
 ]
 
 
 class NucleotideTransformerDownstreamTasksConfig(datasets.BuilderConfig):
     """BuilderConfig for The Nucleotide Transformer downstream taks dataset."""
 
-    def __init__(
-        self, *args, task: str, num_labels=int, dtype: str = "int32", **kwargs
-    ):
+    def __init__(self, *args, task: str, dtype: str = "int32", **kwargs):
         """BuilderConfig downstream tasks dataset.
         Args:
             task (:obj:`str`): Task name.
@@ -68,7 +66,6 @@ class NucleotideTransformerDownstreamTasksConfig(datasets.BuilderConfig):
             **kwargs,
         )
         self.task = task
-        self.num_labels = num_labels
         self.dtype = dtype
 
 
@@ -76,24 +73,18 @@ class NucleotideTransformerDownstreamTasks(datasets.GeneratorBasedBuilder):
     VERSION = datasets.Version("1.1.0")
     BUILDER_CONFIG_CLASS = NucleotideTransformerDownstreamTasksConfig
     BUILDER_CONFIGS = [
-        NucleotideTransformerDownstreamTasksConfig(
-            task=task, num_labels=num_labels, dtype=dtype
-        )
-        for (task, num_labels, dtype) in _TASKS_NUM_LABELS_DTYPE
+        NucleotideTransformerDownstreamTasksConfig(task=task, dtype=dtype)
+        for (task, dtype) in _TASKS_DTYPE
     ]
     DEFAULT_CONFIG_NAME = "deepstarr"
 
     def _info(self):
-        features_dict = {
+
+        features = {
             "sequence": datasets.Value("string"),
             "name": datasets.Value("string"),
+            "labels": datasets.Sequence("int32"),
         }
-        labels_dict = {
-            f"label_{i}": datasets.Value(self.config.dtype)
-            for i in range(self.config.num_labels)
-        }
-        features_dict.update(labels_dict)
-        features = datasets.Features(features_dict)
 
         return datasets.DatasetInfo(
             # This is the description that will appear on the datasets page.
@@ -135,15 +126,10 @@ class NucleotideTransformerDownstreamTasks(datasets.GeneratorBasedBuilder):
                 sequence, name = str(record.seq), str(record.name)
                 labels = [float(label) for label in name.split("|")[1:]]
 
-                sequence_name_dict = {
+                # yield example
+                yield key, {
                     "sequence": sequence,
                     "name": name,
+                    "labels": labels,
                 }
-
-                labels_dict = {
-                    f"label_{i}": labels[i] for i in range(self.config.num_labels)
-                }
-                sequence_name_dict.update(labels_dict)
-                # yield example
-                yield key, sequence_name_dict
                 key += 1