feat: revert to working version

nucleotide_transformer_downstream_tasks_multilabel.py

@@ -44,17 +44,19 @@ _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_DTYPE = [
-    ("deepstarr", "float32"),
-    ("toy_classification", "int32"),
-    ("toy_regression", "float32"),
+_TASKS_NUM_LABELS_DTYPE = [
+    ("deepstarr", 6, "float32"),
+    ("toy_classification", 2, "int32"),
+    ("toy_regression", 2, "float32"),
 ]
 
 
 class NucleotideTransformerDownstreamTasksConfig(datasets.BuilderConfig):
     """BuilderConfig for The Nucleotide Transformer downstream taks dataset."""
 
-    def __init__(self, *args, task: str, dtype: str = "int32", **kwargs):
+    def __init__(
+        self, *args, task: str, num_labels=int, dtype: str = "int32", **kwargs
+    ):
         """BuilderConfig downstream tasks dataset.
         Args:
             task (:obj:`str`): Task name.
@@ -66,6 +68,7 @@ class NucleotideTransformerDownstreamTasksConfig(datasets.BuilderConfig):
             **kwargs,
         )
         self.task = task
+        self.num_labels = num_labels
         self.dtype = dtype
 
 
@@ -73,18 +76,24 @@ class NucleotideTransformerDownstreamTasks(datasets.GeneratorBasedBuilder):
     VERSION = datasets.Version("1.1.0")
     BUILDER_CONFIG_CLASS = NucleotideTransformerDownstreamTasksConfig
     BUILDER_CONFIGS = [
-        NucleotideTransformerDownstreamTasksConfig(task=task, dtype=dtype)
-        for (task, dtype) in _TASKS_DTYPE
+        NucleotideTransformerDownstreamTasksConfig(
+            task=task, num_labels=num_labels, dtype=dtype
+        )
+        for (task, num_labels, dtype) in _TASKS_NUM_LABELS_DTYPE
     ]
     DEFAULT_CONFIG_NAME = "deepstarr"
 
     def _info(self):
-
-        features = {
+        features_dict = {
             "sequence": datasets.Value("string"),
             "name": datasets.Value("string"),
-            # "labels": datasets.Sequence(self.config.dtype),
         }
+        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.
@@ -126,10 +135,15 @@ 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,
-                    # "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