feat: Add the rest of the downstream tasks

H3/test.fna

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H3/train.fna

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H3K14ac/test.fna

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H3K79me3/test.fna

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H3K79me3/train.fna

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H3K9ac/test.fna

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H4ac/test.fna

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H4ac/train.fna

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enhancers/test.fna

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enhancers/train.fna

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nucleotide_transformer_downstream_tasks.py

@@ -16,6 +16,7 @@
 Transformer paper."""
 
 from typing import List
+
 import datasets
 from Bio import SeqIO
 
@@ -42,8 +43,24 @@ _HOMEPAGE = "https://github.com/instadeepai/nucleotide-transformer"
 _LICENSE = "https://github.com/instadeepai/nucleotide-transformer/LICENSE.md"
 
 _TASKS = [
-    'enhancers_types',
-    'promoter_all'
+    "H4ac",
+    "H3K36me3",
+    "splice_sites_donors",
+    "splice_sites_acceptors",
+    "H3",
+    "H4",
+    "H3K4me3",
+    "splice_sites_all",
+    "H3K4me1",
+    "H3K14ac",
+    "enhancers_types",
+    "promoter_no_tata",
+    "H3K79me3",
+    "H3K4me2",
+    "promoter_tata",
+    "enhancers",
+    "H3K9ac",
+    "promoter_all",
 ]
 
 
@@ -58,7 +75,7 @@ class NucleotideTransformerDownstreamTasksConfig(datasets.BuilderConfig):
         """
         super().__init__(
             *args,
-            name=f'{task}',
+            name=f"{task}",
             **kwargs,
         )
         self.task = task
@@ -94,25 +111,27 @@ class NucleotideTransformerDownstreamTasks(datasets.GeneratorBasedBuilder):
             citation=_CITATION,
         )
 
-    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
+    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')
+        train_file = dl_manager.download_and_extract(self.config.task + "/train.fna")
+        test_file = dl_manager.download_and_extract(self.config.task + "/test.fna")
 
         return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN,
-                                    gen_kwargs={"file": train_file}
-                                    ),
-            datasets.SplitGenerator(name=datasets.Split.TEST,
-                                    gen_kwargs={"file": test_file}
-                                    ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN, gen_kwargs={"file": train_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:
-            fasta_sequences = SeqIO.parse(f, 'fasta')
+        with open(file, "rt") as f:
+            fasta_sequences = SeqIO.parse(f, "fasta")
 
             for record in fasta_sequences:
 
@@ -122,8 +141,8 @@ class NucleotideTransformerDownstreamTasks(datasets.GeneratorBasedBuilder):
 
                 # yield example
                 yield key, {
-                    'sequence': sequence,
-                    'name': name,
-                    'label': label,
+                    "sequence": sequence,
+                    "name": name,
+                    "label": label,
                 }
-                key += 1
+                key += 1

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