Update time_series_library.py

time_series_library.py

@@ -24,28 +24,36 @@ class TimeSeriesLibrary(GeneratorBasedBuilder):
 
     def _split_generators(self, dl_manager):
         dfiles = self.config.data_files
-        files = dfiles if isinstance(dfiles, (list, tuple)) else [dfiles]
+        files = list(dfiles) if isinstance(dfiles, (list, tuple)) else [dfiles]
     
-        def pick(keys):
-            for k in keys:
-                for f in files:
-                    name = os.path.basename(str(f)).lower()
-                    if k in name:
-                        return f
+        def find_and_pop(keys):
+            keys = [k.lower() for k in keys]
+            for i, f in enumerate(files):
+                name = os.path.basename(str(f)).lower()
+                if any(k in name for k in keys):
+                    return files.pop(i)
             return None
     
-        train_f = pick(["train"])
-        test_f  = pick(["test"])
-        val_f   = pick(["val", "valid", "validation"])
+        train_f = find_and_pop(["train"])
+        val_f   = find_and_pop(["val", "valid", "validation"])
+        test_f  = find_and_pop(["test"])
+        label_f = find_and_pop(["test_label", "label", "labels"])
     
-        if train_f or test_f or val_f:
-            gens = []
-            if train_f: gens.append(SplitGenerator(Split.TRAIN, {"filepath": train_f}))
-            if val_f:   gens.append(SplitGenerator(Split.VALIDATION, {"filepath": val_f}))
-            if test_f:  gens.append(SplitGenerator(Split.TEST, {"filepath": test_f}))
-            return gens
+        gens = []
+        if train_f:
+            gens.append(SplitGenerator(name=Split.TRAIN, gen_kwargs={"filepath": train_f}))
+        if val_f:
+            gens.append(SplitGenerator(name=Split.VALIDATION, gen_kwargs={"filepath": val_f}))
+        if test_f:
+            gens.append(SplitGenerator(name=Split.TEST, gen_kwargs={"filepath": test_f}))
+        if label_f:
+            gens.append(SplitGenerator(name="test_label", gen_kwargs={"filepath": label_f}))
+    
+        if not gens:
+            gens = [SplitGenerator(name=Split.TRAIN, gen_kwargs={"filepath": files})]
+    
+        return gens
     
-        return [SplitGenerator(Split.TRAIN, {"filepath": files})]
 
     def _generate_examples(self, filepath, row_slice=None):
         if isinstance(filepath, (list, tuple)):