Update app.py

app.py

@@ -21,6 +21,21 @@ tokenizer = AutoTokenizer.from_pretrained(llm_model)
 
 #import numpy as np
 
+datasetiter = load_dataset("Namitg02/Test", split='train', streaming=False)
+
+def is_iterable_dataset(datasetiter):
+  return isinstance(datasetiter, torch.utils.data.IterableDataset)
+
+def is_map_style_dataset(datasetiter):
+  return isinstance(datasetiter, torch.utils.data.Dataset)
+
+if is_iterable_dataset(datasetiter):
+  print("The dataset is iterable-style.")
+else:
+  print("The dataset is map-style.")
+
+
+
 from torch.utils.data import Dataset, IterableDataset
 
 class MyIterableDataset(IterableDataset):
@@ -42,8 +57,9 @@ class MapStyleDataset(Dataset):
     def __getitem__(self, idx):
         return self.data[idx]
 
+
 # Create an iterable
-iterable = "Namitg02/Test"
+#iterable = "Namitg02/Test"
 
 # Convert the iterable to a MapStyle dataset
 map_style_dataset = MapStyleDataset(iterable)
@@ -51,16 +67,6 @@ map_style_dataset = MapStyleDataset(iterable)
 # Create a DataLoader for the MapStyle dataset
 data_loader = torch.utils.data.DataLoader(map_style_dataset, batch_size=2)
 
-def is_iterable_dataset(map_style_dataset):
-  return isinstance(map_style_dataset, torch.utils.data.IterableDataset)
-
-def is_map_style_dataset(map_style_dataset):
-  return isinstance(map_style_dataset, torch.utils.data.Dataset)
-
-if is_iterable_dataset(map_style_dataset):
-  print("The dataset is iterable-style.")
-else:
-  print("The dataset is map-style.")