[example] update opt example using booster api (#3918)

examples/language/opt/data.py

@@ -0,0 +1,37 @@
+import torch
+from torch.utils.data import Dataset
+from datasets import load_dataset
+
+
+class NetflixDataset(Dataset):
+    
+    def __init__(self, tokenizer):
+
+        super().__init__()
+
+        self.tokenizer = tokenizer
+        self.input_ids = []
+        self.attn_masks = []
+        self.labels = []
+        self.txt_list = netflix_descriptions = load_dataset("hugginglearners/netflix-shows", split="train")['description']
+        self.max_length = max([len(self.tokenizer.encode(description)) for description in netflix_descriptions])
+
+        for txt in self.txt_list:
+            encodings_dict = self.tokenizer('</s>' + txt + '</s>',
+                                        truncation=True,
+                                        max_length=self.max_length, 
+                                        padding="max_length")
+            self.input_ids.append(torch.tensor(encodings_dict['input_ids']))
+            self.attn_masks.append(torch.tensor(encodings_dict['attention_mask']))
+
+    def __len__(self):
+        return len(self.input_ids)
+
+    def __getitem__(self, idx):
+        return self.input_ids[idx], self.attn_masks[idx]
+    
+
+def netflix_collator(data):
+    return {'input_ids': torch.stack([x[0] for x in data]),       
+            'attention_mask': torch.stack([x[1] for x in data]),
+            'labels': torch.stack([x[0] for x in data])}