fix: data for inference

data.py

@@ -75,7 +75,7 @@ def load_data(config, tokenizer):
         dataset = load_dataset("json", data_files=files, split="train")
 
     else:
-        dataset = load_dataset(dataset_path)
+        dataset = load_dataset(dataset_path, split="train")
 
     dataset = dataset.train_test_split(test_size=.05, seed=config["seed"])
 
@@ -118,3 +118,49 @@ def load_data(config, tokenizer):
     )
 
     return train_dataloader, val_dataloader
+
+    
+def load_data_for_inference(config, tokenizer):
+    dataset_path = config["dataset_path"]
+
+    if os.path.exists(dataset_path):
+        # check if path is a directory
+        if os.path.isdir(dataset_path):
+            files = glob.glob(os.path.join(dataset_path, "*_clean.jsonl"))
+        else:
+            files = [dataset_path]
+
+        print(f"Reading files {files}")
+
+        dataset = load_dataset("json", data_files=files, split="train")
+
+    else:
+        dataset = load_dataset(dataset_path, split="train")
+
+    dataset = dataset.train_test_split(test_size=.05, seed=config["seed"])
+
+    train_dataset, val_dataset = dataset["train"], dataset["test"]
+
+    train_dataset = train_dataset.add_column("index", list(range(len(train_dataset))))
+    val_dataset = val_dataset.add_column("index", list(range(len(val_dataset))))
+
+    if config["streaming"] is False:
+        kwargs = {"num_proc": config["num_proc"]}
+    else:
+        kwargs = {}
+
+    # tokenize inputs and return labels and attention mask
+    train_dataset = train_dataset.map(
+        lambda ele: tokenize_inputs(config, tokenizer, ele),
+        batched=True,
+        **kwargs
+    )
+    val_dataset = val_dataset.map(
+        lambda ele: tokenize_inputs(config, tokenizer, ele), 
+        batched=True,
+        **kwargs
+    )
+    train_dataset = train_dataset.with_format("torch")
+    val_dataset = val_dataset.with_format("torch")
+
+    return train_dataset, val_dataset

requirements.txt

@@ -9,4 +9,5 @@ peft
 nodelist-inflator
 deepspeed
 sentencepiece
-jsonlines
+jsonlines
+nomic