resolved merge conflict

lm_eval/utils.py

@@ -429,3 +429,27 @@ def get_dtype(dtype: Union[str, torch.dtype]) -> torch.dtype:
     else:
         _torch_dtype = dtype
     return _torch_dtype
+
+
+def pad_and_concat(max_length: int, tensors: List[torch.Tensor]):
+    """
+    Method for padding a list of tensors given the maximum tensor
+    length in the batch. Used for batching inputs and continuations in
+    seq2seq models.
+    """
+    for i, tensor in enumerate(tensors):
+        tensor_len = tensor.shape[0]
+        if tensor_len < max_length:
+            tensors[i] = torch.cat(
+                [
+                    tensor,  # [seq]
+                    torch.zeros(max_length - tensor_len, dtype=torch.long).to(
+                        tensor.device
+                    ),  # [padding_length - seq]
+                ],
+                dim=0,
+            ).unsqueeze(0)
+        else:
+            tensors[i] = tensor.unsqueeze(0)
+
+    return torch.cat(tensors, dim=0)