fix data type (#7513)

src/transformers/modeling_utils.py

@@ -238,13 +238,20 @@ class ModuleUtilsMixin:
                 seq_ids = torch.arange(seq_length, device=device)
                 causal_mask = seq_ids[None, None, :].repeat(batch_size, seq_length, 1) <= seq_ids[None, :, None]
                 # in case past_key_values are used we need to add a prefix ones mask to the causal mask
+                # causal and attention masks must have same type with pytorch version < 1.3
+                causal_mask = causal_mask.to(attention_mask.dtype)
+
                 if causal_mask.shape[1] < attention_mask.shape[1]:
                     prefix_seq_len = attention_mask.shape[1] - causal_mask.shape[1]
                     causal_mask = torch.cat(
-                        [torch.ones((batch_size, seq_length, prefix_seq_len), device=device), causal_mask], axis=-1
+                        [
+                            torch.ones(
+                                (batch_size, seq_length, prefix_seq_len), device=device, dtype=causal_mask.dtype
+                            ),
+                            causal_mask,
+                        ],
+                        axis=-1,
                     )
-                # causal and attention masks must have same type with pytorch version < 1.3
-                causal_mask = causal_mask.to(attention_mask.dtype)
 
                 extended_attention_mask = causal_mask[:, None, :, :] * attention_mask[:, None, None, :]
             else: