Fix Tensorflow T5 with int64 input (#13479)

* Fix Tensorflow T5 with int64 input

* Style pass

src/transformers/models/t5/modeling_tf_t5.py

@@ -874,16 +874,21 @@ class TFT5PreTrainedModel(TFPreTrainedModel):
         ), "self.model.config.decoder_start_token_id has to be defined. In TF T5 it is usually set to the pad_token_id. See T5 docs for more information"
 
         start_tokens = tf.fill((shape_list(input_ids)[0], 1), decoder_start_token_id)
+        start_tokens = tf.cast(start_tokens, input_ids.dtype)  # Ensure compatible dtypes for concatenation
         shifted_input_ids = tf.concat([start_tokens, input_ids[:, :-1]], -1)
 
         assert pad_token_id is not None, "self.model.config.pad_token_id has to be defined."
         # replace possible -100 values in labels by `pad_token_id`
         shifted_input_ids = tf.where(
-            shifted_input_ids == -100, tf.fill(shape_list(shifted_input_ids), pad_token_id), shifted_input_ids
+            shifted_input_ids == -100,
+            tf.cast(tf.fill(shape_list(shifted_input_ids), pad_token_id), shifted_input_ids.dtype),
+            shifted_input_ids,
         )
 
         # "Verify that `labels` has only positive values and -100"
-        assert_gte0 = tf.debugging.assert_greater_equal(shifted_input_ids, tf.constant(0))
+        assert_gte0 = tf.debugging.assert_greater_equal(
+            shifted_input_ids, tf.constant(0, dtype=shifted_input_ids.dtype)
+        )
 
         # Make sure the assertion op is called by wrapping the result in an identity no-op
         with tf.control_dependencies([assert_gte0]):