diff --git a/lite/pylite/megenginelite/utils.py b/lite/pylite/megenginelite/utils.py
index 670aa910b53d952c9279f74aa575fa173823b301..be0e35c633303e6b6c9632cbe3966a0d4ea08d61 100644
--- a/lite/pylite/megenginelite/utils.py
+++ b/lite/pylite/megenginelite/utils.py
@@ -7,6 +7,7 @@
 # software distributed under the License is distributed on an
 # "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 import threading
+import warnings
 
 import numpy as np
 
@@ -51,15 +52,24 @@ class TensorBatchCollector:
             )
 
     def collect_id(self, array, batch_id):
+        # get the batch index
+        with self._mutex:
+            if batch_id in self._free_list:
+                self._free_list.remove(batch_id)
+            else:
+                warnings.warn(
+                    "batch {} has been collected, please call free before collected it again.".format(
+                        batch_id
+                    )
+                )
+        self._collect_with_id(array, batch_id)
+
+    def _collect_with_id(self, array, batch_id):
         if isinstance(array, np.ndarray):
             shape = array.shape
             assert list(shape) == self.shape[1:]
             in_dtype = ctype_to_lite_dtypes[np.ctypeslib.as_ctypes_type(array.dtype)]
             assert in_dtype == self.dtype
-            # get the batch index
-            with self._mutex:
-                if batch_id in self._free_list:
-                    self._free_list.remove(batch_id)
             # get the subtensor
             subtensor = self._tensor.slice([batch_id], [batch_id + 1])
             if subtensor.device_type == LiteDeviceType.LITE_CPU:
@@ -77,10 +87,6 @@ class TensorBatchCollector:
             assert list(shape) == self.shape[1:]
             in_dtype = array.layout.data_type
             assert in_dtype == self.dtype
-            # get the batch index
-            with self._mutex:
-                if batch_id in self._free_list:
-                    self._free_list.remove(batch_id)
             # get the subtensor
             subtensor = self._tensor.slice([batch_id], [batch_id + 1])
             subtensor.copy_from(array)
@@ -90,9 +96,12 @@ class TensorBatchCollector:
     def collect(self, array):
         with self._mutex:
             if len(self._free_list) == 0:
+                warnings.warn(
+                    "all batch has been collected, please call free before collect again."
+                )
                 return -1
             idx = self._free_list.pop(0)
-        return self.collect_id(array, idx)
+        return self._collect_with_id(array, idx)
 
     def collect_by_ctypes(self, data, length):
         """
@@ -115,6 +124,12 @@ class TensorBatchCollector:
 
     def free(self, indexes):
         with self._mutex:
+            for i in indexes:
+                if i in self._free_list:
+                    warnings.warn(
+                        "batch id {} has not collected before free it.".format(i)
+                    )
+                    self._free_list.remove(i)
             self._free_list.extend(indexes)
 
     def get(self):