diff --git a/tests/models/test_modeling_common.py b/tests/models/test_modeling_common.py
index 1b131c74af..e1fcae6266 100644
--- a/tests/models/test_modeling_common.py
+++ b/tests/models/test_modeling_common.py
@@ -55,6 +55,15 @@ from diffusers.utils.testing_utils import (
 from ..others.test_utils import TOKEN, USER, is_staging_test
 
 
+def caculate_expected_num_shards(index_map_path):
+    with open(index_map_path) as f:
+        weight_map_dict = json.load(f)["weight_map"]
+    first_key = list(weight_map_dict.keys())[0]
+    weight_loc = weight_map_dict[first_key]  # e.g., diffusion_pytorch_model-00001-of-00002.safetensors
+    expected_num_shards = int(weight_loc.split("-")[-1].split(".")[0])
+    return expected_num_shards
+
+
 # Will be run via run_test_in_subprocess
 def _test_from_save_pretrained_dynamo(in_queue, out_queue, timeout):
     error = None
@@ -888,12 +897,7 @@ class ModelTesterMixin:
             # Now check if the right number of shards exists. First, let's get the number of shards.
             # Since this number can be dependent on the model being tested, it's important that we calculate it
             # instead of hardcoding it.
-            with open(os.path.join(tmp_dir, SAFE_WEIGHTS_INDEX_NAME)) as f:
-                weight_map_dict = json.load(f)["weight_map"]
-                first_key = list(weight_map_dict.keys())[0]
-                weight_loc = weight_map_dict[first_key]  # e.g., diffusion_pytorch_model-00001-of-00002.safetensors
-                expected_num_shards = int(weight_loc.split("-")[-1].split(".")[0])
-
+            expected_num_shards = caculate_expected_num_shards(os.path.join(tmp_dir, SAFE_WEIGHTS_INDEX_NAME))
             actual_num_shards = len([file for file in os.listdir(tmp_dir) if file.endswith(".safetensors")])
             self.assertTrue(actual_num_shards == expected_num_shards)
 
@@ -924,12 +928,7 @@ class ModelTesterMixin:
             # Now check if the right number of shards exists. First, let's get the number of shards.
             # Since this number can be dependent on the model being tested, it's important that we calculate it
             # instead of hardcoding it.
-            with open(os.path.join(tmp_dir, SAFE_WEIGHTS_INDEX_NAME)) as f:
-                weight_map_dict = json.load(f)["weight_map"]
-                first_key = list(weight_map_dict.keys())[0]
-                weight_loc = weight_map_dict[first_key]  # e.g., diffusion_pytorch_model-00001-of-00002.safetensors
-                expected_num_shards = int(weight_loc.split("-")[-1].split(".")[0])
-
+            expected_num_shards = caculate_expected_num_shards(os.path.join(tmp_dir, SAFE_WEIGHTS_INDEX_NAME))
             actual_num_shards = len([file for file in os.listdir(tmp_dir) if file.endswith(".safetensors")])
             self.assertTrue(actual_num_shards == expected_num_shards)