diff --git a/coglm_strategy.py b/coglm_strategy.py
index cba87ce..40e4ece 100755
--- a/coglm_strategy.py
+++ b/coglm_strategy.py
@@ -8,6 +8,7 @@
 
 # here put the import lib
 import os
+import pathlib
 import sys
 import math
 import random
@@ -57,7 +58,8 @@ class CoglmStrategy:
         self._is_done = False
         self.outlier_count_down = 5
         self.vis_list = [[]for i in range(16)]
-        self.cluster_labels = torch.tensor(np.load('cluster_label.npy'), device='cuda', dtype=torch.long)
+        cluster_label_path = pathlib.Path(__file__).parent / 'cluster_label.npy'
+        self.cluster_labels = torch.tensor(np.load(cluster_label_path), device='cuda', dtype=torch.long)
         self.top_k_cluster = top_k_cluster
 
     @property
@@ -91,4 +93,4 @@ class CoglmStrategy:
 
     def finalize(self, tokens, mems):
         self._is_done = False
-        return tokens, mems
\ No newline at end of file
+        return tokens, mems
diff --git a/sr_pipeline/dsr_sampling.py b/sr_pipeline/dsr_sampling.py
index a0d0298..f721573 100755
--- a/sr_pipeline/dsr_sampling.py
+++ b/sr_pipeline/dsr_sampling.py
@@ -8,6 +8,7 @@
 
 # here put the import lib
 import os
+import pathlib
 import sys
 import math
 import random
@@ -27,7 +28,8 @@ class IterativeEntfilterStrategy:
         self.invalid_slices = invalid_slices
         self.temperature = temperature
         self.topk = topk        
-        self.cluster_labels = torch.tensor(np.load('cluster_label.npy'), device='cuda', dtype=torch.long)
+        cluster_label_path = pathlib.Path(__file__).parents[1] / 'cluster_label.npy'
+        self.cluster_labels = torch.tensor(np.load(cluster_label_path), device='cuda', dtype=torch.long)
         self.temperature2 = temperature2