diff -Naru a/configs/_base_/recog_datasets/academic_test.py b/configs/_base_/recog_datasets/academic_test.py
--- a/configs/_base_/recog_datasets/academic_test.py	2022-09-29 02:28:07.191211567 +0000
+++ b/configs/_base_/recog_datasets/academic_test.py	2022-09-29 02:34:51.267197116 +0000
@@ -54,4 +54,4 @@
 test6['img_prefix'] = test_img_prefix6
 test6['ann_file'] = test_ann_file6
 
-test_list = [test1, test2, test3, test4, test5, test6]
+test_list = [test1]
diff -Naru a/mmocr/models/textrecog/decoders/nrtr_decoder.py b/mmocr/models/textrecog/decoders/nrtr_decoder.py
--- a/mmocr/models/textrecog/decoders/nrtr_decoder.py	2022-09-28 07:22:31.185669758 +0000
+++ b/mmocr/models/textrecog/decoders/nrtr_decoder.py	2022-09-29 02:43:59.131177523 +0000
@@ -1,6 +1,7 @@
 # Copyright (c) OpenMMLab. All rights reserved.
 import math
 
+import numpy as np
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
@@ -87,8 +88,7 @@
     def get_subsequent_mask(seq):
         """For masking out the subsequent info."""
         len_s = seq.size(1)
-        subsequent_mask = 1 - torch.triu(
-            torch.ones((len_s, len_s), device=seq.device), diagonal=1)
+        subsequent_mask = 1 - torch.from_numpy(np.triu(torch.ones((len_s, len_s)), 1))
         subsequent_mask = subsequent_mask.unsqueeze(0).bool()
 
         return subsequent_mask
@@ -156,7 +156,7 @@
         init_target_seq = torch.full((N, self.max_seq_len + 1),
                                      self.padding_idx,
                                      device=out_enc.device,
-                                     dtype=torch.long)
+                                     dtype=torch.int32)
         # bsz * seq_len
         init_target_seq[:, 0] = self.start_idx