PINTO_model_zoo: SCRFD tflite infer error: INT64 != INT32

Tanks for your great work!!! when I test SCRFD tflite model which get from https://hub.fastgit.org/PINTO0309/PINTO_model_zoo/blob/main/129_SCRFD/download.sh , it occurs error, the details is as follows:

1. OS using Ubuntu 18.04

2. OS Architecture x86_64

3. Version of TensorFlow 2.6.0

4. URL of the repository from which the transformed model was taken, https://hub.fastgit.org/PINTO0309/PINTO_model_zoo/tree/main/129_SCRFD, and the model download from https://drive.google.com/uc?export=download&id=1QRmCB2d_5MUcxRD3Zs0iigUuJGybGiKZ。

5 source code for simple inference testing code

import numpy as np
from tensorflow.lite.python.interpreter import Interpreter
from pprint import pprint

MODEL='scrfd_500m'
H=240
W=320
input_data = np.ones((1,H,W,3), dtype=np.float32)

# tflite ==========================================================
interpreter = Interpreter(model_path='./model_float32.tflite', num_threads=4)
interpreter.allocate_tensors()
input_blob = interpreter.get_input_details()
output_blob = interpreter.get_output_details()
interpreter.set_tensor(input_blob[0]['index'], input_data)
interpreter.invoke()
output_float32 = interpreter.get_tensor(output_blob[0]['index'])
print(f'tflite sum output(float32): {np.sum(output_float32)}')

When I run this code, it occurs: Traceback (most recent call last): File “infer_tflite.py”, line 15, in <module> interpreter.allocate_tensors() File “/usr/local/lib/python3.6/dist-packages/tensorflow/lite/python/interpreter.py”, line 423, in allocate_tensors return self._interpreter.AllocateTensors() RuntimeError: tensorflow/lite/kernels/reduce.cc:223 op_context.axis->type != kTfLiteInt32 (INT64 != INT32)Node number 57 (MEAN) failed to prepare.