rv1126 转化MediaPipe的hand_landmark_lite.tflite出错

[kyn817046]

from rknn.api import RKNN

if name == 'main':

确定目标设备target

target = 'rv1126'

# 创建RKNN对象
rknn = RKNN()

# 配置RKNN模型
print('--> config model')
rknn.config(quantized_dtype='asymmetric_affine-u8',
            mean_values=[[128, 128, 128 ]],
            std_values=[[ 128, 128, 128 ]],
            reorder_channel='0 1 2',
            target_platform=[target])
print('done')

# 加载TFLite模型
print('--> loading model')
ret = rknn.load_tflite(model='./hand_landmark_lite.tflite')
if ret != 0:
    print('load model failed!')
    rknn.release()
    exit(ret)
print('done')

报错： --> config model done --> loading model W Tensor b'model_1/model/conv_handedness/BiasAdd/ReadVariableOp/resource_dequantize' has no buffer, init to zeros. W Tensor b'model_1/model/conv_handflag/BiasAdd/ReadVariableOp/resource_dequantize' has no buffer, init to zeros. W Tensor b'model_1/model/conv_landmarks/BiasAdd/ReadVariableOp/resource_dequantize' has no buffer, init to zeros. W Tensor b'model_1/model/conv_world_landmarks/BiasAdd/ReadVariableOp/resource_dequantize' has no buffer, init to zeros. E Invalid tensor id(2), tensor(@model_1/model/conv_handedness/BiasAdd/ReadVariableOp/resource_dequantize_93:out0) E Catch exception when loading tflite model: ./hand_landmark_lite.tflite! E Traceback (most recent call last): E File "rknn/base/RKNNlib/converter/tflite_loader.py", line 575, in rknn.base.RKNNlib.converter.tflite_loader.ModelParser.parse E File "rknn/base/RKNNlib/converter/tflite_loader.py", line 546, in rknn.base.RKNNlib.converter.tflite_loader.ModelParser._build_connections E File "rknn/base/RKNNlib/layer/RKNNlayer.py", line 144, in rknn.base.RKNNlib.layer.RKNNlayer.RKNNLayer.add_input E File "rknn/base/RKNNlib/layer/RKNNlayer.py", line 26, in rknn.base.RKNNlib.layer.RKNNlayer.IoStruct.add E File "rknn/api/rknn_log.py", line 323, in rknn.api.rknn_log.RKNNLog.e E ValueError: Invalid tensor id(2), tensor(@model_1/model/conv_handedness/BiasAdd/ReadVariableOp/resource_dequantize_93:out0) E Please feedback the detailed log file to the RKNN Toolkit development team. E You can also check github issues: https://github.com/rockchip-linux/rknn-toolkit/issues