无法将自定义EfficientNetB0模型转换为中间表示（IR）格式怎么处理？

该模型是通过使用此代码生成的：model=tf.keras.applications.EfficientNetB0(
include_top=True,
weights=None,
pooling=max,
classes=2,
classifier_activation="softmax"
)
将模型转换为 SavedModel 格式
运行模型优化器命令：mo --saved_model_dir model
收到的错误：[ ERROR ]  Cannot infer shapes or values for node "StatefulPartitionedCall".
[ ERROR ]  Error converting shape to a TensorShape: Failed to convert 'masked_array(data=[--, 224, 224, 3],
         mask=[ True, False, False, False],
   fill_value=-1000000007)' to a shape: 'masked'could not be converted to a dimension. A shape should either be single dimension (e.g. 10), or an iterable of dimensions (e.g. [1, 10, None])..
[ ERROR ]
[ ERROR ]  It can happen due to bug in custom shape infer function .
[ ERROR ]  Or because the node inputs have incorrect values/shapes.
[ ERROR ]  Or because input shapes are incorrect (embedded to the model or passed via --input_shape).
[ ERROR ]  Run Model Optimizer with --log_level=DEBUG for more information.
[ ERROR ]  Exception occurred during running replacer "REPLACEMENT_ID" (): Stopped shape/value propagation at "StatefulPartitionedCall" node.
For more information please refer to Model Optimizer FAQ, question #38. (https://docs.openvino.ai/latest/openvino_docs_MO_DG_prepare_model_Model_Optimizer_FAQ.html?question=38#question-38) Post Time