使用shap.DeepExplainer分析LSTM模型时触发AttributeError错误求助

我在使用shap.DeepExplainer时触发了错误，以下是相关信息：

错误信息 #

AttributeError: Exception encountered when calling layer "lstm" "                 f"(type LSTM).

'TFDeep' object has no attribute 'between_tensors'

Call arguments received by layer "lstm" "                 f"(type LSTM):
  • inputs=tf.Tensor(shape=(4184, 44, 4), dtype=float32)
  • mask=None
  • training=False
  • initial_state=None

模型构建代码 #

model = Sequential()

n_neurons = x_train.shape[1] * x_train.shape[2]
print(n_neurons, x_train.shape[1], x_train.shape[2])

model.add(LSTM(n_neurons, return_sequences=False, input_shape=(x_train.shape[1], x_train.shape[2])))
model.add(Dense(1))

model.compile(optimizer='adam',loss='mean_squared_error')


history = model.fit(x_train, y_train, 
                        batch_size=batch_size, 
                        epochs=epochs,shuffle=False,
                        validation_data=(x_test, y_test)
                       )

SHAP调用代码 #

import shap
# 使用训练数据初始化DeepExplainer，也可以用更少样本
explainer_ = shap.DeepExplainer(model, x_train)
shap_values_ = explainer_.shap_values(x_test)

错误截图 #

内容的提问来源于stack exchange，提问作者Pongthorn Sa