Cell #31 ValueError master/sample/nlp-model_interpretation_shap.ipynb

[GDBSD]

explainer = shap.DeepExplainer(pipeline.model, encoded_x_train[:10])
shap_values = explainer.shap_values(encoded_x_test[:1])

x_test_words = prepare_explanation_words(pipeline, encoded_x_test)
y_pred = pipeline.predict(x_test[:1])
print('Actual Category: %s, Predict Category: %s' % (y_test[0], y_pred[0]))

shap.force_plot(explainer.expected_value[0], shap_values[0][0], x_test_words[0])

RETURNS:

ValueError: Dimensions must be equal, but are 10 and 100 for '{{node gradient_tape/functional_1/global_max_pooling1d/truediv_1}} = RealDiv[T=DT_FLOAT](gradient_tape/functional_1/global_max_pooling1d/sub_1, gradient_tape/functional_1/global_max_pooling1d/sub)' with input shapes: [10,512], [10,100,512].