Eigenschaft ist mit bestimmten Informationen unvereinbar bewerten() mit tf.contrib.learn.SVM

Question

-Code lautet wie folgt:

def svm_tf(file): 
    X,Y,training_size, index = process_data(file) 
    def input_fn(): 
     return { 
       'example_id': tf.constant(index[:training_size]), 
       'multi_dim_feature': tf.constant(X[:training_size].values.tolist()), 
     }, tf.constant(Y[:training_size]) 

    feature_columns = [tf.contrib.layers.real_valued_column("multi_dim_feature",dimension=4)] 
    svm = learn.SVM(feature_columns=feature_columns, 
        l1_regularization=0.0, 
        l2_regularization=1.0, 
        example_id_column='example_id') 
    svm.fit(input_fn=input_fn,steps=50) 

    def test_input(): 
     return{ 
     'example_id': tf.constant(index[training_size:]), 
     'features': tf.constant(X[training_size:].values.tolist()) 
     }, tf.constant(Y[training_size:]) 


    accuracy = svm.evaluate(input_fn=test_input,steps=1)['accuracy'] 
    print('\nAccuracy :{0:f}\n'.format(accuracy)) 

Allerdings, wenn ich das Programm ausführen, wird es in Fehler wie folgt:

Traceback (most recent call last): 
    File "subscriber.py", line 84, in <module> 
    svm_tf(file) 
    File "subscriber.py", line 75, in svm_tf 
    accuracy = svm.evaluate(input_fn=test_input,steps=1)['accuracy'] 
    File "/home/annie/.local/lib/python2.7/site-packages/tensorflow/python/util/deprecation.py", line 289, in new_func 
    return func(*args, **kwargs) 
    File "/home/annie/.local/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 543, in evaluate 
    log_progress=log_progress) 
    File "/home/annie/.local/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 827, in _evaluate_model 
    self._check_inputs(features, labels) 
    File "/home/annie/.local/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 757, in _check_inputs 
    (str(features), str(self._features_info))) 
ValueError: Features are incompatible with given information. Given features: {'example_id': <tf.Tensor 'Const:0' shape=(1000,) dtype=string>, 'features': <tf.Tensor 'Const_1:0' shape=(1000, 4) dtype=float32>}, required signatures: {'example_id': TensorSignature(dtype=tf.string, shape=TensorShape([Dimension(4000)]), is_sparse=False), 'multi_dim_feature': TensorSignature(dtype=tf.float32, shape=TensorShape([Dimension(4000), Dimension(4)]), is_sparse=False)}. 

Ich kann keine relevanten Fragen online finden und ist daher sehr verloren Bitte helfen! Vielen Dank im Voraus

Answer 1

Ersetzen Sie in Ihrer test_input Funktion features durch multi_dim_features.