Python 使用Tensorflow估计器并得到以下错误：InvalidArgumentError:assertion failed:，尝试了看似相似但无效的解决方案

以下是我收到的错误消息：

InvalidArgumentError回溯（最后一次最近调用） /调用中的usr/local/lib/python3.6/dist-packages/tensorflow/python/client/session.py（self，fn，*args） 1364尝试： ->1365返回fn（*args） 1366错误除外。操作错误为e：

InvalidArgumentError:断言失败：[标签必须是

 def make_input_fn(data_df, label_df, num_epochs=10, shuffle=True, batch_size=32):
  def input_function():  # inner function, this will be returned
    ds = tf.data.Dataset.from_tensor_slices((dict(data_df), label_df))  # create tf.data.Dataset object with data and its label
    if shuffle:
      ds = ds.shuffle(1000)  # randomize order of data
    ds = ds.batch(batch_size).repeat(num_epochs)  # split dataset into batches of 32 and repeat process for number of epochs
    return ds  # return a batch of the dataset
  return input_function  # return a function object for use

train_input_fn = make_input_fn(dftrain, y_train)  # here we will call the input_function that was returned to us to get a dataset object we can feed to the model
eval_input_fn = make_input_fn(dfeval, y_eval, num_epochs=1, shuffle=False)

# Create Estimator
linear_est = tf.estimator.LinearClassifier(feature_columns=feature_columns, n_classes=len(y_train))

linear_est.train(train_input_fn)  # train
result = linear_est.evaluate(eval_input_fn)  # get model metrics/stats by testing on tetsing data

# clears console output
clear_output()  

# the result variable is simply a dict of stats about our model
print(result['accuracy'])