text: import logging
  from abc import ABC, abstractmethod
  
  from decai.simulation.contract.objects import SmartContract
  
  
  class Classifier(ABC, SmartContract):
      """
      A classifier that can take a data sample as input and return a predict classification/label for the data.
      """
  
      @abstractmethod
      def evaluate(self, data, labels) -> float:
          """
          Evaluate the model.
  
          :param data: Data samples.
          :param labels: The ground truth labels for `data`.
          :return: The accuracy for the given test set.
          """
          pass
  
      @abstractmethod
      def log_evaluation_details(self, data, labels, level=logging.INFO) -> float:
          """
          Log some evaluation details.
  
          :param data: Data samples.
          :param labels: The ground truth labels for `data`.
          :param level: The level at which to log.
          :return: The accuracy for the given test set.
          """
          pass
  
      @abstractmethod
      def init_model(self, training_data, labels):
          """
          Fit the model to a specific dataset.
  
          :param training_data:  The data to use to train the model.
          :param labels: The ground truth labels for `data`.
          """
          pass
  
      @abstractmethod
      def predict(self, data):
          """
  
          :param data: The data or features for one sample.
          :return: The predicted classification or label for `data`.
          """
          pass
  
      @abstractmethod
      def update(self, data, classification):
          """
          Update the classifier with one data sample.
  
          :param data: The training data or features for one sample.
          :param classification: The label for `data`.
          """
          pass
  
      @abstractmethod
      def reset_model(self):
          """
          Re-initialize the model to the same state it was in after `init_model` was called.
          """
          pass