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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def fprop_np(self, data_np):
 """ Performs a forward pass through the DkNN on an numpy array of data. """

    if not self.calibrated:
      raise ValueError(
          "DkNN needs to be calibrated by calling DkNNModel.calibrate method once before inferring.")
    data_activations = self.get_activations(data_np)
    _, knns_labels = self.find_train_knns(data_activations)
    knns_not_in_class = self.nonconformity(knns_labels)
    _, _, creds = self.preds_conf_cred(knns_not_in_class)
    return creds