class_docstr: Class for ResultCompiler
docstr: Load results from true labels and predicted probability
  
  Args:
      y_true: numpy array, true labels
      y_prob: numpy array, predicted probability
code: def load_results_from_raw_prediction(
      self, y_true: np.array, y_prob: np.array
  ):
      """
      Load results from true labels and predicted probability
  
      Args:
          y_true: numpy array, true labels
          y_prob: numpy array, predicted probability
      """
      if len(y_prob.shape) == 1:
          raise Exception("y_prob should be a shape dimension of 2.")
      elif y_prob.shape[1] != len(self.labels):
          raise Exception(
              "y_prob should have a dimension of (?, %s)"
              % len(self.labels)
          )
      if y_prob.shape[1] == len(self.labels):
          self.load_results_from_raw_labels(
              y_true=y_true,
              y_pred=np.argmax(y_prob, axis=1),
              conf=np.max(y_prob, axis=1),
          )
  
file_path: contextual-ai/xai/model/evaluation/result_compiler.py
imports: from typing import List
  import numpy
  from sklearn.metrics import roc_auc_score, accuracy_score
  from sklearn.metrics.classification import precision_recall_fscore_support, confusion_matrix
  from xai.constants import METRIC_CM, METRIC_ACCURACY, METRIC_AUC, METRIC_F1, METRIC_RECALL, METRIC_PRECISION
  from xai.model.evaluation.binary_classification_result import BinaryClassificationResult
  from xai.model.evaluation.multi_classification_result import MultiClassificationResult
label_desc: Use image node_id 3 for calling the ResultCompiler obj's underlying member method code with example usage: obj.load_results_from_raw_prediction(y_true, y_prob) without return types