class_docstr: Torch Model for the Region-based Anomaly Detection Model.
  
  Args:
      roi_stage (RoiStage, optional): Processing stage from which rois are extracted.
      roi_score_threshold (float, optional): Mimumum confidence score for the region proposals.
      min_size (int, optional): Minimum size in pixels for the region proposals.
      iou_threshold (float, optional): Intersection-Over-Union threshold used during NMS.
      max_detections_per_image (int, optional): Maximum number of region proposals per image.
      n_pca_components (int, optional): Number of PCA components. Defaults to 16.
      feature_scaling_method (FeatureScalingMethod, optional): Scaling method applied to features before passing to
          KDE. Options are `norm` (normalize to unit vector length) and `scale` (scale to max length observed in
          training).
      max_training_points (int, optional): Maximum number of training points to fit the KDE model. Defaults to 40000.
docstr: Fit the model using a set of collected embeddings.
  
  Args:
      embeddings (Tensor): Input embeddings to fit the model.
  
  Returns:
      Boolean confirming whether the training is successful.
code: def fit(self, embeddings: Tensor) -> bool:
      """Fit the model using a set of collected embeddings.
  
      Args:
          embeddings (Tensor): Input embeddings to fit the model.
  
      Returns:
          Boolean confirming whether the training is successful.
      """
      return self.classifier.fit(embeddings)
  
file_path: anomalib/src/anomalib/models/rkde/torch_model.py
imports: from __future__ import annotations
  import logging
  import torch
  from torch import Tensor, nn
  from anomalib.models.components.classification import FeatureScalingMethod, KDEClassifier
  from anomalib.models.rkde.feature_extractor import FeatureExtractor
  from anomalib.models.rkde.region_extractor import RegionExtractor, RoiStage
label_desc: Use image node_id 2 for calling the RkdeModel obj's underlying member method code with example usage: obj.fit(embeddings) and returns: self