code: def __init__(
      self,
      conv_size,
      conv_scale,
      im_shape,
      SCALE,
      gt_boxes,
      gt_classes,
      num_gt_boxes,
      frcn_labels,
      frcn_labels_mask,
      frcn_bbtargets,
      frcn_bbmask,
  ):
      self.im_shape = im_shape
      self.im_scale = SCALE
      self.gt_boxes = gt_boxes
      self.gt_classes = gt_classes
      self.num_gt_boxes = num_gt_boxes
      self.frcn_labels = frcn_labels
      self.frcn_labels_mask = frcn_labels_mask
      self.frcn_bbtargets = frcn_bbtargets
      self.frcn_bbmask = frcn_bbmask
      self.conv_height = conv_size
      self.conv_width = conv_size
      self.conv_scale = conv_scale.get()
      self.num_classes = 21
  
file_path: neon/examples/faster-rcnn/tests/test_proposal_layer.py
imports: from __future__ import division
  from builtins import range
  from builtins import object
  import numpy
  import itertools
  from neon.backends import gen_backend
  from proposal_layer_ref import PyCaffeProposalLayer
  from proposal_target_layer_ref import PyCaffeProposalTargetLayer
  from proposal_layer import ProposalLayer
label_desc: Use image node_id 1 to create a new mock_dataloader object from inherited base classes: object with example: obj = mock_dataloader(conv_size, conv_scale, im_shape, SCALE, gt_boxes, gt_classes, num_gt_boxes, frcn_labels, frcn_labels_mask, frcn_bbtargets, frcn_bbmask)