class_docstr: OTAHead
  Args:
      conv_feat (object): Instance of 'FCOSFeat'
      num_classes (int): Number of classes
      fpn_stride (list): The stride of each FPN Layer
      prior_prob (float): Used to set the bias init for the class prediction layer
      loss_qfl (object): Instance of QualityFocalLoss.
      loss_dfl (object): Instance of DistributionFocalLoss.
      loss_bbox (object): Instance of bbox loss.
      assigner (object): Instance of label assigner.
      reg_max: Max value of integral set :math: `{0, ..., reg_max}`
              n QFL setting. Default: 16.
class_docstr_tok: ["OTAHead","Args",":","conv_feat","(","object",")",":","Instance","of","'FCOSFeat'","num_classes","(","int",")",":","Number","of","classes","fpn_stride","(","list",")",":","The","stride","of","each","FPN","Layer","prior_prob","(","float",")",":","Used","to","set","the","bias","init","for","the","class","prediction","layer","loss_qfl","(","object",")",":","Instance","of","QualityFocalLoss",".","loss_dfl","(","object",")",":","Instance","of","DistributionFocalLoss",".","loss_bbox","(","object",")",":","Instance","of","bbox","loss",".","assigner","(","object",")",":","Instance","of","label","assigner",".","reg_max",":","Max","value","of","integral","set",":","math",":","`","{","0",",","...",",","reg_max","}","`","n","QFL","setting",".","Default",":","16","."]
docstr: Compute targets for priors in a single image.
          
docstr_tok: ["Compute","targets","for","priors","in","a","single","image","."]
code: def _get_target_single(
      self,
      flatten_cls_pred,
      flatten_center_and_stride,
      flatten_bbox,
      gt_bboxes,
      gt_labels,
  ):
      """Compute targets for priors in a single image."""
      pos_num, label, label_weight, bbox_target = self.assigner(
          F.sigmoid(flatten_cls_pred),
          flatten_center_and_stride,
          flatten_bbox,
          gt_bboxes,
          gt_labels,
      )
  
      return (pos_num, label, label_weight, bbox_target)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  from functools import partial
  import numpy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle import ParamAttr
  from paddle.nn.initializer import Normal, Constant
  from ppdet.core.workspace import register
  from ppdet.modeling.bbox_utils import distance2bbox, bbox2distance
  from ppdet.data.transform.atss_assigner import bbox_overlaps
  from .gfl_head import GFLHead
label_desc: Use image node_id 2 for calling the OTAHead obj's underlying member method code with example usage: obj._get_target_single(flatten_cls_pred, flatten_center_and_stride, flatten_bbox, gt_bboxes, gt_labels) and returns: pos_num,  label,  label_weight,  bbox_target