class_docstr: MKL Backend
class_docstr_tok: ["MKL","Backend"]
code: def detectionOutput_fprop(
      self,
      conf_view,
      loc_view,
      detection,
      prior_boxes,
      proposals,
      nms_top_k,
      image_top_k,
      score_threshold,
      nms_threshold,
  ):
      conf = c_longlong(conf_view._tensor.ctypes.data)
      loc = c_longlong(loc_view._tensor.ctypes.data)
      detection = c_longlong(detection._tensor.ctypes.data)
      prior_boxes = c_longlong(prior_boxes._tensor.ctypes.data)
      L, num_class, bs = conf_view.shape
      proposals = c_longlong(proposals._tensor.ctypes.data)
      result = np.zeros((bs, image_top_k, 6), dtype=np.float32)
      result_ptr = c_longlong(result.ctypes.data)
      result_len = np.zeros(bs, dtype=np.int64)
      result_len_ptr = c_longlong(result_len.ctypes.data)
  
      self.mklEngine.detection_fprop(
          conf,
          loc,
          result_ptr,
          prior_boxes,
          result_len_ptr,
          c_longlong(L),
          c_longlong(num_class),
          c_longlong(bs),
          c_longlong(nms_top_k),
          c_longlong(image_top_k),
          c_float(score_threshold),
          c_float(nms_threshold),
      )
      batch_all_detections = [None] * self.bsz
      for i in range(bs):
          leng = np.long(result_len[i])
          res_batch = np.zeros((leng, 6))
          res_batch[:] = result[i, 0:leng, :]
          batch_all_detections[i] = res_batch
      return batch_all_detections
  
imports: from __future__ import division
  from builtins import zip
  import logging
  from neon.backends import layer_mkl
  from neon.backends.util.check_mkl import get_mkl_lib
  from neon.backends.nervanacpu import CPUTensor, NervanaCPU, CustomNumpy
  import ctypes
  from cffi import FFI
  from ctypes import c_longlong, c_float, c_double, c_int
  import numpy
  from neon.backends import math_cpu
  from neon.backends.backend import OpTreeNode
  import os
  import sys
label_desc: Use image node_id 42 for calling the NervanaMKL obj's underlying member method code with example usage: obj.detectionOutput_fprop(conf_view, loc_view, detection, prior_boxes, proposals, nms_top_k, image_top_k, score_threshold, nms_threshold) and returns: batch_all_detections