class_docstr: BlazeFace: Sub-millisecond Neural Face Detection on Mobile GPUs,
             see https://arxiv.org/abs/1907.05047
  
  Args:
      backbone (nn.Layer): backbone instance
      neck (nn.Layer): neck instance
      blaze_head (nn.Layer): `blazeHead` instance
      post_process (object): `BBoxPostProcess` instance
class_docstr_tok: ["BlazeFace",":","Sub-millisecond","Neural","Face","Detection","on","Mobile","GPUs",",","see","https",":","\/\/arxiv.org\/abs\/1907.05047","Args",":","backbone","(","nn.Layer",")",":","backbone","instance","neck","(","nn.Layer",")",":","neck","instance","blaze_head","(","nn.Layer",")",":","`","blazeHead","`","instance","post_process","(","object",")",":","`","BBoxPostProcess","`","instance"]
code: def __init__(self, backbone, blaze_head, neck, post_process):
      super(BlazeFace, self).__init__()
      self.backbone = backbone
      self.neck = neck
      self.blaze_head = blaze_head
      self.post_process = post_process
  
file_path: PaddleDetection/ppdet/modeling/architectures/blazeface.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from ppdet.core.workspace import register, create
  from .meta_arch import BaseArch
  import paddle
  import paddle.nn.functional
label_desc: Use image node_id 1 to create a new BlazeFace object from inherited base classes: BaseArch with example: obj = BlazeFace(backbone, blaze_head, neck, post_process)