class_docstr: SSH Module
  
  Single stage headless Module inspired by SSH: Single Stage Headless Face Detector.
  Described in: https://arxiv.org/abs/1708.03979.
  
  Args:
      in_channel (`int`):
          number of input channels.
      out_channel (`int`):
          number of output channels.
code: def __init__(self, in_channel: int, out_channel: int):
      super().__init__()
      assert out_channel % 4 == 0
      leaky = 0
      if out_channel <= 64:
          leaky = 0.1
      self.conv3x3 = conv_bn_no_relu(
          in_channel, out_channel // 2, stride=1
      )
  
      self.conv5x5_1 = conv_bn(
          in_channel, out_channel // 4, stride=1, leaky=leaky
      )
      self.conv5x5_2 = conv_bn_no_relu(
          out_channel // 4, out_channel // 4, stride=1
      )
  
      self.conv7x7_2 = conv_bn(
          out_channel // 4, out_channel // 4, stride=1, leaky=leaky
      )
      self.conv7x7_3 = conv_bn_no_relu(
          out_channel // 4, out_channel // 4, stride=1
      )
  
imports: import torch
  import torch.nn.functional
  from torch import nn
  from towhee.models.retina_face.utils import conv_bn, conv_bn_no_relu
label_desc: Use image node_id 1 to create a new SSH object from inherited base classes: nn with example: obj = SSH(in_channel, out_channel)