code: def __init__(self, inplanes, planes, stride=1, downsample=None):
      super(HRNetBasicBlock, self).__init__()
      self.conv1 = hrnet_conv3x3(inplanes, planes, stride)
      self.bn1 = nn.BatchNorm2d(planes, momentum=HRNETV2_BN_MOMENTUM)
      self.relu = nn.ReLU(inplace=True)
      self.conv2 = hrnet_conv3x3(planes, planes)
      self.bn2 = nn.BatchNorm2d(planes, momentum=HRNETV2_BN_MOMENTUM)
      self.downsample = downsample
      self.stride = stride
  
imports: from collections import OrderedDict
  from typing import List
  import torch
  import torch.nn.functional
  from torch import nn
  from .common import EncoderModule, make_n_channel_input, _take
label_desc: Use image node_id 1 to create a new HRNetBasicBlock object from inherited base classes: nn with example: obj = HRNetBasicBlock(inplanes, planes, stride, downsample)