class_docstr: Building block of resnet.
class_docstr_tok: ["Building","block","of","resnet","."]
code: def __init__(self, planes, stride=1, downsample=False):
      super(BasicBlock, self).__init__()
  
      self.conv1 = keras.layers.Conv2D(
          planes, 3, strides=stride, padding="same", use_bias=False
      )
      self.bn1 = keras.layers.BatchNormalization()
      self.conv2 = keras.layers.Conv2D(
          planes, 3, padding="same", use_bias=False
      )
      self.bn2 = keras.layers.BatchNormalization()
      if downsample:
          self.downsample = downsample
          self.dconv1 = keras.layers.Conv2D(
              planes, 1, strides=stride, padding="same", use_bias=False
          )
          self.dbn1 = keras.layers.BatchNormalization()
      else:
          self.downsample = downsample
  
file_path: graphics/tensorflow_graphics/projects/cvxnet/lib/resnet.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow.compat.v1
label_desc: Use image node_id 1 to create a new BasicBlock object from inherited base classes: keras with example: obj = BasicBlock(planes, stride, downsample)