code: def __init__(self, out_channel, strides=1, downsample=None, **kwargs):
      super(BasicBlock, self).__init__(**kwargs)
      self.conv1 = layers.Conv2D(
          out_channel,
          kernel_size=3,
          strides=strides,
          padding="SAME",
          use_bias=False,
      )
      self.bn1 = layers.BatchNormalization(momentum=0.9, epsilon=1e-5)
      # -----------------------------------------
      self.conv2 = layers.Conv2D(
          out_channel,
          kernel_size=3,
          strides=1,
          padding="SAME",
          use_bias=False,
      )
      self.bn2 = layers.BatchNormalization(momentum=0.9, epsilon=1e-5)
      # -----------------------------------------
      self.downsample = downsample
      self.relu = layers.ReLU()
      self.add = layers.Add()
  
file_path: deep-learning-for-image-processing/tensorflow_classification/Test5_resnet/model.py
imports: from tensorflow.keras import layers, Model, Sequential
label_desc: Use image node_id 1 to create a new BasicBlock object from inherited base classes: layers with example: obj = BasicBlock(out_channel, strides, downsample)