class_docstr: ResNet-18 (V1).
class_docstr_tok: ["ResNet-18","(","V1",")","."]
code: def __init__(self, feature_dims):
      super(Resnet18, self).__init__()
      self.conv1 = keras.layers.Conv2D(
          64, 7, strides=2, padding="same", use_bias=False
      )
      self.bn1 = keras.layers.BatchNormalization()
      self.relu1 = keras.layers.ReLU()
      self.maxpool = keras.layers.MaxPooling2D(
          3, strides=2, padding="same"
      )
      layers = [2, 2, 2, 2]
  
      self.layer1 = ResLayer(BasicBlock, 64, 64, layers[0])
      self.layer2 = ResLayer(BasicBlock, 64, 128, layers[1], stride=2)
      self.layer3 = ResLayer(BasicBlock, 128, 256, layers[2], stride=2)
      self.layer4 = ResLayer(BasicBlock, 256, 512, layers[3], stride=2)
  
      self.fc = keras.layers.Dense(feature_dims, activation=None)
  
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 Resnet18 object from inherited base classes: keras with example: obj = Resnet18(feature_dims)