code: def initial_conv(input):
      x = keras.layers.Convolution2D(
          16,
          (3, 3),
          padding="same",
          kernel_initializer="he_normal",
          kernel_regularizer=keras.regularizers.l2(weight_decay),
          use_bias=False,
      )(input)
  
      channel_axis = (
          1 if K.image_data_format() == "channels_first" else -1
      )
  
      x = keras.layers.BatchNormalization(
          axis=channel_axis,
          momentum=0.1,
          epsilon=1e-5,
          gamma_initializer="uniform",
      )(x)
      x = keras.layers.Activation("relu")(x)
      return x
  
imports: from ..imports import *
label_desc: Use image node_id 1 for calling a global function with example usage: initial_conv(input) and returns: x