code: def parse_default_keras_layer(keras_layer, input_names):
      layer = {}
  
      # Extract name for finding weights and biases
      layer["name"] = keras_layer["config"]["name"]
      layer["class_name"] = keras_layer["class_name"]
      if input_names is not None:
          layer["inputs"] = input_names
  
      layer["data_format"] = keras_layer["config"].get(
          "data_format", "channels_last"
      )
  
      if "activation" in keras_layer["config"]:
          layer["activation"] = keras_layer["config"]["activation"]
      if "epsilon" in keras_layer["config"]:
          layer["epsilon"] = keras_layer["config"]["epsilon"]
      if "use_bias" in keras_layer["config"]:
          layer["use_bias"] = keras_layer["config"]["use_bias"]
  
      return layer
  
imports: import json
  import h5py
  from hls4ml.model import ModelGraph
label_desc: Use image node_id 5 for calling a global function with example usage: parse_default_keras_layer(keras_layer, input_names) and returns: layer