code: def baseline_model():
      """Build, compile and train the baseline model."""
      base_model_epoch = 1
      model = _build_model()
      callbacks = []
      model = _train_model(model, callbacks, base_model_epoch)
  
      return model
  
imports: import numpy
  import tensorflow
  from tensorflow_model_optimization.python.core.clustering.keras import cluster
  from tensorflow_model_optimization.python.core.clustering.keras import cluster_config
  from tensorflow_model_optimization.python.core.clustering.keras.experimental import cluster
  from tensorflow_model_optimization.python.core.quantization.keras import quantize
  from tensorflow_model_optimization.python.core.quantization.keras.collab_opts.cluster_preserve import cluster_utils
  from tensorflow_model_optimization.python.core.quantization.keras.collab_opts.cluster_preserve import default_8bit_cluster_preserve_quantize_scheme
  from tensorflow_model_optimization.python.core.sparsity.keras import prune
  from tensorflow_model_optimization.python.core.sparsity.keras import pruning_callbacks
  from tensorflow_model_optimization.python.core.sparsity.keras import pruning_schedule
label_desc: Use image node_id 4 for calling a global function with example usage: baseline_model() and returns: model