code: def _create_model_dense(
      features, num_hidden_layers, hidden_layers_dim, num_output_classes
  ):
      with C.layers.default_options(
          init=C.layers.glorot_uniform(), activation=C.sigmoid
      ):
          h = features
          for _ in range(num_hidden_layers):
              h = C.layers.Dense(hidden_layers_dim)(h)
          last_layer = C.layers.Dense(
              num_output_classes, activation=None
          )
  
          return last_layer(h)
  
file_path: CNTK/bindings/python/cntk/contrib/netopt/test/factorization_test.py
imports: import numpy
  import pytest
  import cntk
  import cntk.contrib.netopt.factorization
label_desc: Use image node_id 1 for calling a global function with example usage: _create_model_dense(features, num_hidden_layers, hidden_layers_dim, num_output_classes) and returns: last_layer