code: def linear_transform_weights(
      input_dim, output_dim, param_list=None, name=""
  ):
      "theano shared variable given input and output dimension"
      weight_inialization = uniform(
          np.sqrt(2.0 / input_dim), (input_dim, output_dim)
      )
      W = theano.shared(weight_inialization, name=name)
  
      assert param_list is not None
  
      param_list.append(W)
      return W
  
imports: from __future__ import absolute_import, print_function, division
  import theano
  import theano.tensor
  import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: linear_transform_weights(input_dim, output_dim, param_list, name) and returns: W