code: def _add_uniform_scaling_initializer_transformer(
      parent, node, full_name, name, logs
  ):
      """Updates references to uniform_unit_scaling_initializer.
  
      Transforms:
      tf.uniform_unit_scaling_initializer(factor, seed, dtype) to
      tf.compat.v1.keras.initializers.VarianceScaling(
          scale=factor, distribution="uniform", seed=seed)
  
      Note: to apply this transformation, symbol must be added
      to reordered_function_names above.
      """
      for keyword_arg in node.keywords:
          if keyword_arg.arg == "factor":
              keyword_arg.arg = "scale"
  
      distribution_value = '"uniform"'
      # Parse with pasta instead of ast to avoid emitting a spurious trailing \n.
      ast_value = pasta.parse(distribution_value)
      node.keywords.append(
          ast.keyword(arg="distribution", value=ast_value)
      )
  
      lineno = node.func.value.lineno
      col_offset = node.func.value.col_offset
      node.func.value = ast_edits.full_name_node(
          "tf.compat.v1.keras.initializers"
      )
      node.func.value.lineno = lineno
      node.func.value.col_offset = col_offset
      node.func.attr = "VarianceScaling"
      return node
  
imports: import ast
  import copy
  import functools
  import sys
  import pasta
  from tensorflow.tools.compatibility import all_renames_v2
  from tensorflow.tools.compatibility import ast_edits
  from tensorflow.tools.compatibility import module_deprecations_v2
  from tensorflow.tools.compatibility import reorders_v2
label_desc: Use image node_id 18 for calling a global function with example usage: _add_uniform_scaling_initializer_transformer(parent, node, full_name, name, logs) and returns: node