class_docstr: String Proccesor() objects together into a processor_group.
class_docstr_tok: ["String","Proccesor","(",")","objects","together","into","a","processor_group","."]
docstr: Run the DAG and get complete outputs dictionary for the processor_group.
  
  Args:
    inputs: A dictionary of input tensors fed to the signal processing
      processor_group.
    **kwargs: Other kwargs for all the modules in the dag.
  
  Returns:
    A nested dictionary of all the output tensors.
docstr_tok: ["Run","the","DAG","and","get","complete","outputs","dictionary","for","the","processor_group",".","Args",":","inputs",":","A","dictionary","of","input","tensors","fed","to","the","signal","processing","processor_group",".","*","*","kwargs",":","Other","kwargs","for","all","the","modules","in","the","dag",".","Returns",":","A","nested","dictionary","of","all","the","output","tensors","."]
code: def get_controls(self, inputs: TensorDict, **kwargs) -> TensorDict:
      """Run the DAG and get complete outputs dictionary for the processor_group.
  
      Args:
        inputs: A dictionary of input tensors fed to the signal processing
          processor_group.
        **kwargs: Other kwargs for all the modules in the dag.
  
      Returns:
        A nested dictionary of all the output tensors.
      """
      # Also build layer on get_controls(), instead of just __call__().
      self.built = True
      return super().call(inputs, **kwargs)
  
imports: from typing import Dict, Text
  from ddsp import core
  from ddsp import dags
  import gin
  import tensorflow
label_desc: Use image node_id 4 for calling the ProcessorGroup obj's underlying member method code with example usage: obj.get_controls(inputs) and returns: super