class_docstr: Computes a weighted average of the different channels across timesteps.
  Uses 1 parameter pr. channel to compute the attention value for
  a single timestep.
class_docstr_tok: ["Computes","a","weighted","average","of","the","different","channels","across","timesteps",".","Uses","1","parameter","pr",".","channel","to","compute","the","attention","value","for","a","single","timestep","."]
code: def compute_mask(self, input, input_mask=None):
      if isinstance(input_mask, list):
          return [None] * len(input_mask)
      else:
          return None
  
file_path: textgenrnn/textgenrnn/AttentionWeightedAverage.py
imports: from tensorflow.keras.layers import Layer, InputSpec
  from tensorflow.keras import backend
  from tensorflow.keras import initializers
label_desc: Use image node_id 6 for calling the AttentionWeightedAverage obj's underlying member method code with example usage: obj.compute_mask(input, input_mask) and returns: unknown, None