class_docstr: Initialize to the identity kernel with the given shape.
  
  This creates an n-D kernel suitable for `SignalConv*` with the requested
  support that produces an output identical to its input (except possibly at the
  signal boundaries).
  
  Note: The identity initializer in `tf.keras.initializers` is only suitable for
  matrices, not for n-D convolution kernels (i.e., no spatial support).
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code: def get_config(self):
      config = super().get_config()
      config.update(gain=self.gain)
      return config
  
imports: import tensorflow
label_desc: Use image node_id 3 for calling the IdentityInitializer obj's underlying member method code with example usage: obj.get_config() and returns: config