class_docstr: Demodulation layer for StyleGAN.
  
  This layer applies the Demodulated Convolution layer from StyleGANv2
  that is used in the paper "
  Analyzing and Improving the Image Quality of StyleGAN".
  https://arxiv.org/pdf/1912.04958.pdf
  
  It takes in the style input and applies demodulation on the features.
class_docstr_tok: ["Demodulation","layer","for","StyleGAN",".","This","layer","applies","the","Demodulated","Convolution","layer","from","StyleGANv2","that","is","used","in","the","paper","``","Analyzing","and","Improving","the","Image","Quality","of","StyleGAN","''",".","https",":","\/\/arxiv.org\/pdf\/1912.04958.pdf","It","takes","in","the","style","input","and","applies","demodulation","on","the","features","."]
docstr: Returns the config of the layer.
docstr_tok: ["Returns","the","config","of","the","layer","."]
code: def get_config(self) -> Dict[str, Any]:
      """Returns the config of the layer."""
      config = {
          "kernel_size": self._kernel_size,
          "filters": self._filters,
          "kernel_initializer": serialize_keras_object(
              self._kernel_initializer
          ),
          "bias_initializer": serialize_keras_object(
              self._bias_initializer
          ),
      }
      base_config = super().get_config()
      base_config.update(config)
      return base_config
  
imports: import math
  from typing import Any, Callable, Dict, Optional, Sequence, Tuple, Union, List
  import numpy
  import tensorflow
label_desc: Use image node_id 4 for calling the DemodulatedConvolution obj's underlying member method code with example usage: obj.get_config() and returns: base_config