parameters: (self, *cu_biases)
return_statement: return (b_wi + b_wh,)
docstring: r"""Stitching cudnn canonical biases to generate tf canonical biases.
docstring_summary: r"""Stitching cudnn canonical biases to generate tf canonical biases.
docstring_tokens: r Stitching cudnn canonical biases to generate tf canonical biases .
function: def _cudnn_to_tf_biases(self, *cu_biases):
      r"""Stitching cudnn canonical biases to generate tf canonical biases."""
      # Save only the sum instead of individual biases. When recovering, return
      # two biases each with half the value. Since RNN does not regularize by
      # weight decay, it has no side effect in training or inference.
      b_wi, b_wh = cu_biases
      return (b_wi + b_wh,)
function_tokens: def _cudnn_to_tf_biases ( self , * cu_biases ) : # Save only the sum instead of individual biases. When recovering, return # two biases each with half the value. Since RNN does not regularize by # weight decay, it has no side effect in training or inference. b_wi , b_wh = cu_biases return ( b_wi + b_wh , )