class_docstr: Linear time-varying finite impulse response (LTV-FIR) filter.
class_docstr_tok: ["Linear","time-varying","finite","impulse","response","(","LTV-FIR",")","filter","."]
docstr: Filter audio with LTV-FIR filter.
  
  Args:
    audio: Dry audio. 2-D Tensor of shape [batch, n_samples].
    magnitudes: Magnitudes tensor of shape [batch, n_frames, n_filter_banks].
      Expects float32 that is strictly positive.
  
  Returns:
    signal: Filtered audio of shape [batch, n_samples, 1].
docstr_tok: ["Filter","audio","with","LTV-FIR","filter",".","Args",":","audio",":","Dry","audio",".","2-D","Tensor","of","shape","[","batch",",","n_samples","]",".","magnitudes",":","Magnitudes","tensor","of","shape","[","batch",",","n_frames",",","n_filter_banks","]",".","Expects","float32","that","is","strictly","positive",".","Returns",":","signal",":","Filtered","audio","of","shape","[","batch",",","n_samples",",","1","]","."]
code: def get_signal(self, audio, magnitudes):
      """Filter audio with LTV-FIR filter.
  
      Args:
        audio: Dry audio. 2-D Tensor of shape [batch, n_samples].
        magnitudes: Magnitudes tensor of shape [batch, n_frames, n_filter_banks].
          Expects float32 that is strictly positive.
  
      Returns:
        signal: Filtered audio of shape [batch, n_samples, 1].
      """
      return core.frequency_filter(
          audio, magnitudes, window_size=self.window_size
      )
  
imports: from ddsp import core
  from ddsp import processors
  from ddsp import synths
  import gin
  import tensorflow.compat.v2
label_desc: Use image node_id 3 for calling the FIRFilter obj's underlying member method code with example usage: obj.get_signal(audio, magnitudes) and returns: core