def get_controls(self, amplitudes, harmonic_distribution, f0_hz):
"""Convert network output tensors into a dictionary of synthesizer controls.
Args:
amplitudes: 3-D Tensor of synthesizer controls, of shape
[batch, time, 1].
harmonic_distribution: 3-D Tensor of synthesizer controls, of shape
[batch, time, n_harmonics].
f0_hz: Fundamental frequencies in hertz. Shape [batch, time, 1].
Returns:
controls: Dictionary of tensors of synthesizer controls.
"""
# Scale the amplitudes.
if self.scale_fn is not None:
amplitudes = self.scale_fn(amplitudes)
harmonic_distribution = self.scale_fn(harmonic_distribution)
# Bandlimit the harmonic distribution.
if self.normalize_below_nyquist:
n_harmonics = int(harmonic_distribution.shape[-1])
harmonic_frequencies = core.get_harmonic_frequencies(
f0_hz, n_harmonics)
harmonic_distribution = core.remove_above_nyquist(
harmonic_frequencies, harmonic_distribution, self.sample_rate)
# Normalize
harmonic_distribution /= tf.reduce_sum(harmonic_distribution,
axis=-1,
keepdims=True)
return {
'amplitudes': amplitudes,
'harmonic_distribution': harmonic_distribution,
'f0_hz': f0_hz
}
def get_controls(self, amplitudes, frequencies):
"""Convert network output tensors into a dictionary of synthesizer controls.
Args:
amplitudes: 3-D Tensor of synthesizer controls, of shape
[batch, time, n_sinusoids].
frequencies: 3-D Tensor of synthesizer controls, of shape
[batch, time, n_sinusoids]. Expects strictly positive in Hertz.
Returns:
controls: Dictionary of tensors of synthesizer controls.
"""
# Scale the inputs.
if self.amp_scale_fn is not None:
amplitudes = self.amp_scale_fn(amplitudes)
if self.freq_scale_fn is not None:
frequencies = self.freq_scale_fn(frequencies, scale=self.freq_scale, hz_max=self.hz_max)
amplitudes = core.remove_above_nyquist(frequencies,
amplitudes,
self.sample_rate)
return {'amplitudes': amplitudes,
'frequencies': frequencies}