def test_output_shape_is_correct(self):
synthesizer = synths.Additive(n_samples=64000,
sample_rate=16000,
scale_fn=None,
normalize_below_nyquist=True)
batch_size = 3
num_frames = 1000
amp = tf.zeros((batch_size, num_frames, 1), dtype=tf.float32) + 1.0
harmonic_distribution = tf.zeros(
(batch_size, num_frames, 16), dtype=tf.float32) + 1.0 / 16
f0_hz = tf.zeros((batch_size, num_frames, 1), dtype=tf.float32) + 16000
output = synthesizer(amp, harmonic_distribution, f0_hz)
self.assertAllEqual([batch_size, 64000], output.shape.as_list())
def setUp(self):
"""Create some dummy input data for the chain."""
super(ProcessorGroupTest, self).setUp()
# Create inputs.
self.n_batch = 4
self.n_frames = 1000
self.n_time = 64000
rand_signal = lambda ch: np.random.randn(self.n_batch, self.n_frames,
ch)
self.nn_outputs = {
'amps': rand_signal(1),
'harmonic_distribution': rand_signal(99),
'magnitudes': rand_signal(256),
'f0_hz': 200 + rand_signal(1),
'target_audio': np.random.randn(self.n_batch, self.n_time)
}
# Create Processors.
additive = synths.Additive(name='additive')
noise = synths.FilteredNoise(name='noise')
add = processors.Add(name='add')
reverb = effects.Reverb(trainable=True, name='reverb')
# Create DAG for testing.
self.dag = [
(additive, ['amps', 'harmonic_distribution', 'f0_hz']),
(noise, ['magnitudes']),
(add, ['noise/signal', 'additive/signal']),
(reverb, ['add/signal']),
]
self.expected_outputs = [
'amps',
'harmonic_distribution',
'magnitudes',
'f0_hz',
'target_audio',
'additive/signal',
'additive/controls/amplitudes',
'additive/controls/harmonic_distribution',
'additive/controls/f0_hz',
'noise/signal',
'noise/controls/magnitudes',
'add/signal',
'reverb/signal',
'reverb/controls/ir',
'processor_group/signal',
]