def test_output_is_correct(self):
processor = processors.Add(name='add')
x = tf.zeros((2, 3), dtype=tf.float32) + 1.0
y = tf.zeros((2, 3), dtype=tf.float32) + 2.0
output = processor(x, y)
expected = np.zeros((2, 3), dtype=np.float32) + 3.0
self.assertAllEqual(expected, output)
def test_output_is_correct(self):
processor = processors.Add(name='add')
x = tf.zeros((2, 3), dtype=tf.float32) + 1.0
y = tf.zeros((2, 3), dtype=tf.float32) + 2.0
output = processor(x, y)
with self.cached_session() as sess:
actual = sess.run(output)
expected = np.zeros((2, 3), dtype=np.float32) + 3.0
self.assertAllEqual(expected, actual)
def setUp(self):
"""Create some dummy input data for the chain."""
super().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.
harmonic = synths.Harmonic(name='harmonic')
noise = synths.FilteredNoise(name='noise')
add = processors.Add(name='add')
reverb = effects.Reverb(trainable=True, name='reverb')
# Create DAG for testing.
self.dag = [
(harmonic, ['amps', 'harmonic_distribution', 'f0_hz']),
(noise, ['magnitudes']),
(add, ['noise/signal', 'harmonic/signal']),
(reverb, ['add/signal']),
]
self.expected_outputs = [
'amps',
'harmonic_distribution',
'magnitudes',
'f0_hz',
'target_audio',
'harmonic/signal',
'harmonic/controls/amplitudes',
'harmonic/controls/harmonic_distribution',
'harmonic/controls/f0_hz',
'noise/signal',
'noise/controls/magnitudes',
'add/signal',
'reverb/signal',
'reverb/controls/ir',
'out/signal',
]