class Precision_16_32Test(unittest.TestCase):
def setUp(self):
self.precision_instance = Precision('16.32')
def test_half_precision_instanciation(self):
assert (self.precision_instance.compute_precision == tf.float16)
assert (self.precision_instance.weight_update_precision == tf.float32)
def test_set_precision(self):
self.precision_instance.apply()
input_layer = tf.keras.layers.Input(shape=(None, 1))
layer = tf.keras.layers.Dense(1)
assert (layer.compute_dtype == tf.float16)
output = layer(input_layer)
assert (output.dtype == tf.float16)
model = tf.keras.Model(inputs=input_layer, outputs=output)
with tf.GradientTape() as tape:
input_data = np.array([[1]])
output_data = model(input_data)
grad = tape.gradient(output_data, model.trainable_variables)
# note gradients dtype are tf.float32
assert (all([g.dtype == tf.float32 for g in grad]))
# note that model weights are also tf.float32
assert (all(
[var.dtype == tf.float32 for var in model.trainable_variables]))
class Precision32_32Test(unittest.TestCase):
def setUp(self):
self.precision_instance = Precision('32.32')
def test_full_precision_instantiation(self):
assert (self.precision_instance.compute_precision == tf.float32)
assert (self.precision_instance.weight_update_precision == tf.float32)
def test_set_precision(self):
self.precision_instance.apply()
input_layer = tf.keras.layers.Input(shape=(1))
layer = tf.keras.layers.Dense(1)
assert (layer.dtype == tf.float32)
output = layer(input_layer)
assert (output.dtype == tf.float32)
model = tf.keras.Model(inputs=input_layer, outputs=output)
with tf.GradientTape() as tape:
input_data = np.array([[1]])
output_data = model(input_data)
grads = tape.gradient(output_data, model.trainable_variables)
assert (all([g.dtype == tf.float32 for g in grads]))
def test_mixed_precision(self):
mixed_precision = Precision('16.32')
mixed_precision.apply()
model = self.get_model()
computed_value = model(self.input_value).numpy()
# checking for underflow
self.assertNotAlmostEqual(self.expected_value[0][0],
computed_value[0][0],
places=10)
def test_full_precision(self):
full_precision = Precision('32.32')
full_precision.apply()
model = self.get_model()
computed_value = model(self.input_value).numpy()
# checking it did NOT underflow
self.assertAlmostEqual(self.expected_value[0][0],
computed_value[0][0],
places=10)
