def testSerialization(self):
quantize_config = n_bit_registry.DefaultNBitQuantizeConfig(
['kernel'], ['activation'], False,
num_bits_weight=4, num_bits_activation=4)
expected_config = {
'class_name': 'DefaultNBitQuantizeConfig',
'config': {
'weight_attrs': ['kernel'],
'activation_attrs': ['activation'],
'quantize_output': False,
'num_bits_weight': 4,
'num_bits_activation': 4
}
}
serialized_quantize_config = serialize_keras_object(quantize_config)
self.assertEqual(expected_config, serialized_quantize_config)
quantize_config_from_config = deserialize_keras_object(
serialized_quantize_config,
module_objects=globals(),
custom_objects=n_bit_registry._types_dict())
self.assertEqual(quantize_config, quantize_config_from_config)
def testGetsResultQuantizers_EmptyWhenFalse(self):
layer = self._simple_dense_layer()
quantize_config = n_bit_registry.DefaultNBitQuantizeConfig(
[], [], False, num_bits_weight=4, num_bits_activation=4)
output_quantizers = quantize_config.get_output_quantizers(layer)
self.assertEqual([], output_quantizers)
def testGetsResultQuantizers_ReturnsQuantizer(self):
layer = self._simple_dense_layer()
quantize_config = n_bit_registry.DefaultNBitQuantizeConfig(
[], [], True, num_bits_weight=4, num_bits_activation=4)
output_quantizers = quantize_config.get_output_quantizers(layer)
self.assertLen(output_quantizers, 1)
self._assert_activation_quantizers(output_quantizers)
def testSetsQuantizeWeights_ErrorOnWrongShapeOfWeight(self):
layer = self._simple_dense_layer()
quantize_kernel = K.variable(np.ones([1, 2]))
quantize_config = n_bit_registry.DefaultNBitQuantizeConfig(
['kernel'], ['activation'], False,
num_bits_weight=4, num_bits_activation=4)
with self.assertRaises(ValueError):
quantize_config.set_quantize_weights(layer, [quantize_kernel])
def testSetsQuantizeActivations(self):
layer = self._simple_dense_layer()
quantize_activation = keras.activations.relu
quantize_config = n_bit_registry.DefaultNBitQuantizeConfig(
['kernel'], ['activation'], False,
num_bits_weight=4, num_bits_activation=4)
quantize_config.set_quantize_activations(layer, [quantize_activation])
self.assertEqual(layer.activation, quantize_activation)
def testSetsQuantizeWeights(self):
layer = self._simple_dense_layer()
quantize_kernel = K.variable(np.ones(layer.kernel.shape.as_list()))
quantize_config = n_bit_registry.DefaultNBitQuantizeConfig(
['kernel'], ['activation'], False,
num_bits_weight=4, num_bits_activation=4)
quantize_config.set_quantize_weights(layer, [quantize_kernel])
self._assert_kernel_equality(layer.kernel, quantize_kernel)
def testGetsQuantizeActivationsAndQuantizers(self):
layer = self._simple_dense_layer()
quantize_config = n_bit_registry.DefaultNBitQuantizeConfig(
['kernel'], ['activation'], False,
num_bits_weight=4, num_bits_activation=4)
(activations, activation_quantizers) = self._convert_list(
quantize_config.get_activations_and_quantizers(layer))
self._assert_activation_quantizers(activation_quantizers)
self.assertEqual([layer.activation], activations)
def testSetsQuantizeActivations_ErrorOnWrongNumberOfActivations(self):
layer = self._simple_dense_layer()
quantize_activation = keras.activations.relu
quantize_config = n_bit_registry.DefaultNBitQuantizeConfig(
['kernel'], ['activation'], False,
num_bits_weight=4, num_bits_activation=4)
with self.assertRaises(ValueError):
quantize_config.set_quantize_activations(layer, [])
with self.assertRaises(ValueError):
quantize_config.set_quantize_activations(
layer, [quantize_activation, quantize_activation])