def _validate_embedded_fixed_features(comp):
"""Checks that the embedded fixed features of |comp| are set up properly."""
for feature in comp.spec.fixed_feature:
check.Gt(feature.embedding_dim, 0,
'Embeddings requested for non-embedded feature: %s' % feature)
if feature.is_constant:
check.IsTrue(feature.HasField('pretrained_embedding_matrix'),
'Constant embeddings must be pretrained: %s' % feature)
def __init__(self, component):
"""Initializes weights and layers.
Args:
component: Parent ComponentBuilderBase object.
"""
super(BiaffineLabelNetwork, self).__init__(component)
parameters = component.spec.network_unit.parameters
self._num_labels = int(parameters['num_labels'])
check.Gt(self._num_labels, 0, 'Expected some labels')
check.Eq(len(self._fixed_feature_dims.items()), 0,
'Expected no fixed features')
check.Eq(len(self._linked_feature_dims.items()), 2,
'Expected two linked features')
check.In('sources', self._linked_feature_dims,
'Missing required linked feature')
check.In('targets', self._linked_feature_dims,
'Missing required linked feature')
self._source_dim = self._linked_feature_dims['sources']
self._target_dim = self._linked_feature_dims['targets']
# TODO(googleuser): Make parameter initialization configurable.
self._weights = []
self._weights.append(
tf.get_variable(
'weights_pair',
[self._num_labels, self._source_dim, self._target_dim],
tf.float32,
tf.random_normal_initializer(stddev=1e-4, seed=self._seed)))
self._weights.append(
tf.get_variable(
'weights_source', [self._num_labels, self._source_dim],
tf.float32,
tf.random_normal_initializer(stddev=1e-4, seed=self._seed)))
self._weights.append(
tf.get_variable(
'weights_target', [self._num_labels, self._target_dim],
tf.float32,
tf.random_normal_initializer(stddev=1e-4, seed=self._seed)))
self._biases = []
self._biases.append(
tf.get_variable(
'biases', [self._num_labels], tf.float32,
tf.random_normal_initializer(stddev=1e-4, seed=self._seed)))
self._params.extend(self._weights + self._biases)
self._regularized_weights.extend(self._weights)
self._layers.append(
network_units.Layer(self, 'labels', self._num_labels))
def testCheckGt(self):
check.Gt(2, 1, 'foo')
with self.assertRaisesRegexp(ValueError, 'bar'):
check.Gt(1, 1, 'bar')
with self.assertRaisesRegexp(RuntimeError, 'baz'):
check.Gt(-1, 1, 'baz', RuntimeError)
