def testTrainClassifierNonInMemory(self):
ops.reset_default_graph()
expected_first, expected_second, expected_third = (
self._get_expected_ensembles_for_classification())
with self.test_session() as sess:
# Train without train_in_memory mode.
with sess.graph.as_default():
train_op, ensemble_serialized = self._get_train_op_and_ensemble(
boosted_trees._create_classification_head(n_classes=2),
run_config.RunConfig(),
is_classification=True,
train_in_memory=False)
_, serialized = sess.run([train_op, ensemble_serialized])
# Validate the trained ensemble.
ensemble_proto = boosted_trees_pb2.TreeEnsemble()
ensemble_proto.ParseFromString(serialized)
self.assertProtoEquals(expected_first, ensemble_proto)
# Run one more time and validate the trained ensemble.
_, serialized = sess.run([train_op, ensemble_serialized])
ensemble_proto = boosted_trees_pb2.TreeEnsemble()
ensemble_proto.ParseFromString(serialized)
self.assertProtoEquals(expected_second, ensemble_proto)
# Third round training and validation.
_, serialized = sess.run([train_op, ensemble_serialized])
ensemble_proto = boosted_trees_pb2.TreeEnsemble()
ensemble_proto.ParseFromString(serialized)
self.assertProtoEquals(expected_third, ensemble_proto)
def testTrainClassifierNonInMemory(self):
ops.reset_default_graph()
expected_first, expected_second, expected_third = (
self._get_expected_ensembles_for_classification())
with self.test_session() as sess:
# Train without train_in_memory mode.
with sess.graph.as_default():
train_op, ensemble_serialized = self._get_train_op_and_ensemble(
boosted_trees._create_classification_head(n_classes=2),
run_config.RunConfig(),
is_classification=True,
train_in_memory=False)
_, serialized = sess.run([train_op, ensemble_serialized])
# Validate the trained ensemble.
ensemble_proto = boosted_trees_pb2.TreeEnsemble()
ensemble_proto.ParseFromString(serialized)
self.assertProtoEquals(expected_first, ensemble_proto)
# Run one more time and validate the trained ensemble.
_, serialized = sess.run([train_op, ensemble_serialized])
ensemble_proto = boosted_trees_pb2.TreeEnsemble()
ensemble_proto.ParseFromString(serialized)
self.assertProtoEquals(expected_second, ensemble_proto)
# Third round training and validation.
_, serialized = sess.run([train_op, ensemble_serialized])
ensemble_proto = boosted_trees_pb2.TreeEnsemble()
ensemble_proto.ParseFromString(serialized)
self.assertProtoEquals(expected_third, ensemble_proto)