def make_empty_classifier(id="", data_id=None, component_id=None):
message = fcm.Classifier()
message.id = id # id is mandatory
if component_id is not None:
message.component_id = component_id
if data_id is not None:
message.data_id = data_id
return message
def make_merger(id, merged_ids, merge_type=None):
message = fcm.Merger()
message.id = id
for c in merged_ids:
message.merged_ids.append(c)
if merge_type is not None:
message.merge_type = merge_type
return message
def make_trigger(id, classifier, component_ids, model=None):
message = fcm.Trigger()
message.id = id
if model is not None:
message.model = model
message.classifier.CopyFrom(classifier) # Classifier has to be trained
for component_id in component_ids:
message.component_ids.append(component_id)
return message
def make_classifier(id, classifier_file, component_id=None, data_id=None):
message = fcm.Classifier()
message.id = id
message.classifier_file = classifier_file
if data_id is not None:
message.data_id = data_id
if component_id is not None:
message.component_id = component_id
return message
def make_data(id, num_train, num_test, label_name=None, source=None):
message = fcm.Data()
message.id = id
message.num_train = num_train
message.num_test = num_test
if source is not None:
message.source.CopyFrom(source)
if label_name is not None:
message.label_name.extend(label_name)
return message
def __init__(self, verbose=True):
self.system_serialized = fcm.System().SerializeToString()
self.verbose = verbose
self.metrics = {}
self.start = "" # Indicates the beginning of the graph/ensemble
def __deserialize(self):
system = fcm.System()
system.ParseFromString(self.system_serialized)
return system
def make_empty_trigger(id, component_ids):
message = fcm.Trigger()
message.id = id
for component_id in component_ids:
message.component_ids.append(component_id)
return message
import numpy as np
import Source.protobuf.make_util as make_util
import Source.io_util as io_util
import Source.protobuf.FastComposedModels_pb2 as fcm
if __name__ == '__main__':
# Load RAW(!) classifier
# OLD AND NEW.
name = "/dataT/eid/GIT/tpml/ml_experiments/001interns/demo_classifier"
# name = "/dataT/eid/GIT/tpml/ml_experiments/001interns/demo_classifier_v001"
msg = fcm.ClassifierRawData()
io_util.read_message(name, msg)
print(msg)