def run_graph(spin):
graph = erdos.graph.get_current_graph()
first = graph.add(FirstOp, name='first')
second = graph.add(SecondOp, name='second', init_args={'spin': spin})
graph.connect([first], [second])
graph.connect([second], [first])
graph.execute(FLAGS.framework)
def run_graph(argv):
"""Sums the squares of 2 numbers. """
graph = erdos.graph.get_current_graph()
sub_graph = graph.add(SumSquaresGraph, name="sum_squares")
# Add operators
int1 = graph.add(IntegerOp,
name="int1",
init_args={
"number": 1,
"stream_name": "int1_out"
},
setup_args={"stream_name": "int1_out"})
int2 = graph.add(IntegerOp,
name="int2",
init_args={
"number": 2,
"stream_name": "int2_out"
},
setup_args={"stream_name": "int2_out"})
square_op = graph.add(SquareOp, name="default_square")
# Connect operators
graph.connect([int1, int2], [sub_graph])
graph.connect([sub_graph], [square_op])
# Execute graph
graph.execute(FLAGS.framework)
def run_graph(n_pub, n_sub, spin):
graph = erdos.graph.get_current_graph()
# Add publishers
publishers = []
for i in range(n_pub):
pub = graph.add(PublisherOp, name='publisher_%d' % i)
publishers.append(pub)
# Add subscribers
subscribers = []
for i in range(n_sub):
sub = graph.add(
SubscriberOp,
name='subscriber_%d' % i,
init_args={
'num_pub_ops': n_pub,
'spin': spin
})
subscribers.append(sub)
# Connect operators
graph.connect(publishers, subscribers)
# Execute graph
graph.execute(FLAGS.framework)
def add_object_tracking_op(graph, carla_op, obj_detector_ops):
tracker_op = None
name = 'tracker_' + FLAGS.tracker_type
setup_args = {'output_stream_name': 'tracker_stream'}
init_args = {
'output_stream_name': 'tracker_stream',
'tracker_type': FLAGS.tracker_type,
'flags': FLAGS,
'log_file_name': FLAGS.log_file_name,
'csv_file_name': FLAGS.csv_log_file_name
}
if FLAGS.tracker_type == 'cv2':
# Doesn't require a GPU.
tracker_op = graph.add(ObjectTrackerOp,
name=name,
setup_args=setup_args,
init_args=init_args)
else:
# Other trackers require a GPU.
tracker_op = graph.add(
ObjectTrackerOp,
name=name,
setup_args=setup_args,
init_args=init_args,
_resources={"GPU": FLAGS.obj_tracking_gpu_memory_fraction})
graph.connect([carla_op] + obj_detector_ops, [tracker_op])
return tracker_op
def analyze_frequency(graph, file_name, output_file_name):
log_reader_op = graph.add(
LogReaderOp,
'log_reader',
init_args={
'output_name': 'log_reader',
'log_file_name': file_name
},
setup_args={'output_name': 'log_reader'})
frequency_jitter_op = graph.add(
WindowOp,
name='frequency_jitter_op',
init_args={
'output_stream_name': 'frequency_jitter_stream',
'assigner': SliddingCountWindowAssigner(2),
'trigger': CountWindowTrigger(2),
'processor': FrequencyMissProcessor()
},
setup_args={'output_stream_name': 'frequency_jitter_stream'})
file_writer_op = graph.add(
FileWriterOp,
name='frequency_file_op',
init_args={'file_name': output_file_name})
graph.connect([log_reader_op], [frequency_jitter_op])
graph.connect([frequency_jitter_op], [file_writer_op])
def add_localization_graph(graph, front_locations, tracker_ops):
# 1 LIDAR, 100000 points per point cloud.
lidar_op = graph.add(LidarOperator,
name='lidar',
init_args={
'num_points': 100000,
'buffer_logs': FLAGS.buffer_logs
},
setup_args={'op_name': 'lidar'})
# 1 GPS
gps_op = graph.add(GPSOperator,
name='GPS',
init_args={'buffer_logs': FLAGS.buffer_logs})
# 1 IMU
imu_op = graph.add(
IMUOperator,
name='IMU',
init_args={'buffer_logs': FLAGS.buffer_logs},
)
# 4 short range radars
short_radars = ['front_left', 'front_right', 'rear_left', 'rear_right']
short_radar_ops = []
for location in short_radars:
radar_name = 'short_radar_' + location
short_radar_ops.append(add_radar_op(graph, radar_name))
# 1 long range radar
long_radar_op = add_radar_op(graph, 'long_radar')
# 1 SLAM operator.
slam_op = graph.add(SLAMOperator,
name='SLAM',
init_args={
'min_runtime_us': 1,
'max_runtime_us': 100,
'buffer_logs': FLAGS.buffer_logs
})
# 3 depth cameras
depth_camera_ops = []
for location in front_locations:
depth_camera_ops.append(
add_depth_camera_op(graph, 'depth_camera_' + location))
# fusion operator
fusion_op = graph.add(FusionOperator,
name='fusion',
init_args={
'min_runtime_us': 1,
'max_runtime_us': 100,
'buffer_logs': FLAGS.buffer_logs
})
graph.connect([lidar_op, long_radar_op, gps_op, imu_op], [slam_op])
graph.connect([slam_op, lidar_op] + tracker_ops + short_radar_ops +
depth_camera_ops, [fusion_op])
return (slam_op, fusion_op)
def run_graph(spin):
graph = erdos.graph.get_current_graph()
first_graph = graph.add(FirstGraph, name='first_graph')
second_graph = graph.add(SecondGraph,
name='second_graph',
setup_args={'spin': spin})
graph.connect([first_graph], [second_graph])
graph.connect([second_graph], [first_graph])
graph.execute(FLAGS.framework)
def main():
# Create operators
graph = erdos.graph.get_current_graph()
car_racing_op = graph.add(CarRacingOp, name='car_racing')
action_op = graph.add(ActionOp, name='action')
# Add connect streams to operators for cyclical graph
graph.connect([car_racing_op], [action_op])
graph.connect([action_op], [car_racing_op])
# Execute graph
graph.execute("ray")
def main(argv):
# Set up graph
graph = erdos.graph.get_current_graph()
# Add operators
input_op = graph.add(InputOperator, name='input_op')
push_op = graph.add(PushOperator, name='push_op')
# Connect graph
graph.connect([input_op], [push_op])
# Execute graph
graph.execute(FLAGS.framework)
def main(argv):
# Set up the graph.
graph = erdos.graph.get_current_graph()
# Add the operators.
source_op_1 = graph.add(SourceOperator, name = "FirstOperator")
debug_op_1 = graph.add(DebugOperator, name = "DebugOperator")
sink_op_1 = graph.add(SinkOperator, name = "SinkOperator")
# Connect the operators.
graph.connect([source_op_1], [debug_op_1])
graph.connect([debug_op_1], [sink_op_1])
# Execute the graph.
graph.execute('ray')
def run_graph():
"""Sums the squares of 2 numbers. """
# Set up graph
graph = erdos.graph.get_current_graph()
# Add operators
sum_squares_graph = graph.add(SumSquaresGraph, name='sum_squares')
square_op = graph.add(SquareOp, name='square')
# Connect Operators
graph.connect([sum_squares_graph], [square_op])
# Execute graph
graph.execute(FLAGS.framework)
def main(argv):
graph = erdos.graph.get_current_graph()
publish_op_one = graph.add(PublisherOperator,
name='publish_op_one',
init_args={'text': 'publish-one'})
publish_op_two = graph.add(PublisherOperator,
name='publish_op_two',
init_args={'text': 'publish-two'})
subscriber_with_print_op = graph.add(SubscriberWithPrintOperator,
name='subscriber_with_print')
subscriber_without_print_op = graph.add(SubscriberWithoutPrintOperator,
name='subscriber_without_print')
graph.connect([publish_op_one], [subscriber_with_print_op])
graph.connect([publish_op_two], [subscriber_without_print_op])
graph.execute(FLAGS.framework)
def add_detector_ops(graph, carla_op):
detector_ops = []
if FLAGS.detector_ssd_mobilenet_v1:
detector_ops.append(
add_detector_op_helper(
graph, 'detector_ssd_mobilenet_v1',
'dependencies/data/ssd_mobilenet_v1_coco_2018_01_28/frozen_inference_graph.pb',
FLAGS.obj_detection_gpu_memory_fraction))
if FLAGS.detector_frcnn_resnet101:
detector_ops.append(
add_detector_op_helper(
graph, 'detector_faster_rcnn_resnet101',
'dependencies/data/faster_rcnn_resnet101_coco_2018_01_28/frozen_inference_graph.pb',
FLAGS.obj_detection_gpu_memory_fraction))
if FLAGS.detector_ssd_resnet50_v1:
detector_ops.append(
add_detector_op_helper(
graph, 'detector_ssd_resnet50_v1',
'dependencies/data/ssd_resnet50_v1_fpn_shared_box_predictor_640x640_coco14_sync_2018_07_03/frozen_inference_graph.pb',
FLAGS.obj_detection_gpu_memory_fraction))
if FLAGS.detector_center_net:
obj_det_op = graph.add(DetectionCenterNetOperator,
name='detector_center_net',
setup_args={'output_stream_name': 'obj_stream'},
init_args={
'output_stream_name': 'obj_stream',
'flags': FLAGS,
'log_file_name': FLAGS.log_file_name,
'csv_file_name': FLAGS.csv_log_file_name
})
detector_ops.append(obj_det_op)
graph.connect([carla_op], detector_ops)
return detector_ops
def add_record_op(graph, carla_op, name, filename, filter_name):
record_op = graph.add(RecordOp,
name=name,
init_args={'filename': filename},
setup_args={'filter_name': filter_name})
graph.connect([carla_op], [record_op])
return record_op
def add_lidar_record_op(graph, carla_op):
record_lidar_op = graph.add(
RecordOp,
name='record_lidar',
init_args={'filename': 'pylot_lidar_data.erdos'},
setup_args={'filter': 'lidar'})
graph.connect([carla_op], [record_lidar_op])
return record_lidar_op
def main(argv):
# Set up the graph.
graph = erdos.graph.get_current_graph()
# Add the operators.
source_op = graph.add(FirstOperator,
name="gen_op",
init_args={'batch_size': 10})
sum_op = graph.add(SecondOperator, name="sum_op")
assert_op = graph.add(ThirdOperator, name="assert_op")
# Connect the operators.
graph.connect([source_op], [sum_op])
graph.connect([sum_op], [assert_op])
# Execute the graph.
graph.execute('ray')
def add_lidar_visualizer_op(graph, carla_op):
lidar_visualizer_op = graph.add(LidarVisualizerOperator,
name='lidar_visualizer',
init_args={
'flags': FLAGS,
'log_file_name': FLAGS.log_file_name
})
graph.connect([carla_op], [lidar_visualizer_op])
def run_graph(argv):
# Extract variables
num_messages = int(FLAGS.num_msg)
fps = int(FLAGS.fps)
fail_time = int(FLAGS.fail_time)
state_size = int(FLAGS.state_size)
checkpoint_freq = int(FLAGS.checkpoint_freq)
# Define graph
graph = erdos.graph.get_current_graph()
source_op = graph.add(
Source,
name='source',
init_args={'num_messages': num_messages,
'fps': fps,
'checkpoint_freq': checkpoint_freq}
)
failure_op = graph.add(
FailureOperator,
name='primary_failure',
init_args={'state_size': state_size,
'checkpoint_freq': checkpoint_freq})
sink_op = graph.add(
Sink,
name='sink',
init_args={'state_size': state_size,
'checkpoint_freq': checkpoint_freq}
)
controller_op = graph.add(
ControllerOperator,
name='controller',
init_args={'pre_failure_time_elapse_s': fail_time})
# Connect Graph
graph.connect([source_op], [failure_op])
graph.connect([failure_op], [sink_op])
graph.connect([sink_op], [controller_op])
graph.connect([controller_op], [source_op, failure_op, sink_op])
# Execute Graph
graph.execute(FLAGS.framework)
def add_fusion_ops(graph, carla_op, obj_detector_ops):
fusion_op = graph.add(FusionOperator,
name='fusion',
setup_args={'output_stream_name': 'fusion_vehicles'},
init_args={
'flags': FLAGS,
'output_stream_name': 'fusion_vehicles',
'log_file_name': FLAGS.log_file_name,
'csv_file_name': FLAGS.csv_log_file_name
})
fusion_verification_op = graph.add(
FusionVerificationOperator,
name='fusion_verifier',
init_args={'log_file_name': FLAGS.log_file_name})
graph.connect(obj_detector_ops + [carla_op], [fusion_op])
graph.connect([fusion_op, carla_op], [fusion_verification_op])
return (fusion_op, fusion_verification_op)
def main(argv):
graph = erdos.graph.get_current_graph()
input_ops = []
for i in range(0, 2):
input_op = graph.add(InputOperator, name='input' + str(i))
input_ops.append(input_op)
sync_op = graph.add(SynchronizerLastDataOperator, name='synchronizer')
# sync_op = SynchronizerBestDataOperator()
# sync_op = SynchronizerDataWithinLimitOperator(500)
# TODO(ionel): Implement!
# sync_op = SynchronizerByDeadlineOperator()
# sync_op = SynchronizerBestDataWithDelay()
graph.connect(input_ops, [sync_op])
graph.execute(FLAGS.framework)
def add_segmented_video_op(graph, carla_op):
segmented_video_op = graph.add(SegmentedVideoOperator,
name='segmented_video',
init_args={
'flags': FLAGS,
'log_file_name': FLAGS.log_file_name
})
graph.connect([carla_op], [segmented_video_op])
return segmented_video_op
def add_traffic_sign_det_op(graph, name):
return graph.add(TrafficSignDetOperator,
name=name,
init_args={
'min_runtime_us': 1,
'max_runtime_us': 100,
'buffer_logs': FLAGS.buffer_logs
},
setup_args={'op_name': name})
def add_lane_det_op(graph, name):
return graph.add(LaneDetOperator,
name=name,
init_args={
'min_runtime_us': 1,
'max_runtime_us': 100,
'buffer_logs': FLAGS.buffer_logs
},
setup_args={'op_name': name})
def add_segmentation_op(graph, name):
return graph.add(SegmentationOperator,
name=name,
init_args={
'min_runtime_us': 1,
'max_runtime_us': 100,
'buffer_logs': FLAGS.buffer_logs
},
setup_args={'op_name': name})
def main(argv):
# Set up the graph.
graph = erdos.graph.get_current_graph()
# Add the operators.
source_op_1 = graph.add(
SourceOperator,
name="FirstOperator",
init_args={
'batch_size': BATCH_SIZE,
'send_batch': lambda x: x % 2 == True,
'output_stream_name': 'first-stream',
},
setup_args={
'output_stream_name': 'first-stream',
})
source_op_2 = graph.add(
SourceOperator,
name="SecondOperator",
init_args={
'batch_size': BATCH_SIZE,
'send_batch': lambda x: x % 2 == False,
'output_stream_name': 'second-stream',
},
setup_args={
'output_stream_name': 'second-stream',
})
release_op = graph.add(
EarlyReleaseOperator,
name="ReleaseOperator",
init_args={
'output_stream_name': 'release-stream',
},
setup_args={
'output_stream_name': 'release-stream',
})
sink_op = graph.add(SinkOperator, name="SinkOperator")
# Connect the operators.
graph.connect([source_op_1, source_op_2], [release_op])
graph.connect([release_op], [sink_op])
# Execute the graph.
graph.execute('ray')
def add_camera_video_op(graph, carla_op, name, filter_name):
video_op = graph.add(VideoOperator,
name=name,
init_args={
'flags': FLAGS,
'log_file_name': FLAGS.log_file_name
},
setup_args={'filter_name': filter_name})
graph.connect([carla_op], [video_op])
return video_op
def create_agent_op(graph, bgr_camera_setup):
agent_op = graph.add(PylotAgentOperator,
name='pylot_agent',
init_args={
'flags': FLAGS,
'bgr_camera_setup': bgr_camera_setup,
'log_file_name': FLAGS.log_file_name,
'csv_file_name': FLAGS.csv_log_file_name
})
return agent_op
def add_prediction_graph(graph, tracker_ops):
prediction_op = graph.add(PredictionOperator,
name='prediction',
init_args={
'min_runtime_us': 1,
'max_runtime_us': 100,
'buffer_logs': FLAGS.buffer_logs
})
graph.connect([prediction_op], tracker_ops)
return [prediction_op]
def add_record_carla_op(graph, carla_op):
input_names = [
'vehicle_pos', 'acceleration', 'forward_speed', 'traffic_lights',
'pedestrians', 'vehicles', 'traffic_signs'
]
record_carla_op = graph.add(
RecordOp,
name='record_carla',
init_args={'filename': 'pylot_carla_data.erdos'},
setup_args={'filter': input_names})
graph.connect([carla_op], [record_carla_op])
def add_detector_op(graph, detector_name):
return graph.add(DetectionOperator,
name=detector_name,
init_args={
'min_runtime_us': 1,
'max_runtime_us': 100,
'min_det_objs': 3,
'max_det_objs': 15,
'buffer_logs': FLAGS.buffer_logs
},
setup_args={'op_name': detector_name})
