def video_job_info(s3_bucket, s3_prefix, aws_region):
dir_path = os.path.dirname(os.path.realpath(__file__))
pip_path = "{}/test_data/pip.mp4".format(dir_path)
mainview_path = "{}/test_data/45degree.mp4".format(dir_path)
topview_path = "{}/test_data/simtrace.mp4".format(dir_path)
for filepath in (pip_path, mainview_path, topview_path):
with open(filepath, "w") as filepointer:
filepointer.write("")
return [IterationData('pip', s3_bucket, s3_prefix, aws_region, pip_path),
IterationData('45degree', s3_bucket, s3_prefix, aws_region, mainview_path),
IterationData('topview', s3_bucket, s3_prefix, aws_region, topview_path)]
def main():
""" Main function for tournament worker """
parser = argparse.ArgumentParser()
parser.add_argument('-p',
'--preset',
help="(string) Name of a preset to run \
(class name from the 'presets' directory.)",
type=str,
required=False)
parser.add_argument('--s3_bucket',
help='list(string) S3 bucket',
type=str,
nargs='+',
default=rospy.get_param("MODEL_S3_BUCKET",
["gsaur-test"]))
parser.add_argument('--s3_prefix',
help='list(string) S3 prefix',
type=str,
nargs='+',
default=rospy.get_param("MODEL_S3_PREFIX",
["sagemaker"]))
parser.add_argument('--aws_region',
help='(string) AWS region',
type=str,
default=rospy.get_param("AWS_REGION", "us-east-1"))
parser.add_argument('--number_of_trials',
help='(integer) Number of trials',
type=int,
default=int(rospy.get_param("NUMBER_OF_TRIALS", 10)))
parser.add_argument(
'-c',
'--local_model_directory',
help='(string) Path to a folder containing a checkpoint \
to restore the model from.',
type=str,
default='./checkpoint')
parser.add_argument('--number_of_resets',
help='(integer) Number of resets',
type=int,
default=int(rospy.get_param("NUMBER_OF_RESETS", 0)))
parser.add_argument('--penalty_seconds',
help='(float) penalty second',
type=float,
default=float(rospy.get_param("PENALTY_SECONDS", 2.0)))
parser.add_argument('--job_type',
help='(string) job type',
type=str,
default=rospy.get_param("JOB_TYPE", "EVALUATION"))
parser.add_argument('--is_continuous',
help='(boolean) is continous after lap completion',
type=bool,
default=utils.str2bool(
rospy.get_param("IS_CONTINUOUS", False)))
parser.add_argument('--race_type',
help='(string) Race type',
type=str,
default=rospy.get_param("RACE_TYPE", "TIME_TRIAL"))
parser.add_argument('--off_track_penalty',
help='(float) off track penalty second',
type=float,
default=float(rospy.get_param("OFF_TRACK_PENALTY",
2.0)))
parser.add_argument('--collision_penalty',
help='(float) collision penalty second',
type=float,
default=float(rospy.get_param("COLLISION_PENALTY",
5.0)))
args = parser.parse_args()
arg_s3_bucket = args.s3_bucket
arg_s3_prefix = args.s3_prefix
logger.info("S3 bucket: %s \n S3 prefix: %s", arg_s3_bucket, arg_s3_prefix)
# tournament_worker: names to be displayed in MP4.
# This is racer alias in tournament worker case.
display_names = rospy.get_param('DISPLAY_NAME', "")
metrics_s3_buckets = rospy.get_param('METRICS_S3_BUCKET')
metrics_s3_object_keys = rospy.get_param('METRICS_S3_OBJECT_KEY')
arg_s3_bucket, arg_s3_prefix = utils.force_list(
arg_s3_bucket), utils.force_list(arg_s3_prefix)
metrics_s3_buckets = utils.force_list(metrics_s3_buckets)
metrics_s3_object_keys = utils.force_list(metrics_s3_object_keys)
validate_list = [
arg_s3_bucket, arg_s3_prefix, metrics_s3_buckets,
metrics_s3_object_keys
]
simtrace_s3_bucket = rospy.get_param('SIMTRACE_S3_BUCKET', None)
mp4_s3_bucket = rospy.get_param('MP4_S3_BUCKET', None)
if simtrace_s3_bucket:
simtrace_s3_object_prefix = rospy.get_param('SIMTRACE_S3_PREFIX')
simtrace_s3_bucket = utils.force_list(simtrace_s3_bucket)
simtrace_s3_object_prefix = utils.force_list(simtrace_s3_object_prefix)
validate_list.extend([simtrace_s3_bucket, simtrace_s3_object_prefix])
if mp4_s3_bucket:
mp4_s3_object_prefix = rospy.get_param('MP4_S3_OBJECT_PREFIX')
mp4_s3_bucket = utils.force_list(mp4_s3_bucket)
mp4_s3_object_prefix = utils.force_list(mp4_s3_object_prefix)
validate_list.extend([mp4_s3_bucket, mp4_s3_object_prefix])
if not all([lambda x: len(x) == len(validate_list[0]), validate_list]):
utils.log_and_exit(
"Eval worker error: Incorrect arguments passed: {}".format(
validate_list), utils.SIMAPP_SIMULATION_WORKER_EXCEPTION,
utils.SIMAPP_EVENT_ERROR_CODE_500)
if args.number_of_resets != 0 and args.number_of_resets < MIN_RESET_COUNT:
raise GenericRolloutException(
"number of resets is less than {}".format(MIN_RESET_COUNT))
# Instantiate Cameras
if len(arg_s3_bucket) == 1:
configure_camera(namespaces=['racecar'])
else:
configure_camera(namespaces=[
'racecar_{}'.format(str(agent_index))
for agent_index in range(len(arg_s3_bucket))
])
agent_list = list()
s3_bucket_dict = dict()
s3_prefix_dict = dict()
s3_writers = list()
# tournament_worker: list of required S3 locations
simtrace_s3_bucket_dict = dict()
simtrace_s3_prefix_dict = dict()
metrics_s3_bucket_dict = dict()
metrics_s3_obect_key_dict = dict()
mp4_s3_bucket_dict = dict()
mp4_s3_object_prefix_dict = dict()
for agent_index, s3_bucket_val in enumerate(arg_s3_bucket):
agent_name = 'agent' if len(arg_s3_bucket) == 1 else 'agent_{}'.format(
str(agent_index))
racecar_name = 'racecar' if len(
arg_s3_bucket) == 1 else 'racecar_{}'.format(str(agent_index))
s3_bucket_dict[agent_name] = arg_s3_bucket[agent_index]
s3_prefix_dict[agent_name] = arg_s3_prefix[agent_index]
# tournament_worker: remap key with agent_name instead of agent_index for list of S3 locations.
simtrace_s3_bucket_dict[agent_name] = simtrace_s3_bucket[agent_index]
simtrace_s3_prefix_dict[agent_name] = simtrace_s3_object_prefix[
agent_index]
metrics_s3_bucket_dict[agent_name] = metrics_s3_buckets[agent_index]
metrics_s3_obect_key_dict[agent_name] = metrics_s3_object_keys[
agent_index]
mp4_s3_bucket_dict[agent_name] = mp4_s3_bucket[agent_index]
mp4_s3_object_prefix_dict[agent_name] = mp4_s3_object_prefix[
agent_index]
s3_client = SageS3Client(bucket=arg_s3_bucket[agent_index],
s3_prefix=arg_s3_prefix[agent_index],
aws_region=args.aws_region)
# Load the model metadata
if not os.path.exists(os.path.join(CUSTOM_FILES_PATH, agent_name)):
os.makedirs(os.path.join(CUSTOM_FILES_PATH, agent_name))
model_metadata_local_path = os.path.join(
os.path.join(CUSTOM_FILES_PATH, agent_name), 'model_metadata.json')
utils.load_model_metadata(
s3_client,
os.path.normpath("%s/model/model_metadata.json" %
arg_s3_prefix[agent_index]),
model_metadata_local_path)
# Handle backward compatibility
_, _, version = parse_model_metadata(model_metadata_local_path)
if float(version) < float(utils.SIMAPP_VERSION) and \
not utils.has_current_ckpnt_name(arg_s3_bucket[agent_index], arg_s3_prefix[agent_index], args.aws_region):
utils.make_compatible(arg_s3_bucket[agent_index],
arg_s3_prefix[agent_index], args.aws_region,
SyncFiles.TRAINER_READY.value)
# Select the optimal model
utils.do_model_selection(s3_bucket=arg_s3_bucket[agent_index],
s3_prefix=arg_s3_prefix[agent_index],
region=args.aws_region)
# Download hyperparameters from SageMaker
if not os.path.exists(agent_name):
os.makedirs(agent_name)
hyperparameters_file_success = False
hyperparams_s3_key = os.path.normpath(arg_s3_prefix[agent_index] +
"/ip/hyperparameters.json")
hyperparameters_file_success = s3_client.download_file(
s3_key=hyperparams_s3_key,
local_path=os.path.join(agent_name, "hyperparameters.json"))
sm_hyperparams_dict = {}
if hyperparameters_file_success:
logger.info("Received Sagemaker hyperparameters successfully!")
with open(os.path.join(agent_name,
"hyperparameters.json")) as file:
sm_hyperparams_dict = json.load(file)
else:
logger.info("SageMaker hyperparameters not found.")
agent_config = {
'model_metadata': model_metadata_local_path,
ConfigParams.CAR_CTRL_CONFIG.value: {
ConfigParams.LINK_NAME_LIST.value: [
link_name.replace('racecar', racecar_name)
for link_name in LINK_NAMES
],
ConfigParams.VELOCITY_LIST.value: [
velocity_topic.replace('racecar', racecar_name)
for velocity_topic in VELOCITY_TOPICS
],
ConfigParams.STEERING_LIST.value: [
steering_topic.replace('racecar', racecar_name)
for steering_topic in STEERING_TOPICS
],
ConfigParams.CHANGE_START.value:
utils.str2bool(rospy.get_param('CHANGE_START_POSITION',
False)),
ConfigParams.ALT_DIR.value:
utils.str2bool(
rospy.get_param('ALTERNATE_DRIVING_DIRECTION', False)),
ConfigParams.ACTION_SPACE_PATH.value:
'custom_files/' + agent_name + '/model_metadata.json',
ConfigParams.REWARD.value:
reward_function,
ConfigParams.AGENT_NAME.value:
racecar_name,
ConfigParams.VERSION.value:
version,
ConfigParams.NUMBER_OF_RESETS.value:
args.number_of_resets,
ConfigParams.PENALTY_SECONDS.value:
args.penalty_seconds,
ConfigParams.NUMBER_OF_TRIALS.value:
args.number_of_trials,
ConfigParams.IS_CONTINUOUS.value:
args.is_continuous,
ConfigParams.RACE_TYPE.value:
args.race_type,
ConfigParams.COLLISION_PENALTY.value:
args.collision_penalty,
ConfigParams.OFF_TRACK_PENALTY.value:
args.off_track_penalty
}
}
metrics_s3_config = {
MetricsS3Keys.METRICS_BUCKET.value:
metrics_s3_buckets[agent_index],
MetricsS3Keys.METRICS_KEY.value:
metrics_s3_object_keys[agent_index],
# Replaced rospy.get_param('AWS_REGION') to be equal to the argument being passed
# or default argument set
MetricsS3Keys.REGION.value:
args.aws_region,
# Replaced rospy.get_param('MODEL_S3_BUCKET') to be equal to the argument being passed
# or default argument set
MetricsS3Keys.STEP_BUCKET.value:
arg_s3_bucket[agent_index],
# Replaced rospy.get_param('MODEL_S3_PREFIX') to be equal to the argument being passed
# or default argument set
MetricsS3Keys.STEP_KEY.value:
os.path.join(arg_s3_prefix[agent_index],
EVALUATION_SIMTRACE_DATA_S3_OBJECT_KEY)
}
aws_region = rospy.get_param('AWS_REGION', args.aws_region)
s3_writer_job_info = []
if simtrace_s3_bucket:
s3_writer_job_info.append(
IterationData(
'simtrace', simtrace_s3_bucket[agent_index],
simtrace_s3_object_prefix[agent_index], aws_region,
os.path.join(
ITERATION_DATA_LOCAL_FILE_PATH, agent_name,
IterationDataLocalFileNames.
SIM_TRACE_EVALUATION_LOCAL_FILE.value)))
if mp4_s3_bucket:
s3_writer_job_info.extend([
IterationData(
'pip', mp4_s3_bucket[agent_index],
mp4_s3_object_prefix[agent_index], aws_region,
os.path.join(
ITERATION_DATA_LOCAL_FILE_PATH, agent_name,
IterationDataLocalFileNames.
CAMERA_PIP_MP4_VALIDATION_LOCAL_PATH.value)),
IterationData(
'45degree', mp4_s3_bucket[agent_index],
mp4_s3_object_prefix[agent_index], aws_region,
os.path.join(
ITERATION_DATA_LOCAL_FILE_PATH, agent_name,
IterationDataLocalFileNames.
CAMERA_45DEGREE_MP4_VALIDATION_LOCAL_PATH.value)),
IterationData(
'topview', mp4_s3_bucket[agent_index],
mp4_s3_object_prefix[agent_index], aws_region,
os.path.join(
ITERATION_DATA_LOCAL_FILE_PATH, agent_name,
IterationDataLocalFileNames.
CAMERA_TOPVIEW_MP4_VALIDATION_LOCAL_PATH.value))
])
s3_writers.append(S3Writer(job_info=s3_writer_job_info))
run_phase_subject = RunPhaseSubject()
agent_list.append(
create_rollout_agent(agent_config,
EvalMetrics(agent_name, metrics_s3_config),
run_phase_subject))
agent_list.append(create_obstacles_agent())
agent_list.append(create_bot_cars_agent())
# ROS service to indicate all the robomaker markov packages are ready for consumption
signal_robomaker_markov_package_ready()
PhaseObserver('/agent/training_phase', run_phase_subject)
graph_manager, _ = get_graph_manager(hp_dict=sm_hyperparams_dict,
agent_list=agent_list,
run_phase_subject=run_phase_subject)
ds_params_instance = S3BotoDataStoreParameters(
aws_region=args.aws_region,
bucket_names=s3_bucket_dict,
base_checkpoint_dir=args.local_model_directory,
s3_folders=s3_prefix_dict)
graph_manager.data_store = S3BotoDataStore(params=ds_params_instance,
graph_manager=graph_manager,
ignore_lock=True)
graph_manager.env_params.seed = 0
task_parameters = TaskParameters()
task_parameters.checkpoint_restore_path = args.local_model_directory
tournament_worker(graph_manager=graph_manager,
number_of_trials=args.number_of_trials,
task_parameters=task_parameters,
s3_writers=s3_writers,
is_continuous=args.is_continuous)
# tournament_worker: write race report to local file.
write_race_report(graph_manager,
model_s3_bucket_map=s3_bucket_dict,
model_s3_prefix_map=s3_prefix_dict,
metrics_s3_bucket_map=metrics_s3_bucket_dict,
metrics_s3_key_map=metrics_s3_obect_key_dict,
simtrace_s3_bucket_map=simtrace_s3_bucket_dict,
simtrace_s3_prefix_map=simtrace_s3_prefix_dict,
mp4_s3_bucket_map=mp4_s3_bucket_dict,
mp4_s3_prefix_map=mp4_s3_object_prefix_dict,
display_names=display_names)
# tournament_worker: terminate tournament_race_node.
terminate_tournament_race()
def main():
screen.set_use_colors(False)
parser = argparse.ArgumentParser()
parser.add_argument(
'-c',
'--checkpoint_dir',
help=
'(string) Path to a folder containing a checkpoint to restore the model from.',
type=str,
default='./checkpoint')
parser.add_argument('--s3_bucket',
help='(string) S3 bucket',
type=str,
default=rospy.get_param("SAGEMAKER_SHARED_S3_BUCKET",
"gsaur-test"))
parser.add_argument('--s3_prefix',
help='(string) S3 prefix',
type=str,
default=rospy.get_param("SAGEMAKER_SHARED_S3_PREFIX",
"sagemaker"))
parser.add_argument(
'--num_workers',
help="(int) The number of workers started in this pool",
type=int,
default=int(rospy.get_param("NUM_WORKERS", 1)))
parser.add_argument('--rollout_idx',
help="(int) The index of current rollout worker",
type=int,
default=0)
parser.add_argument('-r',
'--redis_ip',
help="(string) IP or host for the redis server",
default='localhost',
type=str)
parser.add_argument('-rp',
'--redis_port',
help="(int) Port of the redis server",
default=6379,
type=int)
parser.add_argument('--aws_region',
help='(string) AWS region',
type=str,
default=rospy.get_param("AWS_REGION", "us-east-1"))
parser.add_argument('--reward_file_s3_key',
help='(string) Reward File S3 Key',
type=str,
default=rospy.get_param("REWARD_FILE_S3_KEY", None))
parser.add_argument('--model_metadata_s3_key',
help='(string) Model Metadata File S3 Key',
type=str,
default=rospy.get_param("MODEL_METADATA_FILE_S3_KEY",
None))
# For training job, reset is not allowed. penalty_seconds, off_track_penalty, and
# collision_penalty will all be 0 be default
parser.add_argument('--number_of_resets',
help='(integer) Number of resets',
type=int,
default=int(rospy.get_param("NUMBER_OF_RESETS", 0)))
parser.add_argument('--penalty_seconds',
help='(float) penalty second',
type=float,
default=float(rospy.get_param("PENALTY_SECONDS", 0.0)))
parser.add_argument('--job_type',
help='(string) job type',
type=str,
default=rospy.get_param("JOB_TYPE", "TRAINING"))
parser.add_argument('--is_continuous',
help='(boolean) is continous after lap completion',
type=bool,
default=utils.str2bool(
rospy.get_param("IS_CONTINUOUS", False)))
parser.add_argument('--race_type',
help='(string) Race type',
type=str,
default=rospy.get_param("RACE_TYPE", "TIME_TRIAL"))
parser.add_argument('--off_track_penalty',
help='(float) off track penalty second',
type=float,
default=float(rospy.get_param("OFF_TRACK_PENALTY",
0.0)))
parser.add_argument('--collision_penalty',
help='(float) collision penalty second',
type=float,
default=float(rospy.get_param("COLLISION_PENALTY",
0.0)))
args = parser.parse_args()
s3_client = SageS3Client(bucket=args.s3_bucket,
s3_prefix=args.s3_prefix,
aws_region=args.aws_region)
logger.info("S3 bucket: %s", args.s3_bucket)
logger.info("S3 prefix: %s", args.s3_prefix)
# Load the model metadata
model_metadata_local_path = os.path.join(CUSTOM_FILES_PATH,
'model_metadata.json')
utils.load_model_metadata(s3_client, args.model_metadata_s3_key,
model_metadata_local_path)
# Download and import reward function
if not args.reward_file_s3_key:
log_and_exit(
"Reward function code S3 key not available for S3 bucket {} and prefix {}"
.format(args.s3_bucket, args.s3_prefix),
SIMAPP_SIMULATION_WORKER_EXCEPTION, SIMAPP_EVENT_ERROR_CODE_500)
download_customer_reward_function(s3_client, args.reward_file_s3_key)
try:
from custom_files.customer_reward_function import reward_function
except Exception as e:
log_and_exit("Failed to import user's reward_function: {}".format(e),
SIMAPP_SIMULATION_WORKER_EXCEPTION,
SIMAPP_EVENT_ERROR_CODE_400)
# Instantiate Cameras
configure_camera(namespaces=['racecar'])
preset_file_success, _ = download_custom_files_if_present(
s3_client, args.s3_prefix)
#! TODO each agent should have own config
_, _, version = utils_parse_model_metadata.parse_model_metadata(
model_metadata_local_path)
agent_config = {
'model_metadata': model_metadata_local_path,
ConfigParams.CAR_CTRL_CONFIG.value: {
ConfigParams.LINK_NAME_LIST.value:
LINK_NAMES,
ConfigParams.VELOCITY_LIST.value:
VELOCITY_TOPICS,
ConfigParams.STEERING_LIST.value:
STEERING_TOPICS,
ConfigParams.CHANGE_START.value:
utils.str2bool(rospy.get_param('CHANGE_START_POSITION', True)),
ConfigParams.ALT_DIR.value:
utils.str2bool(
rospy.get_param('ALTERNATE_DRIVING_DIRECTION', False)),
ConfigParams.ACTION_SPACE_PATH.value:
'custom_files/model_metadata.json',
ConfigParams.REWARD.value:
reward_function,
ConfigParams.AGENT_NAME.value:
'racecar',
ConfigParams.VERSION.value:
version,
ConfigParams.NUMBER_OF_RESETS.value:
args.number_of_resets,
ConfigParams.PENALTY_SECONDS.value:
args.penalty_seconds,
ConfigParams.NUMBER_OF_TRIALS.value:
None,
ConfigParams.IS_CONTINUOUS.value:
args.is_continuous,
ConfigParams.RACE_TYPE.value:
args.race_type,
ConfigParams.COLLISION_PENALTY.value:
args.collision_penalty,
ConfigParams.OFF_TRACK_PENALTY.value:
args.off_track_penalty
}
}
#! TODO each agent should have own s3 bucket
step_metrics_prefix = rospy.get_param('SAGEMAKER_SHARED_S3_PREFIX')
if args.num_workers > 1:
step_metrics_prefix = os.path.join(step_metrics_prefix,
str(args.rollout_idx))
metrics_s3_config = {
MetricsS3Keys.METRICS_BUCKET.value:
rospy.get_param('METRICS_S3_BUCKET'),
MetricsS3Keys.METRICS_KEY.value:
rospy.get_param('METRICS_S3_OBJECT_KEY'),
MetricsS3Keys.REGION.value: rospy.get_param('AWS_REGION')
}
metrics_s3_model_cfg = {
MetricsS3Keys.METRICS_BUCKET.value:
args.s3_bucket,
MetricsS3Keys.METRICS_KEY.value:
os.path.join(args.s3_prefix, DEEPRACER_CHKPNT_KEY_SUFFIX),
MetricsS3Keys.REGION.value:
args.aws_region
}
run_phase_subject = RunPhaseSubject()
agent_list = list()
agent_list.append(
create_rollout_agent(
agent_config,
TrainingMetrics(agent_name='agent',
s3_dict_metrics=metrics_s3_config,
s3_dict_model=metrics_s3_model_cfg,
ckpnt_dir=args.checkpoint_dir,
run_phase_sink=run_phase_subject,
use_model_picker=(args.rollout_idx == 0)),
run_phase_subject))
agent_list.append(create_obstacles_agent())
agent_list.append(create_bot_cars_agent())
# ROS service to indicate all the robomaker markov packages are ready for consumption
signal_robomaker_markov_package_ready()
PhaseObserver('/agent/training_phase', run_phase_subject)
aws_region = rospy.get_param('AWS_REGION', args.aws_region)
simtrace_s3_bucket = rospy.get_param('SIMTRACE_S3_BUCKET', None)
mp4_s3_bucket = rospy.get_param('MP4_S3_BUCKET',
None) if args.rollout_idx == 0 else None
if simtrace_s3_bucket:
simtrace_s3_object_prefix = rospy.get_param('SIMTRACE_S3_PREFIX')
if args.num_workers > 1:
simtrace_s3_object_prefix = os.path.join(simtrace_s3_object_prefix,
str(args.rollout_idx))
if mp4_s3_bucket:
mp4_s3_object_prefix = rospy.get_param('MP4_S3_OBJECT_PREFIX')
s3_writer_job_info = []
if simtrace_s3_bucket:
s3_writer_job_info.append(
IterationData(
'simtrace', simtrace_s3_bucket, simtrace_s3_object_prefix,
aws_region,
os.path.join(
ITERATION_DATA_LOCAL_FILE_PATH, 'agent',
IterationDataLocalFileNames.SIM_TRACE_TRAINING_LOCAL_FILE.
value)))
if mp4_s3_bucket:
s3_writer_job_info.extend([
IterationData(
'pip', mp4_s3_bucket, mp4_s3_object_prefix, aws_region,
os.path.join(
ITERATION_DATA_LOCAL_FILE_PATH, 'agent',
IterationDataLocalFileNames.
CAMERA_PIP_MP4_VALIDATION_LOCAL_PATH.value)),
IterationData(
'45degree', mp4_s3_bucket, mp4_s3_object_prefix, aws_region,
os.path.join(
ITERATION_DATA_LOCAL_FILE_PATH, 'agent',
IterationDataLocalFileNames.
CAMERA_45DEGREE_MP4_VALIDATION_LOCAL_PATH.value)),
IterationData(
'topview', mp4_s3_bucket, mp4_s3_object_prefix, aws_region,
os.path.join(
ITERATION_DATA_LOCAL_FILE_PATH, 'agent',
IterationDataLocalFileNames.
CAMERA_TOPVIEW_MP4_VALIDATION_LOCAL_PATH.value))
])
s3_writer = S3Writer(job_info=s3_writer_job_info)
redis_ip = s3_client.get_ip()
logger.info("Received IP from SageMaker successfully: %s", redis_ip)
# Download hyperparameters from SageMaker
hyperparameters_file_success = False
hyperparams_s3_key = os.path.normpath(args.s3_prefix +
"/ip/hyperparameters.json")
hyperparameters_file_success = s3_client.download_file(
s3_key=hyperparams_s3_key, local_path="hyperparameters.json")
sm_hyperparams_dict = {}
if hyperparameters_file_success:
logger.info("Received Sagemaker hyperparameters successfully!")
with open("hyperparameters.json") as filepointer:
sm_hyperparams_dict = json.load(filepointer)
else:
logger.info("SageMaker hyperparameters not found.")
enable_domain_randomization = utils.str2bool(
rospy.get_param('ENABLE_DOMAIN_RANDOMIZATION', False))
if preset_file_success:
preset_location = os.path.join(CUSTOM_FILES_PATH, "preset.py")
preset_location += ":graph_manager"
graph_manager = short_dynamic_import(preset_location,
ignore_module_case=True)
logger.info("Using custom preset file!")
else:
graph_manager, _ = get_graph_manager(
hp_dict=sm_hyperparams_dict,
agent_list=agent_list,
run_phase_subject=run_phase_subject,
enable_domain_randomization=enable_domain_randomization)
# If num_episodes_between_training is smaller than num_workers then cancel worker early.
episode_steps_per_rollout = graph_manager.agent_params.algorithm.num_consecutive_playing_steps.num_steps
# Reduce number of workers if allocated more than num_episodes_between_training
if args.num_workers > episode_steps_per_rollout:
logger.info(
"Excess worker allocated. Reducing from {} to {}...".format(
args.num_workers, episode_steps_per_rollout))
args.num_workers = episode_steps_per_rollout
if args.rollout_idx >= episode_steps_per_rollout or args.rollout_idx >= args.num_workers:
err_msg_format = "Exiting excess worker..."
err_msg_format += "(rollout_idx[{}] >= num_workers[{}] or num_episodes_between_training[{}])"
logger.info(
err_msg_format.format(args.rollout_idx, args.num_workers,
episode_steps_per_rollout))
# Close the down the job
utils.cancel_simulation_job(
os.environ.get('AWS_ROBOMAKER_SIMULATION_JOB_ARN'),
rospy.get_param('AWS_REGION'))
memory_backend_params = DeepRacerRedisPubSubMemoryBackendParameters(
redis_address=redis_ip,
redis_port=6379,
run_type=str(RunType.ROLLOUT_WORKER),
channel=args.s3_prefix,
num_workers=args.num_workers,
rollout_idx=args.rollout_idx)
graph_manager.memory_backend_params = memory_backend_params
ds_params_instance = S3BotoDataStoreParameters(
aws_region=args.aws_region,
bucket_names={'agent': args.s3_bucket},
base_checkpoint_dir=args.checkpoint_dir,
s3_folders={'agent': args.s3_prefix})
graph_manager.data_store = S3BotoDataStore(ds_params_instance,
graph_manager)
task_parameters = TaskParameters()
task_parameters.checkpoint_restore_path = args.checkpoint_dir
rollout_worker(graph_manager=graph_manager,
num_workers=args.num_workers,
rollout_idx=args.rollout_idx,
task_parameters=task_parameters,
s3_writer=s3_writer)
def simtrace_job_info(s3_bucket, s3_prefix, aws_region):
dir_path = os.path.dirname(os.path.realpath(__file__))
simtrace_path = "{}/test_data/simtrace.csv".format(dir_path)
with open(simtrace_path, "w") as filepointer:
filepointer.write("")
return [IterationData('simtrace', s3_bucket, s3_prefix, aws_region, simtrace_path)]
def main():
""" Main function for evaluation worker """
parser = argparse.ArgumentParser()
parser.add_argument('-p',
'--preset',
help="(string) Name of a preset to run \
(class name from the 'presets' directory.)",
type=str,
required=False)
parser.add_argument('--s3_bucket',
help='list(string) S3 bucket',
type=str,
nargs='+',
default=rospy.get_param("MODEL_S3_BUCKET",
["gsaur-test"]))
parser.add_argument('--s3_prefix',
help='list(string) S3 prefix',
type=str,
nargs='+',
default=rospy.get_param("MODEL_S3_PREFIX",
["sagemaker"]))
parser.add_argument('--s3_endpoint_url',
help='(string) S3 endpoint URL',
type=str,
default=rospy.get_param("S3_ENDPOINT_URL", None))
parser.add_argument('--aws_region',
help='(string) AWS region',
type=str,
default=rospy.get_param("AWS_REGION", "us-east-1"))
parser.add_argument('--number_of_trials',
help='(integer) Number of trials',
type=int,
default=int(rospy.get_param("NUMBER_OF_TRIALS", 10)))
parser.add_argument(
'-c',
'--local_model_directory',
help='(string) Path to a folder containing a checkpoint \
to restore the model from.',
type=str,
default='./checkpoint')
parser.add_argument('--number_of_resets',
help='(integer) Number of resets',
type=int,
default=int(rospy.get_param("NUMBER_OF_RESETS", 0)))
parser.add_argument('--penalty_seconds',
help='(float) penalty second',
type=float,
default=float(rospy.get_param("PENALTY_SECONDS", 2.0)))
parser.add_argument('--job_type',
help='(string) job type',
type=str,
default=rospy.get_param("JOB_TYPE", "EVALUATION"))
parser.add_argument('--is_continuous',
help='(boolean) is continous after lap completion',
type=bool,
default=utils.str2bool(
rospy.get_param("IS_CONTINUOUS", False)))
parser.add_argument('--race_type',
help='(string) Race type',
type=str,
default=rospy.get_param("RACE_TYPE", "TIME_TRIAL"))
parser.add_argument('--off_track_penalty',
help='(float) off track penalty second',
type=float,
default=float(rospy.get_param("OFF_TRACK_PENALTY",
2.0)))
parser.add_argument('--collision_penalty',
help='(float) collision penalty second',
type=float,
default=float(rospy.get_param("COLLISION_PENALTY",
5.0)))
parser.add_argument('--round_robin_advance_dist',
help='(float) round robin distance 0-1',
type=float,
default=float(
rospy.get_param("ROUND_ROBIN_ADVANCE_DIST", 0.05)))
parser.add_argument('--start_position_offset',
help='(float) offset start 0-1',
type=float,
default=float(
rospy.get_param("START_POSITION_OFFSET", 0.0)))
args = parser.parse_args()
arg_s3_bucket = args.s3_bucket
arg_s3_prefix = args.s3_prefix
logger.info("S3 bucket: %s \n S3 prefix: %s \n S3 endpoint URL: %s",
args.s3_bucket, args.s3_prefix, args.s3_endpoint_url)
metrics_s3_buckets = rospy.get_param('METRICS_S3_BUCKET')
metrics_s3_object_keys = rospy.get_param('METRICS_S3_OBJECT_KEY')
arg_s3_bucket, arg_s3_prefix = utils.force_list(
arg_s3_bucket), utils.force_list(arg_s3_prefix)
metrics_s3_buckets = utils.force_list(metrics_s3_buckets)
metrics_s3_object_keys = utils.force_list(metrics_s3_object_keys)
validate_list = [
arg_s3_bucket, arg_s3_prefix, metrics_s3_buckets,
metrics_s3_object_keys
]
simtrace_s3_bucket = rospy.get_param('SIMTRACE_S3_BUCKET', None)
mp4_s3_bucket = rospy.get_param('MP4_S3_BUCKET', None)
if simtrace_s3_bucket:
simtrace_s3_object_prefix = rospy.get_param('SIMTRACE_S3_PREFIX')
simtrace_s3_bucket = utils.force_list(simtrace_s3_bucket)
simtrace_s3_object_prefix = utils.force_list(simtrace_s3_object_prefix)
validate_list.extend([simtrace_s3_bucket, simtrace_s3_object_prefix])
if mp4_s3_bucket:
mp4_s3_object_prefix = rospy.get_param('MP4_S3_OBJECT_PREFIX')
mp4_s3_bucket = utils.force_list(mp4_s3_bucket)
mp4_s3_object_prefix = utils.force_list(mp4_s3_object_prefix)
validate_list.extend([mp4_s3_bucket, mp4_s3_object_prefix])
if not all([lambda x: len(x) == len(validate_list[0]), validate_list]):
log_and_exit(
"Eval worker error: Incorrect arguments passed: {}".format(
validate_list), SIMAPP_SIMULATION_WORKER_EXCEPTION,
SIMAPP_EVENT_ERROR_CODE_500)
if args.number_of_resets != 0 and args.number_of_resets < MIN_RESET_COUNT:
raise GenericRolloutException(
"number of resets is less than {}".format(MIN_RESET_COUNT))
# Instantiate Cameras
if len(arg_s3_bucket) == 1:
configure_camera(namespaces=['racecar'])
else:
configure_camera(namespaces=[
'racecar_{}'.format(str(agent_index))
for agent_index in range(len(arg_s3_bucket))
])
agent_list = list()
s3_bucket_dict = dict()
s3_prefix_dict = dict()
s3_writers = list()
start_positions = get_start_positions(len(arg_s3_bucket))
done_condition = utils.str_to_done_condition(
rospy.get_param("DONE_CONDITION", any))
park_positions = utils.pos_2d_str_to_list(
rospy.get_param("PARK_POSITIONS", []))
# if not pass in park positions for all done condition case, use default
if not park_positions:
park_positions = [DEFAULT_PARK_POSITION for _ in arg_s3_bucket]
for agent_index, _ in enumerate(arg_s3_bucket):
agent_name = 'agent' if len(arg_s3_bucket) == 1 else 'agent_{}'.format(
str(agent_index))
racecar_name = 'racecar' if len(
arg_s3_bucket) == 1 else 'racecar_{}'.format(str(agent_index))
s3_bucket_dict[agent_name] = arg_s3_bucket[agent_index]
s3_prefix_dict[agent_name] = arg_s3_prefix[agent_index]
# download model metadata
model_metadata = ModelMetadata(
bucket=arg_s3_bucket[agent_index],
s3_key=get_s3_key(arg_s3_prefix[agent_index],
MODEL_METADATA_S3_POSTFIX),
region_name=args.aws_region,
s3_endpoint_url=args.s3_endpoint_url,
local_path=MODEL_METADATA_LOCAL_PATH_FORMAT.format(agent_name))
_, _, version = model_metadata.get_model_metadata_info()
# Select the optimal model
utils.do_model_selection(s3_bucket=arg_s3_bucket[agent_index],
s3_prefix=arg_s3_prefix[agent_index],
region=args.aws_region,
s3_endpoint_url=args.s3_endpoint_url)
agent_config = {
'model_metadata': model_metadata,
ConfigParams.CAR_CTRL_CONFIG.value: {
ConfigParams.LINK_NAME_LIST.value: [
link_name.replace('racecar', racecar_name)
for link_name in LINK_NAMES
],
ConfigParams.VELOCITY_LIST.value: [
velocity_topic.replace('racecar', racecar_name)
for velocity_topic in VELOCITY_TOPICS
],
ConfigParams.STEERING_LIST.value: [
steering_topic.replace('racecar', racecar_name)
for steering_topic in STEERING_TOPICS
],
ConfigParams.CHANGE_START.value:
utils.str2bool(rospy.get_param('CHANGE_START_POSITION',
False)),
ConfigParams.ALT_DIR.value:
utils.str2bool(
rospy.get_param('ALTERNATE_DRIVING_DIRECTION', False)),
ConfigParams.ACTION_SPACE_PATH.value:
model_metadata.local_path,
ConfigParams.REWARD.value:
reward_function,
ConfigParams.AGENT_NAME.value:
racecar_name,
ConfigParams.VERSION.value:
version,
ConfigParams.NUMBER_OF_RESETS.value:
args.number_of_resets,
ConfigParams.PENALTY_SECONDS.value:
args.penalty_seconds,
ConfigParams.NUMBER_OF_TRIALS.value:
args.number_of_trials,
ConfigParams.IS_CONTINUOUS.value:
args.is_continuous,
ConfigParams.RACE_TYPE.value:
args.race_type,
ConfigParams.COLLISION_PENALTY.value:
args.collision_penalty,
ConfigParams.OFF_TRACK_PENALTY.value:
args.off_track_penalty,
ConfigParams.START_POSITION.value:
start_positions[agent_index],
ConfigParams.DONE_CONDITION.value:
done_condition,
ConfigParams.ROUND_ROBIN_ADVANCE_DIST.value:
args.round_robin_advance_dist,
ConfigParams.START_POSITION_OFFSET.value:
args.start_position_offset
}
}
metrics_s3_config = {
MetricsS3Keys.METRICS_BUCKET.value:
metrics_s3_buckets[agent_index],
MetricsS3Keys.METRICS_KEY.value:
metrics_s3_object_keys[agent_index],
MetricsS3Keys.ENDPOINT_URL.value:
rospy.get_param('S3_ENDPOINT_URL', None),
# Replaced rospy.get_param('AWS_REGION') to be equal to the argument being passed
# or default argument set
MetricsS3Keys.REGION.value:
args.aws_region
}
aws_region = rospy.get_param('AWS_REGION', args.aws_region)
s3_writer_job_info = []
if simtrace_s3_bucket:
s3_writer_job_info.append(
IterationData(
'simtrace', simtrace_s3_bucket[agent_index],
simtrace_s3_object_prefix[agent_index], aws_region,
os.path.join(
ITERATION_DATA_LOCAL_FILE_PATH, agent_name,
IterationDataLocalFileNames.
SIM_TRACE_EVALUATION_LOCAL_FILE.value)))
if mp4_s3_bucket:
s3_writer_job_info.extend([
IterationData(
'pip', mp4_s3_bucket[agent_index],
mp4_s3_object_prefix[agent_index], aws_region,
os.path.join(
ITERATION_DATA_LOCAL_FILE_PATH, agent_name,
IterationDataLocalFileNames.
CAMERA_PIP_MP4_VALIDATION_LOCAL_PATH.value)),
IterationData(
'45degree', mp4_s3_bucket[agent_index],
mp4_s3_object_prefix[agent_index], aws_region,
os.path.join(
ITERATION_DATA_LOCAL_FILE_PATH, agent_name,
IterationDataLocalFileNames.
CAMERA_45DEGREE_MP4_VALIDATION_LOCAL_PATH.value)),
IterationData(
'topview', mp4_s3_bucket[agent_index],
mp4_s3_object_prefix[agent_index], aws_region,
os.path.join(
ITERATION_DATA_LOCAL_FILE_PATH, agent_name,
IterationDataLocalFileNames.
CAMERA_TOPVIEW_MP4_VALIDATION_LOCAL_PATH.value))
])
s3_writers.append(
S3Writer(job_info=s3_writer_job_info,
s3_endpoint_url=args.s3_endpoint_url))
run_phase_subject = RunPhaseSubject()
agent_list.append(
create_rollout_agent(
agent_config,
EvalMetrics(agent_name, metrics_s3_config, args.is_continuous),
run_phase_subject))
agent_list.append(create_obstacles_agent())
agent_list.append(create_bot_cars_agent())
# ROS service to indicate all the robomaker markov packages are ready for consumption
signal_robomaker_markov_package_ready()
PhaseObserver('/agent/training_phase', run_phase_subject)
enable_domain_randomization = utils.str2bool(
rospy.get_param('ENABLE_DOMAIN_RANDOMIZATION', False))
sm_hyperparams_dict = {}
graph_manager, _ = get_graph_manager(
hp_dict=sm_hyperparams_dict,
agent_list=agent_list,
run_phase_subject=run_phase_subject,
enable_domain_randomization=enable_domain_randomization,
done_condition=done_condition)
ds_params_instance = S3BotoDataStoreParameters(
aws_region=args.aws_region,
bucket_names=s3_bucket_dict,
base_checkpoint_dir=args.local_model_directory,
s3_folders=s3_prefix_dict,
s3_endpoint_url=args.s3_endpoint_url)
graph_manager.data_store = S3BotoDataStore(params=ds_params_instance,
graph_manager=graph_manager,
ignore_lock=True)
graph_manager.env_params.seed = 0
task_parameters = TaskParameters()
task_parameters.checkpoint_restore_path = args.local_model_directory
evaluation_worker(graph_manager=graph_manager,
number_of_trials=args.number_of_trials,
task_parameters=task_parameters,
s3_writers=s3_writers,
is_continuous=args.is_continuous,
park_positions=park_positions)