def sample(self, data):
if self._cur_sample_count >= self.max_sample_count:
return
self._cur_frequency += 1
if self._cur_frequency < self.sampling_frequency:
return
pickle_filename_format = 'sample_{}.pkl'
pickle_filename = pickle_filename_format.format(self._cur_sample_count)
try:
with open(pickle_filename, 'wb') as out_f:
pickle.dump(data, out_f, protocol=2)
except Exception as ex:
raise GenericTrainerException(
'Failed to dump the sample data: {}'.format(ex))
try:
self.s3_client.upload_file(
os.path.normpath("%s/samples/%s" %
(self.s3_prefix, pickle_filename)),
pickle_filename)
except Exception as ex:
raise GenericTrainerException(
'Failed to upload the sample pickle file to S3: {}'.format(ex))
self._cur_frequency = 0
self._cur_sample_count += 1
def __init__(self,
s3_client,
s3_prefix,
max_sample_count=None,
sampling_frequency=None):
self.max_sample_count = max_sample_count or 0
self.sampling_frequency = sampling_frequency or 1
if self.sampling_frequency < 1:
err_msg = "sampling_frequency must be larger or equal to 1. (Given: {})".format(
self.sampling_frequency)
raise GenericTrainerException(err_msg)
self.s3_client = s3_client
self.s3_prefix = s3_prefix
self._cur_sample_count = 0
self._cur_frequency = 0
def create_sensor(sensor_type, config_dict):
'''Factory method for creating sensors
type - String containing the desired sensor type
kwargs - Meta data, usually containing the topics to subscribe to, the
concrete sensor classes are responsible for checking the topics.
'''
if sensor_type == Input.CAMERA.value:
return Camera()
elif sensor_type == Input.LEFT_CAMERA.value:
return LeftCamera()
elif sensor_type == Input.STEREO.value:
return DualCamera()
elif sensor_type == Input.LIDAR.value:
return Lidar()
elif sensor_type == Input.OBSERVATION.value:
return Observation()
else:
raise GenericTrainerException("Unknown sensor")
def get_input_embedders(self, network_type):
try:
return get_left_camera_embedders(network_type)
except Exception as ex:
raise GenericTrainerException('{}'.format(ex))
def get_observation_space(self):
try:
return get_observation_space(Input.LEFT_CAMERA.value)
except Exception as ex:
raise GenericTrainerException('{}'.format(ex))
def get_input_embedders(self, network_type):
try:
return get_observation_embedder()
except Exception as ex:
raise GenericTrainerException('{}'.format(ex))
def get_observation_space(self):
try:
return get_observation_space(Input.OBSERVATION.value)
except Exception as ex:
raise GenericTrainerException('{}'.format(ex))