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def normalized_distance(self, image): """Calculates the distance of a given image to the original image. Parameters ---------- image : `numpy.ndarray` The image that should be compared to the original image. Returns ------- :class:`Distance` ...
def __is_adversarial(self, image, predictions, in_bounds): """Interface to criterion.is_adverarial that calls __new_adversarial if necessary. Parameters ---------- predictions : :class:`numpy.ndarray` A vector with the pre-softmax predictions for some image. ...
def channel_axis(self, batch): """Interface to model.channel_axis for attacks. Parameters ---------- batch : bool Controls whether the index of the axis for a batch of images (4 dimensions) or a single image (3 dimensions) should be returned. """ ...
def has_gradient(self): """Returns true if _backward and _forward_backward can be called by an attack, False otherwise. """ try: self.__model.gradient self.__model.predictions_and_gradient except AttributeError: return False else: ...
def predictions(self, image, strict=True, return_details=False): """Interface to model.predictions for attacks. Parameters ---------- image : `numpy.ndarray` Single input with shape as expected by the model (without the batch dimension). strict : bool ...
def batch_predictions( self, images, greedy=False, strict=True, return_details=False): """Interface to model.batch_predictions for attacks. Parameters ---------- images : `numpy.ndarray` Batch of inputs with shape as expected by the model. greedy : bool ...
def gradient(self, image=None, label=None, strict=True): """Interface to model.gradient for attacks. Parameters ---------- image : `numpy.ndarray` Single input with shape as expected by the model (without the batch dimension). Defaults to the original...
def predictions_and_gradient( self, image=None, label=None, strict=True, return_details=False): """Interface to model.predictions_and_gradient for attacks. Parameters ---------- image : `numpy.ndarray` Single input with shape as expected by the model ...
def backward(self, gradient, image=None, strict=True): """Interface to model.backward for attacks. Parameters ---------- gradient : `numpy.ndarray` Gradient of some loss w.r.t. the logits. image : `numpy.ndarray` Single input with shape as expected by the...
def loss_function(cls, const, a, x, logits, reconstructed_original, confidence, min_, max_): """Returns the loss and the gradient of the loss w.r.t. x, assuming that logits = model(x).""" targeted = a.target_class() is not None if targeted: c_minimize =...
def best_other_class(logits, exclude): """Returns the index of the largest logit, ignoring the class that is passed as `exclude`.""" other_logits = logits - onehot_like(logits, exclude, value=np.inf) return np.argmax(other_logits)
def name(self): """Concatenates the names of the given criteria in alphabetical order. If a sub-criterion is itself a combined criterion, its name is first split into the individual names and the names of the sub-sub criteria is used instead of the name of the sub-criterion. Thi...
def _difference_map(image, color_axis): """Difference map of the image. Approximate derivatives of the function image[c, :, :] (e.g. PyTorch) or image[:, :, c] (e.g. Keras). dfdx, dfdy = difference_map(image) In: image: numpy.ndarray of shape C x h x w or h x w x C, with C = 1 or C = 3 ...
def _compose(image, vec_field, color_axis): """Calculate the composition of the function image with the vector field vec_field by interpolation. new_func = compose(image, vec_field) In: image: numpy.ndarray of shape C x h x w with C = 3 or C = 1 (color channels), h, w >= 2, and [type...
def _create_vec_field(fval, gradf, d1x, d2x, color_axis, smooth=0): """Calculate the deformation vector field In: fval: float gradf: numpy.ndarray of shape C x h x w with C = 3 or C = 1 (color channels), h, w >= 1. d1x: numpy.ndarray of shape C x h x w and [type] = 'Float' or...
def softmax(logits): """Transforms predictions into probability values. Parameters ---------- logits : array_like The logits predicted by the model. Returns ------- `numpy.ndarray` Probability values corresponding to the logits. """ assert logits.ndim == 1 # f...
def crossentropy(label, logits): """Calculates the cross-entropy. Parameters ---------- logits : array_like The logits predicted by the model. label : int The label describing the target distribution. Returns ------- float The cross-entropy between softmax(logit...
def batch_crossentropy(label, logits): """Calculates the cross-entropy for a batch of logits. Parameters ---------- logits : array_like The logits predicted by the model for a batch of inputs. label : int The label describing the target distribution. Returns ------- np....
def binarize(x, values, threshold=None, included_in='upper'): """Binarizes the values of x. Parameters ---------- values : tuple of two floats The lower and upper value to which the inputs are mapped. threshold : float The threshold; defaults to (values[0] + values[1]) / 2 if None. ...
def imagenet_example(shape=(224, 224), data_format='channels_last'): """ Returns an example image and its imagenet class label. Parameters ---------- shape : list of integers The shape of the returned image. data_format : str "channels_first" or "channels_last" Returns ----...
def samples(dataset='imagenet', index=0, batchsize=1, shape=(224, 224), data_format='channels_last'): ''' Returns a batch of example images and the corresponding labels Parameters ---------- dataset : string The data set to load (options: imagenet, mnist, cifar10, cifar100, ...
def onehot_like(a, index, value=1): """Creates an array like a, with all values set to 0 except one. Parameters ---------- a : array_like The returned one-hot array will have the same shape and dtype as this array index : int The index that should be set to `value` v...
def _get_output(self, a, image): """ Looks up the precomputed adversarial image for a given image. """ sd = np.square(self._input_images - image) mses = np.mean(sd, axis=tuple(range(1, sd.ndim))) index = np.argmin(mses) # if we run into numerical problems with this appr...
def _process_gradient(self, backward, dmdp): """ backward: `callable` callable that backpropagates the gradient of the model w.r.t to preprocessed input through the preprocessing to get the gradient of the model's output w.r.t. the input before preprocessing d...
def predictions(self, image): """Convenience method that calculates predictions for a single image. Parameters ---------- image : `numpy.ndarray` Single input with shape as expected by the model (without the batch dimension). Returns ------- ...
def gradient(self, image, label): """Calculates the gradient of the cross-entropy loss w.r.t. the image. The default implementation calls predictions_and_gradient. Subclasses can provide more efficient implementations that only calculate the gradient. Parameters -------...
def clone(git_uri): """ Clone a remote git repository to a local path. :param git_uri: the URI to the git repository to be cloned :return: the generated local path where the repository has been cloned to """ hash_digest = sha256_hash(git_uri) local_path = home_directory_path(FOLDER, hash_di...
def run(command, parser, cl_args, unknown_args): ''' :param command: :param parser: :param cl_args: :param unknown_args: :return: ''' Log.debug("Deactivate Args: %s", cl_args) return cli_helper.run(command, cl_args, "deactivate topology")
def poll(self, timeout=0.0): """Modified version of poll() from asyncore module""" if self.sock_map is None: Log.warning("Socket map is not registered to Gateway Looper") readable_lst = [] writable_lst = [] error_lst = [] if self.sock_map is not None: for fd, obj in self.sock_map.it...
def configure(level, logfile=None): """ configure logging """ log_format = "%(asctime)s-%(levelname)s: %(message)s" date_format = '%a, %d %b %Y %H:%M:%S' logging.basicConfig(format=log_format, datefmt=date_format) Log.setLevel(level) if logfile is not None: fh = logging.FileHandler(logfile) fh.set...
def write_success_response(self, result): """ Result may be a python dictionary, array or a primitive type that can be converted to JSON for writing back the result. """ response = self.make_success_response(result) now = time.time() spent = now - self.basehandler_starttime response[cons...
def write_error_response(self, message): """ Writes the message as part of the response and sets 404 status. """ self.set_status(404) response = self.make_error_response(str(message)) now = time.time() spent = now - self.basehandler_starttime response[constants.RESPONSE_KEY_EXECUTION_TIM...
def write_json_response(self, response): """ write back json response """ self.write(tornado.escape.json_encode(response)) self.set_header("Content-Type", "application/json")
def make_response(self, status): """ Makes the base dict for the response. The status is the string value for the key "status" of the response. This should be "success" or "failure". """ response = { constants.RESPONSE_KEY_STATUS: status, constants.RESPONSE_KEY_VERSION: const...
def make_success_response(self, result): """ Makes the python dict corresponding to the JSON that needs to be sent for a successful response. Result is the actual payload that gets sent. """ response = self.make_response(constants.RESPONSE_STATUS_SUCCESS) response[constants.RESPONSE_KEY_...
def make_error_response(self, message): """ Makes the python dict corresponding to the JSON that needs to be sent for a failed response. Message is the message that is sent as the reason for failure. """ response = self.make_response(constants.RESPONSE_STATUS_FAILURE) response[constants....
def get_argument_cluster(self): """ Helper function to get request argument. Raises exception if argument is missing. Returns the cluster argument. """ try: return self.get_argument(constants.PARAM_CLUSTER) except tornado.web.MissingArgumentError as e: raise Exception(e.log_messa...
def get_argument_role(self): """ Helper function to get request argument. Raises exception if argument is missing. Returns the role argument. """ try: return self.get_argument(constants.PARAM_ROLE, default=None) except tornado.web.MissingArgumentError as e: raise Exception(e.log_...
def get_argument_environ(self): """ Helper function to get request argument. Raises exception if argument is missing. Returns the environ argument. """ try: return self.get_argument(constants.PARAM_ENVIRON) except tornado.web.MissingArgumentError as e: raise Exception(e.log_messa...
def get_argument_topology(self): """ Helper function to get topology argument. Raises exception if argument is missing. Returns the topology argument. """ try: topology = self.get_argument(constants.PARAM_TOPOLOGY) return topology except tornado.web.MissingArgumentError as e: ...
def get_argument_component(self): """ Helper function to get component argument. Raises exception if argument is missing. Returns the component argument. """ try: component = self.get_argument(constants.PARAM_COMPONENT) return component except tornado.web.MissingArgumentError as ...
def get_argument_instance(self): """ Helper function to get instance argument. Raises exception if argument is missing. Returns the instance argument. """ try: instance = self.get_argument(constants.PARAM_INSTANCE) return instance except tornado.web.MissingArgumentError as e: ...
def get_argument_starttime(self): """ Helper function to get starttime argument. Raises exception if argument is missing. Returns the starttime argument. """ try: starttime = self.get_argument(constants.PARAM_STARTTIME) return starttime except tornado.web.MissingArgumentError as ...
def get_argument_endtime(self): """ Helper function to get endtime argument. Raises exception if argument is missing. Returns the endtime argument. """ try: endtime = self.get_argument(constants.PARAM_ENDTIME) return endtime except tornado.web.MissingArgumentError as e: rai...
def get_argument_query(self): """ Helper function to get query argument. Raises exception if argument is missing. Returns the query argument. """ try: query = self.get_argument(constants.PARAM_QUERY) return query except tornado.web.MissingArgumentError as e: raise Exception...
def get_argument_offset(self): """ Helper function to get offset argument. Raises exception if argument is missing. Returns the offset argument. """ try: offset = self.get_argument(constants.PARAM_OFFSET) return offset except tornado.web.MissingArgumentError as e: raise Exc...
def get_argument_length(self): """ Helper function to get length argument. Raises exception if argument is missing. Returns the length argument. """ try: length = self.get_argument(constants.PARAM_LENGTH) return length except tornado.web.MissingArgumentError as e: raise Exc...
def get_required_arguments_metricnames(self): """ Helper function to get metricname arguments. Notice that it is get_argument"s" variation, which means that this can be repeated. Raises exception if argument is missing. Returns a list of metricname arguments """ try: metricnames = self...
def validateInterval(self, startTime, endTime): """ Helper function to validate interval. An interval is valid if starttime and endtime are integrals, and starttime is less than the endtime. Raises exception if interval is not valid. """ start = int(startTime) end = int(endTime) if s...
def start_connect(self): """Tries to connect to the Heron Server ``loop()`` method needs to be called after this. """ Log.debug("In start_connect() of %s" % self._get_classname()) # TODO: specify buffer size, exception handling self.create_socket(socket.AF_INET, socket.SOCK_STREAM) # when ...
def register_on_message(self, msg_builder): """Registers protobuf message builders that this client wants to receive :param msg_builder: callable to create a protobuf message that this client wants to receive """ message = msg_builder() Log.debug("In register_on_message(): %s" % message.DESCRIPTOR....
def send_request(self, request, context, response_type, timeout_sec): """Sends a request message (REQID is non-zero)""" # generates a unique request id reqid = REQID.generate() Log.debug("%s: In send_request() with REQID: %s" % (self._get_classname(), str(reqid))) # register response message type ...
def send_message(self, message): """Sends a message (REQID is zero)""" Log.debug("In send_message() of %s" % self._get_classname()) outgoing_pkt = OutgoingPacket.create_packet(REQID.generate_zero(), message) self._send_packet(outgoing_pkt)
def handle_timeout(self, reqid): """Handles timeout""" if reqid in self.context_map: context = self.context_map.pop(reqid) self.response_message_map.pop(reqid) self.on_response(StatusCode.TIMEOUT_ERROR, context, None)
def create_tar(tar_filename, files, config_dir, config_files): ''' Create a tar file with a given set of files ''' with contextlib.closing(tarfile.open(tar_filename, 'w:gz', dereference=True)) as tar: for filename in files: if os.path.isfile(filename): tar.add(filename, arcname=os.path.basenam...
def get_subparser(parser, command): ''' Retrieve the given subparser from parser ''' # pylint: disable=protected-access subparsers_actions = [action for action in parser._actions if isinstance(action, argparse._SubParsersAction)] # there will probably only be one subparser_action, ...
def get_heron_dir(): """ This will extract heron directory from .pex file. For example, when __file__ is '/Users/heron-user/bin/heron/heron/tools/common/src/python/utils/config.pyc', and its real path is '/Users/heron-user/.heron/bin/heron/tools/common/src/python/utils/config.pyc', the internal variable ``...
def get_heron_libs(local_jars): """Get all the heron lib jars with the absolute paths""" heron_lib_dir = get_heron_lib_dir() heron_libs = [os.path.join(heron_lib_dir, f) for f in local_jars] return heron_libs
def parse_cluster_role_env(cluster_role_env, config_path): """Parse cluster/[role]/[environ], supply default, if not provided, not required""" parts = cluster_role_env.split('/')[:3] if not os.path.isdir(config_path): Log.error("Config path cluster directory does not exist: %s" % config_path) raise Except...
def get_cluster_role_env(cluster_role_env): """Parse cluster/[role]/[environ], supply empty string, if not provided""" parts = cluster_role_env.split('/')[:3] if len(parts) == 3: return (parts[0], parts[1], parts[2]) if len(parts) == 2: return (parts[0], parts[1], "") if len(parts) == 1: return ...
def direct_mode_cluster_role_env(cluster_role_env, config_path): """Check cluster/[role]/[environ], if they are required""" # otherwise, get the client.yaml file cli_conf_file = os.path.join(config_path, CLIENT_YAML) # if client conf doesn't exist, use default value if not os.path.isfile(cli_conf_file): ...
def server_mode_cluster_role_env(cluster_role_env, config_map): """Check cluster/[role]/[environ], if they are required""" cmap = config_map[cluster_role_env[0]] # if role is required but not provided, raise exception role_present = True if len(cluster_role_env[1]) > 0 else False if ROLE_KEY in cmap and cma...
def defaults_cluster_role_env(cluster_role_env): """ if role is not provided, supply userid if environ is not provided, supply 'default' """ if len(cluster_role_env[1]) == 0 and len(cluster_role_env[2]) == 0: return (cluster_role_env[0], getpass.getuser(), ENVIRON) return (cluster_role_env[0], cluster_...
def parse_override_config_and_write_file(namespace): """ Parse the command line for overriding the defaults and create an override file. """ overrides = parse_override_config(namespace) try: tmp_dir = tempfile.mkdtemp() override_config_file = os.path.join(tmp_dir, OVERRIDE_YAML) with open(overri...
def parse_override_config(namespace): """Parse the command line for overriding the defaults""" overrides = dict() for config in namespace: kv = config.split("=") if len(kv) != 2: raise Exception("Invalid config property format (%s) expected key=value" % config) if kv[1] in ['true', 'True', 'TRUE...
def get_java_path(): """Get the path of java executable""" java_home = os.environ.get("JAVA_HOME") return os.path.join(java_home, BIN_DIR, "java")
def check_java_home_set(): """Check if the java home set""" # check if environ variable is set if "JAVA_HOME" not in os.environ: Log.error("JAVA_HOME not set") return False # check if the value set is correct java_path = get_java_path() if os.path.isfile(java_path) and os.access(java_path, os.X_OK)...
def check_release_file_exists(): """Check if the release.yaml file exists""" release_file = get_heron_release_file() # if the file does not exist and is not a file if not os.path.isfile(release_file): Log.error("Required file not found: %s" % release_file) return False return True
def print_build_info(zipped_pex=False): """Print build_info from release.yaml :param zipped_pex: True if the PEX file is built with flag `zip_safe=False'. """ if zipped_pex: release_file = get_zipped_heron_release_file() else: release_file = get_heron_release_file() with open(release_file) as rele...
def get_version_number(zipped_pex=False): """Print version from release.yaml :param zipped_pex: True if the PEX file is built with flag `zip_safe=False'. """ if zipped_pex: release_file = get_zipped_heron_release_file() else: release_file = get_heron_release_file() with open(release_file) as releas...
def insert_bool(param, command_args): ''' :param param: :param command_args: :return: ''' index = 0 found = False for lelem in command_args: if lelem == '--' and not found: break if lelem == param: found = True break index = index + 1 if found: command_args.insert(in...
def run(command, parser, args, unknown_args): """ run command """ # get the command for detailed help command_help = args['help-command'] # if no command is provided, just print main help if command_help == 'help': parser.print_help() return True # get the subparser for the specific command subp...
def get(self): """ get """ try: cluster = self.get_argument_cluster() environ = self.get_argument_environ() role = self.get_argument_role() topology_name = self.get_argument_topology() component = self.get_argument_component() topology = self.tracker.getTopologyByClusterRoleE...
def getComponentExceptionSummary(self, tmaster, component_name, instances=[], callback=None): """ Get the summary of exceptions for component_name and list of instances. Empty instance list will fetch all exceptions. """ if not tmaster or not tmaster.host or not tmaster.stats_port: return ...
def get(self, cluster, environ, topology): ''' :param cluster: :param environ: :param topology: :return: ''' # pylint: disable=no-member options = dict( cluster=cluster, environ=environ, topology=topology, active="topologies", function=common.class...
def get(self): ''' :return: ''' clusters = yield access.get_clusters() # pylint: disable=no-member options = dict( topologies=[], # no topologies clusters=[str(cluster) for cluster in clusters], active="topologies", # active icon the nav bar function=common.cla...
def get(self, cluster, environ, topology): ''' :param cluster: :param environ: :param topology: :return: ''' # fetch the execution of the topology asynchronously execution_state = yield access.get_execution_state(cluster, environ, topology) # fetch scheduler location of the topolog...
def get(self, cluster, environ, topology, container): ''' :param cluster: :param environ: :param topology: :param container: :return: ''' path = self.get_argument("path") options = dict( cluster=cluster, environ=environ, topology=topology, container=c...
def get(self, cluster, environ, topology, container): ''' :param cluster: :param environ: :param topology: :param container: :return: ''' offset = self.get_argument("offset") length = self.get_argument("length") path = self.get_argument("path") data = yield access.get_contai...
def get(self, cluster, environ, topology, container): ''' :param cluster: :param environ: :param topology: :param container: :return: ''' path = self.get_argument("path", default=".") data = yield access.get_filestats(cluster, environ, topology, container, path) options = dict( ...
def get(self, cluster, environ, topology, container): ''' :param cluster: :param environ: :param topology: :param container: :return: ''' # If the file is large, we want to abandon downloading # if user cancels the requests. # pylint: disable=attribute-defined-outside-init se...
def get(self, path): ''' get method ''' path = tornado.escape.url_unescape(path) if not path: path = "." # User should not be able to access anything outside # of the dir that heron-shell is running in. This ensures # sandboxing. So we don't allow absolute paths and parent # accessing...
def register_watch(self, callback): """ Returns the UUID with which the watch is registered. This UUID can be used to unregister the watch. Returns None if watch could not be registered. The argument 'callback' must be a function that takes exactly one argument, the topology on which th...
def unregister_watch(self, uid): """ Unregister the watch with the given UUID. """ # Do not raise an error if UUID is # not present in the watches. Log.info("Unregister a watch with uid: " + str(uid)) self.watches.pop(uid, None)
def trigger_watches(self): """ Call all the callbacks. If any callback raises an Exception, unregister the corresponding watch. """ to_remove = [] for uid, callback in self.watches.items(): try: callback(self) except Exception as e: Log.error("Caught exception whi...
def set_physical_plan(self, physical_plan): """ set physical plan """ if not physical_plan: self.physical_plan = None self.id = None else: self.physical_plan = physical_plan self.id = physical_plan.topology.id self.trigger_watches()
def set_packing_plan(self, packing_plan): """ set packing plan """ if not packing_plan: self.packing_plan = None self.id = None else: self.packing_plan = packing_plan self.id = packing_plan.id self.trigger_watches()
def set_execution_state(self, execution_state): """ set exectuion state """ if not execution_state: self.execution_state = None self.cluster = None self.environ = None else: self.execution_state = execution_state cluster, environ = self.get_execution_state_dc_environ(execution_...
def num_instances(self): """ Number of spouts + bolts """ num = 0 # Get all the components components = self.spouts() + self.bolts() # Get instances for each worker for component in components: config = component.comp.config for kvs in config.kvs: if kvs.key == api_...
def get_machines(self): """ Get all the machines that this topology is running on. These are the hosts of all the stmgrs. """ if self.physical_plan: stmgrs = list(self.physical_plan.stmgrs) return map(lambda s: s.host_name, stmgrs) return []
def get_status(self): """ Get the current state of this topology. The state values are from the topology.proto RUNNING = 1, PAUSED = 2, KILLED = 3 if the state is None "Unknown" is returned. """ status = None if self.physical_plan and self.physical_plan.topology: status = self.phys...
def convert_pb_kvs(kvs, include_non_primitives=True): """ converts pb kvs to dict """ config = {} for kv in kvs: if kv.value: config[kv.key] = kv.value elif kv.serialized_value: # add serialized_value support for python values (fixme) # is this a serialized java object if topo...
def synch_topologies(self): """ Sync the topologies with the statemgrs. """ self.state_managers = statemanagerfactory.get_all_state_managers(self.config.statemgr_config) try: for state_manager in self.state_managers: state_manager.start() except Exception as ex: Log.error("Fo...
def getTopologyByClusterRoleEnvironAndName(self, cluster, role, environ, topologyName): """ Find and return the topology given its cluster, environ, topology name, and an optional role. Raises exception if topology is not found, or more than one are found. """ topologies = list(filter(lambda t: ...
def getTopologiesForStateLocation(self, name): """ Returns all the topologies for a given state manager. """ return filter(lambda t: t.state_manager_name == name, self.topologies)
def addNewTopology(self, state_manager, topologyName): """ Adds a topology in the local cache, and sets a watch on any changes on the topology. """ topology = Topology(topologyName, state_manager.name) Log.info("Adding new topology: %s, state_manager: %s", topologyName, state_manage...
def removeTopology(self, topology_name, state_manager_name): """ Removes the topology from the local cache. """ topologies = [] for top in self.topologies: if (top.name == topology_name and top.state_manager_name == state_manager_name): # Remove topologyInfo if (topol...
def extract_execution_state(self, topology): """ Returns the repesentation of execution state that will be returned from Tracker. """ execution_state = topology.execution_state executionState = { "cluster": execution_state.cluster, "environ": execution_state.environ, "ro...
def extract_scheduler_location(self, topology): """ Returns the representation of scheduler location that will be returned from Tracker. """ schedulerLocation = { "name": None, "http_endpoint": None, "job_page_link": None, } if topology.scheduler_location: sche...
def extract_tmaster(self, topology): """ Returns the representation of tmaster that will be returned from Tracker. """ tmasterLocation = { "name": None, "id": None, "host": None, "controller_port": None, "master_port": None, "stats_port": None, } ...