Python progress_bar.ProgressBar类代码示例

    def __call__(self, machine_graph, machine, plan_n_timesteps):
        """ Place a machine_graph so that each vertex is placed on a core

        :param machine_graph: The machine_graph to place
        :type machine_graph:\
            :py:class:`pacman.model.graphs.machine.MachineGraph`
        :param machine:\
            The machine with respect to which to partition the application\
            graph
        :type machine: :py:class:`spinn_machine.Machine`
        :param plan_n_timesteps: number of timesteps to plan for
        :type  plan_n_timesteps: int
        :return: A set of placements
        :rtype: :py:class:`pacman.model.placements.Placements`
        :raise pacman.exceptions.PacmanPlaceException: \
            If something goes wrong with the placement
        """

        # check that the algorithm can handle the constraints
        ResourceTracker.check_constraints(machine_graph.vertices)

        placements = Placements()
        vertices = sort_vertices_by_known_constraints(machine_graph.vertices)

        # Iterate over vertices and generate placements
        progress = ProgressBar(vertices, "Placing graph vertices")
        resource_tracker = ResourceTracker(machine, plan_n_timesteps)
        for vertex in progress.over(vertices):
            # Create and store a new placement anywhere on the board
            (x, y, p, _, _) = resource_tracker.allocate_constrained_resources(
                vertex.resources_required, vertex.constraints, None)
            placement = Placement(vertex, x, y, p)
            placements.add_placement(placement)
        return placements

    def __call__(self, report_default_directory, dsg_targets, transceiver):
        """ Creates a report that states where in SDRAM each region is \
            (read from machine)

        :param report_default_directory: the folder where reports are written
        :param dsg_targets: the map between placement and file writer
        :param transceiver: the spinnMan instance
        :rtype: None
        """

        directory_name = os.path.join(
            report_default_directory, MEM_MAP_SUBDIR_NAME)
        if not os.path.exists(directory_name):
            os.makedirs(directory_name)

        progress = ProgressBar(dsg_targets, "Writing memory map reports")
        for (x, y, p) in progress.over(dsg_targets):
            file_name = os.path.join(
                directory_name, MEM_MAP_FILENAME.format(x, y, p))
            try:
                with open(file_name, "w") as f:
                    self._describe_mem_map(f, transceiver, x, y, p)
            except IOError:
                logger.exception("Generate_placement_reports: Can't open file"
                                 " {} for writing.", file_name)

    def __call__(self, report_folder, connection_holder, dsg_targets):
        """ Convert synaptic matrix for every application edge.
        """

        # Update the print options to display everything
        print_opts = numpy.get_printoptions()
        numpy.set_printoptions(threshold=numpy.nan)

        if dsg_targets is None:
            raise SynapticConfigurationException(
                "dsg_targets should not be none, used as a check for "
                "connection holder data to be generated")

        # generate folder for synaptic reports
        top_level_folder = os.path.join(report_folder, _DIRNAME)
        if not os.path.exists(top_level_folder):
            os.mkdir(top_level_folder)

        # create progress bar
        progress = ProgressBar(connection_holder.keys(),
                               "Generating synaptic matrix reports")

        # for each application edge, write matrix in new file
        for edge, _ in progress.over(connection_holder.keys()):
            # only write matrix's for edges which have matrix's
            if isinstance(edge, ProjectionApplicationEdge):
                # figure new file name
                file_name = os.path.join(
                    top_level_folder, _TMPL_FILENAME.format(edge.label))
                self._write_file(file_name, connection_holder, edge)

        # Reset the print options
        numpy.set_printoptions(**print_opts)

    def __call__(self, router_tables):
        tables = MulticastRoutingTables()
        previous_masks = dict()

        progress = ProgressBar(
            len(router_tables.routing_tables) * 2,
            "Compressing Routing Tables")

        # Create all masks without holes
        allowed_masks = [_32_BITS - ((2 ** i) - 1) for i in range(33)]

        # Check that none of the masks have "holes" e.g. 0xFFFF0FFF has a hole
        for router_table in router_tables.routing_tables:
            for entry in router_table.multicast_routing_entries:
                if entry.mask not in allowed_masks:
                    raise PacmanRoutingException(
                        "Only masks without holes are allowed in tables for"
                        " BasicRouteMerger (disallowed mask={})".format(
                            hex(entry.mask)))

        for router_table in progress.over(router_tables.routing_tables):
            new_table = self._merge_routes(router_table, previous_masks)
            tables.add_routing_table(new_table)
            n_entries = len([
                entry for entry in new_table.multicast_routing_entries
                if not entry.defaultable])
            # print("Reduced from {} to {}".format(
            #     len(router_table.multicast_routing_entries), n_entries))
            if n_entries > 1023:
                raise PacmanRoutingException(
                    "Cannot make table small enough: {} entries".format(
                        n_entries))

        return tables

    def __call__(self, router_tables, target_length=None):
        # build storage
        compressed_pacman_router_tables = MulticastRoutingTables()

        # create progress bar
        progress = ProgressBar(
            router_tables.routing_tables, "Compressing routing Tables")

        # compress each router
        for router_table in progress.over(router_tables.routing_tables):
            # convert to rig format
            entries = self._convert_to_mundy_format(router_table)

            # compress the router entries
            compressed_router_table_entries = \
                rigs_compressor.minimise(entries, target_length)

            # convert back to pacman model
            compressed_pacman_table = self._convert_to_pacman_router_table(
                compressed_router_table_entries, router_table.x,
                router_table.y)

            # add to new compressed routing tables
            compressed_pacman_router_tables.add_routing_table(
                compressed_pacman_table)

        # return
        return compressed_pacman_router_tables

    def __call__(
            self, transceiver, tags=None, iptags=None, reverse_iptags=None):
        """
        :param tags: the tags object which contains IP and reverse IP tags.
            could be none if these are being given in separate lists
        :param iptags: a list of IP tags, given when tags is none
        :param reverse_iptags: a list of reverse IP tags when tags is none.
        :param transceiver: the transceiver object
        """
        # clear all the tags from the Ethernet connection, as nothing should
        # be allowed to use it (no two apps should use the same Ethernet
        # connection at the same time)
        progress = ProgressBar(MAX_TAG_ID, "Clearing tags")
        for tag_id in progress.over(range(MAX_TAG_ID)):
            transceiver.clear_ip_tag(tag_id)

        # Use tags object to supply tag info if it is supplied
        if tags is not None:
            iptags = list(tags.ip_tags)
            reverse_iptags = list(tags.reverse_ip_tags)

        # Load the IP tags and the Reverse IP tags
        progress = ProgressBar(
            len(iptags) + len(reverse_iptags), "Loading Tags")
        self.load_iptags(iptags, transceiver, progress)
        self.load_reverse_iptags(reverse_iptags, transceiver, progress)
        progress.end()

    def __call__(self, txrx, app_id, all_core_subsets):
        # check that the right number of processors are in sync
        processors_completed = txrx.get_core_state_count(
            app_id, CPUState.FINISHED)
        total_processors = len(all_core_subsets)
        left_to_do_cores = total_processors - processors_completed

        progress = ProgressBar(
            left_to_do_cores,
            "Forcing error cores to generate provenance data")

        error_cores = txrx.get_cores_in_state(
            all_core_subsets, CPUState.RUN_TIME_EXCEPTION)
        watchdog_cores = txrx.get_cores_in_state(
            all_core_subsets, CPUState.WATCHDOG)
        idle_cores = txrx.get_cores_in_state(
            all_core_subsets, CPUState.IDLE)

        if error_cores or watchdog_cores or idle_cores:
            raise ConfigurationException(
                "Some cores have crashed. RTE cores {}, watch-dogged cores {},"
                " idle cores {}".format(
                    error_cores.values(), watchdog_cores.values(),
                    idle_cores.values()))

        # check that all cores are in the state FINISHED which shows that
        # the core has received the message and done provenance updating
        self._update_provenance(txrx, total_processors, processors_completed,
                                all_core_subsets, app_id, progress)
        progress.end()

    def __call__(
            self, live_packet_gatherer_parameters, machine, machine_graph,
            application_graph=None, graph_mapper=None):
        """ Add LPG vertices on Ethernet connected chips as required.

        :param live_packet_gatherer_parameters:\
            the Live Packet Gatherer parameters requested by the script
        :param machine: the SpiNNaker machine as discovered
        :param application_graph: the application graph
        :param machine_graph: the machine graph
        :return: mapping between LPG parameters and LPG vertex
        """
        # pylint: disable=too-many-arguments

        # create progress bar
        progress = ProgressBar(
            machine.ethernet_connected_chips,
            string_describing_what_being_progressed=(
                "Adding Live Packet Gatherers to Graph"))

        # Keep track of the vertices added by parameters and board address
        lpg_params_to_vertices = defaultdict(dict)

        # for every Ethernet connected chip, add the gatherers required
        for chip in progress.over(machine.ethernet_connected_chips):
            for params in live_packet_gatherer_parameters:
                if (params.board_address is None or
                        params.board_address == chip.ip_address):
                    lpg_params_to_vertices[params][chip.x, chip.y] = \
                        self._add_lpg_vertex(application_graph, graph_mapper,
                                             machine_graph, chip, params)

        return lpg_params_to_vertices

    def __call__(
            self, transceiver, placements, provenance_file_path,
            run_time_ms, machine_time_step):
        """
        :param transceiver: the SpiNNMan interface object
        :param placements: The placements of the vertices
        :param has_ran: token that states that the simulation has ran
        :param provenance_file_path: The location to store the profile data
        :param run_time_ms: runtime in ms
        :param machine_time_step: machine time step in ms
        """
        # pylint: disable=too-many-arguments
        machine_time_step_ms = machine_time_step // 1000

        progress = ProgressBar(
            placements.n_placements, "Getting profile data")

        # retrieve provenance data from any cores that provide data
        for placement in progress.over(placements.placements):
            if isinstance(placement.vertex, AbstractHasProfileData):
                # get data
                profile_data = placement.vertex.get_profile_data(
                    transceiver, placement)
                if profile_data.tags:
                    self._write(placement, profile_data, run_time_ms,
                                machine_time_step_ms, provenance_file_path)

    def get_spikes(self, label, buffer_manager, region,
                   placements, graph_mapper, application_vertex,
                   base_key_function, machine_time_step):
        # pylint: disable=too-many-arguments
        results = list()
        missing = []
        ms_per_tick = machine_time_step / 1000.0
        vertices = graph_mapper.get_machine_vertices(application_vertex)
        progress = ProgressBar(vertices,
                               "Getting spikes for {}".format(label))
        for vertex in progress.over(vertices):
            placement = placements.get_placement_of_vertex(vertex)
            vertex_slice = graph_mapper.get_slice(vertex)

            # Read the spikes
            raw_spike_data, data_missing = \
                buffer_manager.get_data_by_placement(placement, region)
            if data_missing:
                missing.append(placement)
            self._process_spike_data(
                vertex_slice, raw_spike_data, ms_per_tick,
                base_key_function(vertex), results)

        if missing:
            missing_str = recording_utils.make_missing_string(missing)
            logger.warning(
                "Population {} is missing spike data in region {} from the"
                " following cores: {}", label, region, missing_str)
        if not results:
            return numpy.empty(shape=(0, 2))
        result = numpy.vstack(results)
        return result[numpy.lexsort((result[:, 1], result[:, 0]))]

    def __call__(
            self, live_packet_gatherer_parameters, placements,
            live_packet_gatherers_to_vertex_mapping, machine,
            machine_graph, application_graph=None, graph_mapper=None):
        """
        :param live_packet_gatherer_parameters: the set of parameters
        :param placements: the placements object
        :param live_packet_gatherers_to_vertex_mapping:\
            the mapping of LPG parameters and the machine vertices associated\
            with it
        :param machine: the SpiNNaker machine
        :param machine_graph: the machine graph
        :param application_graph:  the app graph
        :param graph_mapper: the graph mapper between app and machine graph
        :rtype: None
        """
        # pylint: disable=too-many-arguments
        progress = ProgressBar(
            live_packet_gatherer_parameters,
            string_describing_what_being_progressed=(
                "Adding edges to the machine graph between the vertices to "
                "which live output has been requested and its local Live "
                "Packet Gatherer"))

        for lpg_params in progress.over(live_packet_gatherer_parameters):
            # locate vertices needed to be connected to a LPG with these params
            for vertex in live_packet_gatherer_parameters[lpg_params]:
                self._connect_lpg_vertex(
                    application_graph, graph_mapper, machine,
                    placements, machine_graph, vertex,
                    live_packet_gatherers_to_vertex_mapping, lpg_params)

    def __call__(self, machine_graph, machine, plan_n_timesteps):
        """ Place each vertex in a machine graph on a core in the machine.

        :param machine_graph: The machine_graph to place
        :type machine_graph:\
            :py:class:`pacman.model.graphs.machine.MachineGraph`
        :param machine: A SpiNNaker machine object.
        :type machine: :py:class:`spinn_machine.Machine`
        :param plan_n_timesteps: number of timesteps to plan for
        :type  plan_n_timesteps: int
        :return placements: Placements of vertices on the machine
        :rtype :py:class:`pacman.model.placements.Placements`
        """

        # check that the algorithm can handle the constraints
        ResourceTracker.check_constraints(machine_graph.vertices)

        placements = Placements()
        vertices = sort_vertices_by_known_constraints(machine_graph.vertices)

        # Iterate over vertices and generate placements
        progress = ProgressBar(machine_graph.n_vertices,
                               "Placing graph vertices")
        resource_tracker = ResourceTracker(
            machine, plan_n_timesteps, self._generate_random_chips(machine))
        vertices_on_same_chip = get_same_chip_vertex_groups(machine_graph)
        vertices_placed = set()
        for vertex in progress.over(vertices):
            if vertex not in vertices_placed:
                vertices_placed.update(self._place_vertex(
                    vertex, resource_tracker, machine, placements,
                    vertices_on_same_chip))
        return placements

    def __call__(self, report_default_directory, machine):
        """ Creates a report that states where in SDRAM each region is.

        :param report_default_directory: the folder where reports are written
        :param machine: python representation of the machine
        :rtype: None
        """

        # create file path
        directory_name = os.path.join(
            report_default_directory, self.AREA_CODE_REPORT_NAME)

        # create the progress bar for end users
        progress_bar = ProgressBar(
            len(machine.ethernet_connected_chips),
            "Writing the board chip report")

        # iterate over ethernet chips and then the chips on that board
        with open(directory_name, "w") as writer:
            for ethernet_connected_chip in \
                    progress_bar.over(machine.ethernet_connected_chips):
                chips = machine.get_chips_on_board(ethernet_connected_chip)
                writer.write(
                    "board with IP address : {} : has chips {}\n".format(
                        ethernet_connected_chip.ip_address, list(chips)))

    def __call__(self, machine_graph, graph_mapper):
        """
        :param machine_graph: the machine_graph whose edges are to be filtered
        :param graph_mapper: the graph mapper between graphs
        :return: a new graph mapper and machine graph
        """
        new_machine_graph = MachineGraph(label=machine_graph.label)
        new_graph_mapper = GraphMapper()

        # create progress bar
        progress = ProgressBar(
            machine_graph.n_vertices +
            machine_graph.n_outgoing_edge_partitions,
            "Filtering edges")

        # add the vertices directly, as they wont be pruned.
        for vertex in progress.over(machine_graph.vertices, False):
            self._add_vertex_to_new_graph(
                vertex, graph_mapper, new_machine_graph, new_graph_mapper)

        # start checking edges to decide which ones need pruning....
        for partition in progress.over(machine_graph.outgoing_edge_partitions):
            for edge in partition.edges:
                if self._is_filterable(edge, graph_mapper):
                    logger.debug("this edge was pruned %s", edge)
                    continue
                logger.debug("this edge was not pruned %s", edge)
                self._add_edge_to_new_graph(
                    edge, partition, graph_mapper, new_machine_graph,
                    new_graph_mapper)

        # returned the pruned graph and graph_mapper
        return new_machine_graph, new_graph_mapper

    def __call__(
            self, placements, hostname,
            report_default_directory, write_text_specs,
            machine, graph_mapper=None, placement_order=None):
        """
        :param placements: placements of machine graph to cores
        :param hostname: SpiNNaker machine name
        :param report_default_directory: the location where reports are stored
        :param write_text_specs:\
            True if the textual version of the specification is to be written
        :param machine: the python representation of the SpiNNaker machine
        :param graph_mapper:\
            the mapping between application and machine graph
        :param placement:\
            the optional order in which placements should be examined
        :return: DSG targets (map of placement tuple and filename)
        """
        # pylint: disable=too-many-arguments, too-many-locals
        # pylint: disable=attribute-defined-outside-init
        self._machine = machine
        self._hostname = hostname
        self._report_dir = report_default_directory
        self._write_text = write_text_specs

        # iterate though vertices and call generate_data_spec for each
        # vertex
        targets = DataSpecificationTargets(machine, self._report_dir)

        if placement_order is None:
            placement_order = placements.placements

        progress = ProgressBar(
            placements.n_placements, "Generating data specifications")
        vertices_to_reset = list()
        for placement in progress.over(placement_order):
            # Try to generate the data spec for the placement
            generated = self.__generate_data_spec_for_vertices(
                placement, placement.vertex, targets)

            if generated and isinstance(
                    placement.vertex, AbstractRewritesDataSpecification):
                vertices_to_reset.append(placement.vertex)

            # If the spec wasn't generated directly, and there is an
            # application vertex, try with that
            if not generated and graph_mapper is not None:
                associated_vertex = graph_mapper.get_application_vertex(
                    placement.vertex)
                generated = self.__generate_data_spec_for_vertices(
                    placement, associated_vertex, targets)
                if generated and isinstance(
                        associated_vertex, AbstractRewritesDataSpecification):
                    vertices_to_reset.append(associated_vertex)

        # Ensure that the vertices know their regions have been reloaded
        for vertex in vertices_to_reset:
            vertex.mark_regions_reloaded()

        return targets