def get_v(self, gather=True, compatible_output=False):
"""
Return a 3-column numpy array containing cell ids, time, and Vm for
recorded cells.
:param gather:
not used - inserted to match PyNN specs
:type gather: bool
:param compatible_output:
not used - inserted to match PyNN specs
:type compatible_output: bool
"""
if self._v is None:
timer = None
if conf.config.getboolean("Reports", "outputTimesForSections"):
timer = Timer()
timer.start_timing()
self._v = self._vertex.get_v(
has_ran=self._spinnaker.has_ran,
txrx=self._spinnaker.transceiver,
placements=self._spinnaker.placements,
machine_time_step=self._spinnaker.machine_time_step,
graph_mapper=self._spinnaker.graph_mapper,
compatible_output=compatible_output)
if conf.config.getboolean("Reports", "outputTimesForSections"):
timer.take_sample()
return self._v
def getSpikes(self, compatible_output=False, gather=True):
"""
Return a 2-column numpy array containing cell ids and spike times for
recorded cells. This is read directly from the memory for the board.
"""
if self._spikes is None:
if not gather:
logger.warn("Spynnaker only supports gather = true, will "
" execute as if gather was true anyhow")
timer = None
if not self._vertex.record:
raise exceptions.ConfigurationException(
"This population has not been set to record spikes. "
"Therefore spikes cannot be retrieved. Please set this "
"vertex to record spikes before running this command.")
if not self._spinnaker.has_ran:
raise local_exceptions.SpynnakerException(
"The simulation has not yet ran, therefore spikes cannot"
" be retrieved. Please execute the simulation before"
" running this command")
if conf.config.getboolean("Reports", "outputTimesForSections"):
timer = Timer()
timer.start_timing()
self._spikes = self._vertex.get_spikes(
txrx=self._spinnaker.transceiver,
placements=self._spinnaker.placements,
graph_mapper=self._spinnaker.graph_mapper,
compatible_output=compatible_output)
if conf.config.getboolean("Reports", "outputTimesForSections"):
timer.take_sample()
return self._spikes
def get_gsyn(self, gather=True, compatible_output=False):
"""
Return a 3-column numpy array containing cell ids and synaptic
conductances for recorded cells.
"""
if self._gsyn is None:
if not self._vertex.record_gsyn:
raise exceptions.ConfigurationException(
"This population has not been set to record gsyn. "
"Therefore gsyn cannot be retrieved. Please set this "
"vertex to record gsyn before running this command.")
if not self._spinnaker.has_ran:
raise local_exceptions.SpynnakerException(
"The simulation has not yet run, therefore gsyn cannot"
" be retrieved. Please execute the simulation before"
" running this command")
timer = None
if conf.config.getboolean("Reports", "outputTimesForSections"):
timer = Timer()
timer.start_timing()
self._gsyn = self._vertex.get_gsyn(
has_ran=self._spinnaker.has_ran,
txrx=self._spinnaker.transceiver,
placements=self._spinnaker.placements,
machine_time_step=self._spinnaker.machine_time_step,
graph_mapper=self._spinnaker.graph_mapper,
compatible_output=compatible_output,
runtime=self._spinnaker._runtime)
if conf.config.getboolean("Reports", "outputTimesForSections"):
timer.take_sample()
return self._gsyn
def get_synaptic_list_from_machine(self, graph_mapper, partitioned_graph,
placements, transceiver, routing_infos):
"""
Get synaptic data for all connections in this Projection from the
machine.
"""
if self._stored_synaptic_data_from_machine is None:
timer = None
if conf.config.getboolean("Reports", "outputTimesForSections"):
timer = Timer()
timer.start_timing()
subedges = \
graph_mapper.get_partitioned_edges_from_partitionable_edge(
self)
if subedges is None:
subedges = list()
synaptic_list = copy.copy(self._synapse_list)
synaptic_list_rows = synaptic_list.get_rows()
progress_bar = ProgressBar(
len(subedges),
"Reading back synaptic matrix for edge between"
" {} and {}".format(self._pre_vertex.label,
self._post_vertex.label))
for subedge in subedges:
n_rows = subedge.get_n_rows(graph_mapper)
pre_vertex_slice = \
graph_mapper.get_subvertex_slice(subedge.pre_subvertex)
post_vertex_slice = \
graph_mapper.get_subvertex_slice(subedge.post_subvertex)
sub_edge_post_vertex = \
graph_mapper.get_vertex_from_subvertex(
subedge.post_subvertex)
rows = sub_edge_post_vertex.get_synaptic_list_from_machine(
placements, transceiver, subedge.pre_subvertex, n_rows,
subedge.post_subvertex,
self._synapse_row_io, partitioned_graph,
routing_infos, subedge.weight_scales).get_rows()
for i in range(len(rows)):
synaptic_list_rows[
i + pre_vertex_slice.lo_atom].set_slice_values(
rows[i], vertex_slice=post_vertex_slice)
progress_bar.update()
progress_bar.end()
self._stored_synaptic_data_from_machine = synaptic_list
if conf.config.getboolean("Reports", "outputTimesForSections"):
logger.info("Time to read matrix: {}".format(
timer.take_sample()))
return self._stored_synaptic_data_from_machine
def get_v(self, gather=True, compatible_output=False):
"""
Return a 3-column numpy array containing cell ids, time, and Vm for
recorded cells.
:param gather:
not used - inserted to match PyNN specs
:type gather: bool
:param compatible_output:
not used - inserted to match PyNN specs
:type compatible_output: bool
"""
if self._v_cache_file is None:
if not self._vertex.record_v:
raise exceptions.ConfigurationException(
"This population has not been set to record v. "
"Therefore v cannot be retrieved. Please set this "
"vertex to record v before running this command.")
if not self._spinnaker.has_ran:
raise local_exceptions.SpynnakerException(
"The simulation has not yet run, therefore v cannot"
" be retrieved. Please execute the simulation before"
" running this command")
timer = None
if conf.config.getboolean("Reports", "outputTimesForSections"):
timer = Timer()
timer.start_timing()
v = self._vertex.get_v(
has_ran=self._spinnaker.has_ran,
txrx=self._spinnaker.transceiver,
placements=self._spinnaker.placements,
machine_time_step=self._spinnaker.machine_time_step,
graph_mapper=self._spinnaker.graph_mapper,
compatible_output=compatible_output,
runtime=self._spinnaker._runtime)
if conf.config.getboolean("Reports", "outputTimesForSections"):
logger.info("Time to read v: {}".format(timer.take_sample()))
self._v_cache_file = tempfile.NamedTemporaryFile()
numpy.save(self._v_cache_file, v)
return v
# Reload the data
self._v_cache_file.seek(0)
return numpy.load(self._v_cache_file)
def getSpikes(self, compatible_output=False, gather=True):
"""
Return a 2-column numpy array containing cell ids and spike times for
recorded cells. This is read directly from the memory for the board.
"""
if self._spikes_cache_file is None:
if not gather:
logger.warn("Spynnaker only supports gather = true, will "
" execute as if gather was true anyhow")
timer = None
if not self._vertex.is_recording_spikes():
raise exceptions.ConfigurationException(
"This population has not been set to record spikes. "
"Therefore spikes cannot be retrieved. Please set this "
"vertex to record spikes before running this command.")
if not self._spinnaker.has_ran:
raise local_exceptions.SpynnakerException(
"The simulation has not yet run, therefore spikes cannot"
" be retrieved. Please execute the simulation before"
" running this command")
if conf.config.getboolean("Reports", "outputTimesForSections"):
timer = Timer()
timer.start_timing()
spikes = self._vertex.get_spikes(
self._spinnaker.transceiver,
self._spinnaker.no_machine_time_steps,
self._spinnaker.placements,
self._spinnaker.graph_mapper)
if conf.config.getboolean("Reports", "outputTimesForSections"):
logger.info("Time to get spikes: {}".format(
timer.take_sample()))
self._spikes_cache_file = tempfile.NamedTemporaryFile()
numpy.save(self._spikes_cache_file, spikes)
return spikes
# Load from the file
self._spikes_cache_file.seek(0)
return numpy.load(self._spikes_cache_file)
def get_gsyn(self, gather=True, compatible_output=False):
"""
Return a 3-column numpy array containing cell ids and synaptic
conductances for recorded cells.
"""
if self._gsyn is None:
timer = None
if conf.config.getboolean("Reports", "outputTimesForSections"):
timer = Timer()
timer.start_timing()
self._gsyn = self._vertex.get_gsyn(
has_ran=self._spinnaker.has_ran,
txrx=self._spinnaker.transceiver,
placements=self._spinnaker.placements,
machine_time_step=self._spinnaker.machine_time_step,
graph_mapper=self._spinnaker.graph_mapper,
compatible_output=compatible_output)
if conf.config.getboolean("Reports", "outputTimesForSections"):
timer.take_sample()
return self._gsyn
def get_gsyn(self, gather=True, compatible_output=False):
"""
Return a 3-column numpy array containing cell ids and synaptic
conductances for recorded cells.
"""
if self._gsyn is None:
if not self._vertex.record_gsyn:
raise exceptions.ConfigurationException(
"This population has not been set to record gsyn. "
"Therefore gsyn cannot be retrieved. Please set this "
"vertex to record gsyn before running this command.")
if not self._spinnaker.has_ran:
raise local_exceptions.SpynnakerException(
"The simulation has not yet run, therefore gsyn cannot"
" be retrieved. Please execute the simulation before"
" running this command")
timer = None
if conf.config.getboolean("Reports", "outputTimesForSections"):
timer = Timer()
timer.start_timing()
self._gsyn = self._vertex.get_gsyn(
has_ran=self._spinnaker.has_ran,
txrx=self._spinnaker.transceiver,
placements=self._spinnaker.placements,
machine_time_step=self._spinnaker.machine_time_step,
graph_mapper=self._spinnaker.graph_mapper,
compatible_output=compatible_output,
runtime=self._spinnaker._runtime)
if conf.config.getboolean("Reports", "outputTimesForSections"):
timer.take_sample()
return self._gsyn
def getSpikes(self, compatible_output=False, gather=True):
"""
Return a 2-column numpy array containing cell ids and spike times for
recorded cells. This is read directly from the memory for the board.
"""
if self._spikes is None:
if not gather:
logger.warn("Spynnaker only supports gather = true, will "
" execute as if gather was true anyhow")
timer = None
if not self._vertex.record:
raise exceptions.ConfigurationException(
"This population has not been set to record spikes. "
"Therefore spikes cannot be retrieved. Please set this "
"vertex to record spikes before running this command.")
if not self._spinnaker.has_ran:
raise local_exceptions.SpynnakerException(
"The simulation has not yet run, therefore spikes cannot"
" be retrieved. Please execute the simulation before"
" running this command")
if conf.config.getboolean("Reports", "outputTimesForSections"):
timer = Timer()
timer.start_timing()
self._spikes = self._vertex.get_spikes(
txrx=self._spinnaker.transceiver,
placements=self._spinnaker.placements,
graph_mapper=self._spinnaker.graph_mapper,
compatible_output=compatible_output)
if conf.config.getboolean("Reports", "outputTimesForSections"):
timer.take_sample()
return self._spikes
def test_timer(self):
timer = Timer()
timer.start_timing()
sleep(0.1)
end_time = timer.take_sample().total_seconds()
self.assertAlmostEqual(end_time, 0.1, delta=0.02)
sleep(0.2)
self.assertAlmostEqual(timer.take_sample().total_seconds(),
end_time + 0.2, delta=0.02)
def get_gsyn(self, gather=True, compatible_output=False):
"""
Return a 3-column numpy array containing cell ids and synaptic
conductances for recorded cells.
"""
if self._gsyn_cache_file is None:
if not self._vertex.is_recording_gsyn():
raise exceptions.ConfigurationException(
"This population has not been set to record gsyn. "
"Therefore gsyn cannot be retrieved. Please set this "
"vertex to record gsyn before running this command.")
if not self._spinnaker.has_ran:
raise local_exceptions.SpynnakerException(
"The simulation has not yet run, therefore gsyn cannot"
" be retrieved. Please execute the simulation before"
" running this command")
timer = None
if conf.config.getboolean("Reports", "outputTimesForSections"):
timer = Timer()
timer.start_timing()
gsyn = self._vertex.get_gsyn(
self._spinnaker.transceiver,
self._spinnaker.no_machine_time_steps,
self._spinnaker.placements,
self._spinnaker.graph_mapper)
if conf.config.getboolean("Reports", "outputTimesForSections"):
logger.info("Time to get gsyn: {}".format(timer.take_sample()))
self._gsyn_cache_file = tempfile.NamedTemporaryFile()
numpy.save(self._gsyn_cache_file, gsyn)
return gsyn
# Reload the data
self._gsyn_cache_file.seek(0)
numpy.load(self._gsyn_cache_file)
def get_synaptic_list_from_machine(self, graph_mapper, partitioned_graph,
placements, transceiver, routing_infos):
"""
Get synaptic data for all connections in this Projection from the
machine.
"""
if self._stored_synaptic_data_from_machine is None:
timer = None
if conf.config.getboolean("Reports", "outputTimesForSections"):
timer = Timer()
timer.start_timing()
logger.debug(
"Reading synapse data for edge between {} and {}".format(
self._pre_vertex.label, self._post_vertex.label))
subedges = \
graph_mapper.get_partitioned_edges_from_partitionable_edge(
self)
if subedges is None:
subedges = list()
synaptic_list = copy.copy(self._synapse_list)
synaptic_list_rows = synaptic_list.get_rows()
progress_bar = ProgressBar(
len(subedges), "progress on reading back synaptic matrix")
for subedge in subedges:
n_rows = subedge.get_n_rows(graph_mapper)
pre_vertex_slice = \
graph_mapper.get_subvertex_slice(subedge.pre_subvertex)
post_vertex_slice = \
graph_mapper.get_subvertex_slice(subedge.post_subvertex)
sub_edge_post_vertex = \
graph_mapper.get_vertex_from_subvertex(
subedge.post_subvertex)
rows = sub_edge_post_vertex.get_synaptic_list_from_machine(
placements, transceiver, subedge.pre_subvertex, n_rows,
subedge.post_subvertex, self._synapse_row_io,
partitioned_graph, routing_infos,
subedge.weight_scales).get_rows()
for i in range(len(rows)):
synaptic_list_rows[
i + pre_vertex_slice.lo_atom].set_slice_values(
rows[i], vertex_slice=post_vertex_slice)
progress_bar.update()
progress_bar.end()
self._stored_synaptic_data_from_machine = synaptic_list
if conf.config.getboolean("Reports", "outputTimesForSections"):
timer.take_sample()
return self._stored_synaptic_data_from_machine
def get_v(self, gather=True, compatible_output=False):
"""
Return a 3-column numpy array containing cell ids, time, and Vm for
recorded cells.
:param gather:
not used - inserted to match PyNN specs
:type gather: bool
:param compatible_output:
not used - inserted to match PyNN specs
:type compatible_output: bool
"""
if self._v is None:
if not self._vertex.record_v:
raise exceptions.ConfigurationException(
"This population has not been set to record v. "
"Therefore v cannot be retrieved. Please set this "
"vertex to record v before running this command.")
if not self._spinnaker.has_ran:
raise local_exceptions.SpynnakerException(
"The simulation has not yet run, therefore v cannot"
" be retrieved. Please execute the simulation before"
" running this command")
timer = None
if conf.config.getboolean("Reports", "outputTimesForSections"):
timer = Timer()
timer.start_timing()
self._v = self._vertex.get_v(
has_ran=self._spinnaker.has_ran,
txrx=self._spinnaker.transceiver,
placements=self._spinnaker.placements,
machine_time_step=self._spinnaker.machine_time_step,
graph_mapper=self._spinnaker.graph_mapper,
compatible_output=compatible_output,
runtime=self._spinnaker._runtime)
if conf.config.getboolean("Reports", "outputTimesForSections"):
timer.take_sample()
return self._v
def get_synaptic_list_from_machine(self, graph_mapper, partitioned_graph,
placements, transceiver, routing_infos):
"""
Get synaptic data for all connections in this Projection from the
machine.
:param graph_mapper:
:param partitioned_graph:
:param placements:
:param transceiver:
:param routing_infos:
:return:
"""
if self._stored_synaptic_data_from_machine is None:
logger.debug("Reading synapse data for edge between {} and {}"
.format(self._pre_vertex.label,
self._post_vertex.label))
timer = None
if conf.config.getboolean("Reports", "outputTimesForSections"):
timer = Timer()
timer.start_timing()
subedges = \
graph_mapper.get_partitioned_edges_from_partitionable_edge(
self)
if subedges is None:
subedges = list()
synaptic_list = copy.copy(self._synapse_list)
synaptic_list_rows = synaptic_list.get_rows()
progress_bar = ProgressBar(
len(subedges), "progress on reading back synaptic matrix")
for subedge in subedges:
n_rows = subedge.get_n_rows(graph_mapper)
pre_vertex_slice = \
graph_mapper.get_subvertex_slice(subedge.pre_subvertex)
post_vertex_slice = \
graph_mapper.get_subvertex_slice(subedge.post_subvertex)
sub_edge_post_vertex = \
graph_mapper.get_vertex_from_subvertex(
subedge.post_subvertex)
rows = sub_edge_post_vertex.get_synaptic_list_from_machine(
placements, transceiver, subedge.pre_subvertex, n_rows,
subedge.post_subvertex,
self._synapse_row_io, partitioned_graph,
routing_infos, subedge.weight_scales).get_rows()
for i in range(len(rows)):
delay_stage = math.floor(
float(i) / float(pre_vertex_slice.n_atoms)) + 1
min_delay = (delay_stage *
self.pre_vertex.max_delay_per_neuron)
max_delay = (min_delay +
self.pre_vertex.max_delay_per_neuron - 1)
synaptic_list_rows[
(i % pre_vertex_slice.n_atoms) +
pre_vertex_slice.lo_atom].set_slice_values(
rows[i], post_vertex_slice, min_delay, max_delay)
progress_bar.update()
progress_bar.end()
self._stored_synaptic_data_from_machine = synaptic_list
if conf.config.getboolean("Reports", "outputTimesForSections"):
timer.take_sample()
return self._stored_synaptic_data_from_machine
def run(self, run_time):
"""
:param run_time:
:return:
"""
self._setup_interfaces(
hostname=self._hostname,
virtual_x_dimension=config.getint("Machine",
"virtual_board_x_dimension"),
virtual_y_dimension=config.getint("Machine",
"virtual_board_y_dimension"),
downed_chips=config.get("Machine", "down_chips"),
downed_cores=config.get("Machine", "down_cores"),
requires_virtual_board=config.getboolean("Machine",
"virtual_board"),
requires_wrap_around=config.getboolean("Machine",
"requires_wrap_arounds"),
machine_version=config.getint("Machine", "version"))
# add database generation if requested
if self._create_database:
wait_on_confirmation = \
config.getboolean("Database", "wait_on_confirmation")
self._database_interface = DataBaseInterface(
self._app_data_runtime_folder, wait_on_confirmation,
self._database_socket_addresses)
# create network report if needed
if self._reports_states is not None:
reports.network_specification_partitionable_report(
self._report_default_directory, self._partitionable_graph,
self._hostname)
# calculate number of machine time steps
if run_time is not None:
self._no_machine_time_steps =\
int((run_time * 1000.0) / self._machine_time_step)
ceiled_machine_time_steps = \
math.ceil((run_time * 1000.0) / self._machine_time_step)
if self._no_machine_time_steps != ceiled_machine_time_steps:
raise common_exceptions.ConfigurationException(
"The runtime and machine time step combination result in "
"a factional number of machine runable time steps and "
"therefore spinnaker cannot determine how many to run for")
for vertex in self._partitionable_graph.vertices:
if isinstance(vertex, AbstractDataSpecableVertex):
vertex.set_no_machine_time_steps(
self._no_machine_time_steps)
else:
self._no_machine_time_steps = None
logger.warn("You have set a runtime that will never end, this may"
"cause the neural models to fail to partition "
"correctly")
for vertex in self._partitionable_graph.vertices:
if vertex.is_set_to_record_spikes():
raise common_exceptions.ConfigurationException(
"recording a population when set to infinite runtime "
"is not currently supportable in this tool chain."
"watch this space")
do_timing = config.getboolean("Reports", "outputTimesForSections")
if do_timing:
timer = Timer()
else:
timer = None
self.set_runtime(run_time)
logger.info("*** Running Mapper *** ")
if do_timing:
timer.start_timing()
self.map_model()
if do_timing:
timer.take_sample()
# load database if needed
if self._create_database:
self._database_interface.add_system_params(
self._time_scale_factor, self._machine_time_step,
self._runtime)
self._database_interface.add_machine_objects(self._machine)
self._database_interface.add_partitionable_vertices(
self._partitionable_graph)
self._database_interface.add_partitioned_vertices(
self._partitioned_graph, self._graph_mapper,
self._partitionable_graph)
self._database_interface.add_placements(self._placements,
self._partitioned_graph)
self._database_interface.add_routing_infos(
self._routing_infos, self._partitioned_graph)
self._database_interface.add_routing_tables(self._router_tables)
self._database_interface.add_tags(self._partitioned_graph,
self._tags)
execute_mapping = config.getboolean(
"Database", "create_routing_info_to_neuron_id_mapping")
if execute_mapping:
self._database_interface.create_neuron_to_key_mapping(
graph_mapper=self._graph_mapper,
partitionable_graph=self._partitionable_graph,
partitioned_graph=self._partitioned_graph,
routing_infos=self._routing_infos)
self._database_interface.send_read_notification()
# execute data spec generation
if do_timing:
timer.start_timing()
logger.info("*** Generating Output *** ")
logger.debug("")
executable_targets = self.generate_data_specifications()
if do_timing:
timer.take_sample()
# execute data spec execution
if do_timing:
timer.start_timing()
processor_to_app_data_base_address = \
self.execute_data_specification_execution(
config.getboolean("SpecExecution", "specExecOnHost"),
self._hostname, self._placements, self._graph_mapper,
write_text_specs=config.getboolean(
"Reports", "writeTextSpecs"),
runtime_application_data_folder=self._app_data_runtime_folder)
if self._reports_states is not None:
reports.write_memory_map_report(self._report_default_directory,
processor_to_app_data_base_address)
if do_timing:
timer.take_sample()
if (not isinstance(self._machine, VirtualMachine) and
config.getboolean("Execute", "run_simulation")):
if do_timing:
timer.start_timing()
logger.info("*** Loading tags ***")
self._load_tags(self._tags)
if self._do_load is True:
logger.info("*** Loading data ***")
self._load_application_data(
self._placements, self._router_tables, self._graph_mapper,
processor_to_app_data_base_address, self._hostname,
self._app_id,
machine_version=config.getint("Machine", "version"),
app_data_folder=self._app_data_runtime_folder)
logger.info("*** Loading executables ***")
self._load_executable_images(
executable_targets, self._app_id,
app_data_folder=self._app_data_runtime_folder)
logger.info("*** Loading buffers ***")
self._set_up_send_buffering()
# end of entire loading setup
if do_timing:
timer.take_sample()
if self._do_run is True:
logger.info("*** Running simulation... *** ")
if self._reports_states.transciever_report:
reports.re_load_script_running_aspects(
self._app_data_runtime_folder, executable_targets,
self._hostname, self._app_id, run_time)
# every thing is in sync0. load the initial buffers
self._send_buffer_manager.load_initial_buffers()
wait_on_confirmation = config.getboolean(
"Database", "wait_on_confirmation")
send_start_notification = config.getboolean(
"Database", "send_start_notification")
self._wait_for_cores_to_be_ready(executable_targets,
self._app_id)
# wait till external app is ready for us to start if required
if (self._database_interface is not None and
wait_on_confirmation):
logger.info(
"*** Awaiting for a response from an external source "
"to state its ready for the simulation to start ***")
self._database_interface.wait_for_confirmation()
self._start_all_cores(executable_targets, self._app_id)
if (self._database_interface is not None and
send_start_notification):
self._database_interface.send_start_notification()
if self._runtime is None:
logger.info("Application is set to run forever - exiting")
else:
self._wait_for_execution_to_complete(
executable_targets, self._app_id, self._runtime,
self._time_scale_factor)
self._has_ran = True
if self._retrieve_provance_data:
# retrieve provence data from central
file_path = os.path.join(self._report_default_directory,
"provance_data")
# check the directory doesnt already exist
if not os.path.exists(file_path):
os.mkdir(file_path)
self._write_provanence_data_in_xml(file_path)
# retrieve provenance data from any cores that provide data
for placement in self._placements:
if isinstance(placement.subvertex,
AbstractProvidesProvanenceData):
file_path = os.path.join(
self._report_default_directory,
"Provanence_data_for_core:{}:{}:{}"
.format(placement.x, placement.y, placement.p))
elif isinstance(self._machine, VirtualMachine):
logger.info(
"*** Using a Virtual Machine so no simulation will occur")
else:
logger.info("*** No simulation requested: Stopping. ***")
def run(self, run_time):
"""
:param run_time:
:return:
"""
# sort out config param to be valid types
width = config.get("Machine", "width")
height = config.get("Machine", "height")
if width == "None":
width = None
else:
width = int(width)
if height == "None":
height = None
else:
height = int(height)
number_of_boards = config.get("Machine", "number_of_boards")
if number_of_boards == "None":
number_of_boards = None
self.setup_interfaces(
hostname=self._hostname,
bmp_details=config.get("Machine", "bmp_names"),
downed_chips=config.get("Machine", "down_chips"),
downed_cores=config.get("Machine", "down_cores"),
board_version=config.getint("Machine", "version"),
number_of_boards=number_of_boards, width=width, height=height,
is_virtual=config.getboolean("Machine", "virtual_board"),
virtual_has_wrap_arounds=config.getboolean(
"Machine", "requires_wrap_arounds"),
auto_detect_bmp=config.getboolean("Machine", "auto_detect_bmp"))
# adds extra stuff needed by the reload script which cannot be given
# directly.
if self._reports_states.transciever_report:
self._reload_script.runtime = run_time
self._reload_script.time_scale_factor = self._time_scale_factor
# create network report if needed
if self._reports_states is not None:
reports.network_specification_partitionable_report(
self._report_default_directory, self._partitionable_graph,
self._hostname)
# calculate number of machine time steps
if run_time is not None:
self._no_machine_time_steps =\
int((run_time * 1000.0) / self._machine_time_step)
ceiled_machine_time_steps = \
math.ceil((run_time * 1000.0) / self._machine_time_step)
if self._no_machine_time_steps != ceiled_machine_time_steps:
raise common_exceptions.ConfigurationException(
"The runtime and machine time step combination result in "
"a factional number of machine runable time steps and "
"therefore spinnaker cannot determine how many to run for")
for vertex in self._partitionable_graph.vertices:
if isinstance(vertex, AbstractDataSpecableVertex):
vertex.set_no_machine_time_steps(
self._no_machine_time_steps)
else:
self._no_machine_time_steps = None
logger.warn("You have set a runtime that will never end, this may"
"cause the neural models to fail to partition "
"correctly")
for vertex in self._partitionable_graph.vertices:
if (isinstance(vertex, AbstractPopulationRecordableVertex) and
vertex.record):
raise common_exceptions.ConfigurationException(
"recording a population when set to infinite runtime "
"is not currently supportable in this tool chain."
"watch this space")
do_timing = config.getboolean("Reports", "outputTimesForSections")
if do_timing:
timer = Timer()
else:
timer = None
self.set_runtime(run_time)
logger.info("*** Running Mapper *** ")
if do_timing:
timer.start_timing()
self.map_model()
if do_timing:
timer.take_sample()
# add database generation if requested
needs_database = self._auto_detect_database(self._partitioned_graph)
user_create_database = config.get("Database", "create_database")
if ((user_create_database == "None" and needs_database) or
user_create_database == "True"):
wait_on_confirmation = config.getboolean(
"Database", "wait_on_confirmation")
self._database_interface = SpynnakerDataBaseInterface(
self._app_data_runtime_folder, wait_on_confirmation,
self._database_socket_addresses)
self._database_interface.add_system_params(
self._time_scale_factor, self._machine_time_step,
self._runtime)
self._database_interface.add_machine_objects(self._machine)
self._database_interface.add_partitionable_vertices(
self._partitionable_graph)
self._database_interface.add_partitioned_vertices(
self._partitioned_graph, self._graph_mapper,
self._partitionable_graph)
self._database_interface.add_placements(self._placements,
self._partitioned_graph)
self._database_interface.add_routing_infos(
self._routing_infos, self._partitioned_graph)
self._database_interface.add_routing_tables(self._router_tables)
self._database_interface.add_tags(self._partitioned_graph,
self._tags)
execute_mapping = config.getboolean(
"Database", "create_routing_info_to_neuron_id_mapping")
if execute_mapping:
self._database_interface.create_neuron_to_key_mapping(
graph_mapper=self._graph_mapper,
partitionable_graph=self._partitionable_graph,
partitioned_graph=self._partitioned_graph,
routing_infos=self._routing_infos)
# if using a reload script, add if that needs to wait for
# confirmation
if self._reports_states.transciever_report:
self._reload_script.wait_on_confirmation = wait_on_confirmation
for socket_address in self._database_socket_addresses:
self._reload_script.add_socket_address(socket_address)
self._database_interface.send_read_notification()
# execute data spec generation
if do_timing:
timer.start_timing()
logger.info("*** Generating Output *** ")
logger.debug("")
executable_targets = self.generate_data_specifications()
if do_timing:
timer.take_sample()
# execute data spec execution
if do_timing:
timer.start_timing()
processor_to_app_data_base_address = \
self.execute_data_specification_execution(
config.getboolean("SpecExecution", "specExecOnHost"),
self._hostname, self._placements, self._graph_mapper,
write_text_specs=config.getboolean(
"Reports", "writeTextSpecs"),
runtime_application_data_folder=self._app_data_runtime_folder,
machine=self._machine)
if self._reports_states is not None:
reports.write_memory_map_report(self._report_default_directory,
processor_to_app_data_base_address)
if do_timing:
timer.take_sample()
if (not isinstance(self._machine, VirtualMachine) and
config.getboolean("Execute", "run_simulation")):
if do_timing:
timer.start_timing()
logger.info("*** Loading tags ***")
self.load_tags(self._tags)
if self._do_load is True:
logger.info("*** Loading data ***")
self._load_application_data(
self._placements, self._graph_mapper,
processor_to_app_data_base_address, self._hostname,
app_data_folder=self._app_data_runtime_folder,
verify=config.getboolean("Mode", "verify_writes"))
self.load_routing_tables(self._router_tables, self._app_id)
logger.info("*** Loading executables ***")
self.load_executable_images(executable_targets, self._app_id)
logger.info("*** Loading buffers ***")
self.set_up_send_buffering(self._partitioned_graph,
self._placements, self._tags)
# end of entire loading setup
if do_timing:
timer.take_sample()
if self._do_run is True:
logger.info("*** Running simulation... *** ")
if do_timing:
timer.start_timing()
# every thing is in sync0. load the initial buffers
self._send_buffer_manager.load_initial_buffers()
if do_timing:
timer.take_sample()
wait_on_confirmation = config.getboolean(
"Database", "wait_on_confirmation")
send_start_notification = config.getboolean(
"Database", "send_start_notification")
self.wait_for_cores_to_be_ready(executable_targets,
self._app_id)
# wait till external app is ready for us to start if required
if (self._database_interface is not None and
wait_on_confirmation):
self._database_interface.wait_for_confirmation()
self.start_all_cores(executable_targets, self._app_id)
if (self._database_interface is not None and
send_start_notification):
self._database_interface.send_start_notification()
if self._runtime is None:
logger.info("Application is set to run forever - exiting")
else:
self.wait_for_execution_to_complete(
executable_targets, self._app_id, self._runtime,
self._time_scale_factor)
self._has_ran = True
if self._retrieve_provance_data:
progress = ProgressBar(self._placements.n_placements + 1,
"getting provenance data")
# retrieve provence data from central
file_path = os.path.join(self._report_default_directory,
"provance_data")
# check the directory doesnt already exist
if not os.path.exists(file_path):
os.mkdir(file_path)
# write provanence data
self.write_provenance_data_in_xml(file_path, self._txrx)
progress.update()
# retrieve provenance data from any cores that provide data
for placement in self._placements.placements:
if isinstance(placement.subvertex,
AbstractProvidesProvenanceData):
core_file_path = os.path.join(
file_path,
"Provanence_data_for_{}_{}_{}_{}.xml".format(
placement.subvertex.label,
placement.x, placement.y, placement.p))
placement.subvertex.write_provenance_data_in_xml(
core_file_path, self.transceiver, placement)
progress.update()
progress.end()
elif isinstance(self._machine, VirtualMachine):
logger.info(
"*** Using a Virtual Machine so no simulation will occur")
else:
logger.info("*** No simulation requested: Stopping. ***")
def run(self, run_time):
"""
:param run_time:
:return:
"""
# sort out config param to be valid types
width = config.get("Machine", "width")
height = config.get("Machine", "height")
if width == "None":
width = None
else:
width = int(width)
if height == "None":
height = None
else:
height = int(height)
number_of_boards = config.get("Machine", "number_of_boards")
if number_of_boards == "None":
number_of_boards = None
self.setup_interfaces(
hostname=self._hostname,
bmp_details=config.get("Machine", "bmp_names"),
downed_chips=config.get("Machine", "down_chips"),
downed_cores=config.get("Machine", "down_cores"),
board_version=config.getint("Machine", "version"),
number_of_boards=number_of_boards,
width=width,
height=height,
is_virtual=config.getboolean("Machine", "virtual_board"),
virtual_has_wrap_arounds=config.getboolean(
"Machine", "requires_wrap_arounds"),
auto_detect_bmp=config.getboolean("Machine", "auto_detect_bmp"))
# adds extra stuff needed by the reload script which cannot be given
# directly.
if self._reports_states.transciever_report:
self._reload_script.runtime = run_time
self._reload_script.time_scale_factor = self._time_scale_factor
# create network report if needed
if self._reports_states is not None:
reports.network_specification_partitionable_report(
self._report_default_directory, self._partitionable_graph,
self._hostname)
# calculate number of machine time steps
if run_time is not None:
self._no_machine_time_steps =\
int((run_time * 1000.0) / self._machine_time_step)
ceiled_machine_time_steps = \
math.ceil((run_time * 1000.0) / self._machine_time_step)
if self._no_machine_time_steps != ceiled_machine_time_steps:
raise common_exceptions.ConfigurationException(
"The runtime and machine time step combination result in "
"a factional number of machine runable time steps and "
"therefore spinnaker cannot determine how many to run for")
for vertex in self._partitionable_graph.vertices:
if isinstance(vertex, AbstractDataSpecableVertex):
vertex.set_no_machine_time_steps(
self._no_machine_time_steps)
else:
self._no_machine_time_steps = None
logger.warn("You have set a runtime that will never end, this may"
"cause the neural models to fail to partition "
"correctly")
for vertex in self._partitionable_graph.vertices:
if (isinstance(vertex, AbstractPopulationRecordableVertex)
and vertex.record):
raise common_exceptions.ConfigurationException(
"recording a population when set to infinite runtime "
"is not currently supportable in this tool chain."
"watch this space")
do_timing = config.getboolean("Reports", "outputTimesForSections")
if do_timing:
timer = Timer()
else:
timer = None
self.set_runtime(run_time)
logger.info("*** Running Mapper *** ")
if do_timing:
timer.start_timing()
self.map_model()
if do_timing:
timer.take_sample()
# add database generation if requested
needs_database = self._auto_detect_database(self._partitioned_graph)
user_create_database = config.get("Database", "create_database")
if ((user_create_database == "None" and needs_database)
or user_create_database == "True"):
wait_on_confirmation = config.getboolean("Database",
"wait_on_confirmation")
self._database_interface = SpynnakerDataBaseInterface(
self._app_data_runtime_folder, wait_on_confirmation,
self._database_socket_addresses)
self._database_interface.add_system_params(self._time_scale_factor,
self._machine_time_step,
self._runtime)
self._database_interface.add_machine_objects(self._machine)
self._database_interface.add_partitionable_vertices(
self._partitionable_graph)
self._database_interface.add_partitioned_vertices(
self._partitioned_graph, self._graph_mapper,
self._partitionable_graph)
self._database_interface.add_placements(self._placements,
self._partitioned_graph)
self._database_interface.add_routing_infos(self._routing_infos,
self._partitioned_graph)
self._database_interface.add_routing_tables(self._router_tables)
self._database_interface.add_tags(self._partitioned_graph,
self._tags)
execute_mapping = config.getboolean(
"Database", "create_routing_info_to_neuron_id_mapping")
if execute_mapping:
self._database_interface.create_neuron_to_key_mapping(
graph_mapper=self._graph_mapper,
partitionable_graph=self._partitionable_graph,
partitioned_graph=self._partitioned_graph,
routing_infos=self._routing_infos)
# if using a reload script, add if that needs to wait for
# confirmation
if self._reports_states.transciever_report:
self._reload_script.wait_on_confirmation = wait_on_confirmation
for socket_address in self._database_socket_addresses:
self._reload_script.add_socket_address(socket_address)
self._database_interface.send_read_notification()
# execute data spec generation
if do_timing:
timer.start_timing()
logger.info("*** Generating Output *** ")
logger.debug("")
executable_targets = self.generate_data_specifications()
if do_timing:
timer.take_sample()
# execute data spec execution
if do_timing:
timer.start_timing()
processor_to_app_data_base_address = \
self.execute_data_specification_execution(
config.getboolean("SpecExecution", "specExecOnHost"),
self._hostname, self._placements, self._graph_mapper,
write_text_specs=config.getboolean(
"Reports", "writeTextSpecs"),
runtime_application_data_folder=self._app_data_runtime_folder,
machine=self._machine)
if self._reports_states is not None:
reports.write_memory_map_report(
self._report_default_directory,
processor_to_app_data_base_address)
if do_timing:
timer.take_sample()
if (not isinstance(self._machine, VirtualMachine)
and config.getboolean("Execute", "run_simulation")):
if do_timing:
timer.start_timing()
logger.info("*** Loading tags ***")
self.load_tags(self._tags)
if self._do_load is True:
logger.info("*** Loading data ***")
self._load_application_data(
self._placements,
self._graph_mapper,
processor_to_app_data_base_address,
self._hostname,
app_data_folder=self._app_data_runtime_folder,
verify=config.getboolean("Mode", "verify_writes"))
self.load_routing_tables(self._router_tables, self._app_id)
logger.info("*** Loading executables ***")
self.load_executable_images(executable_targets, self._app_id)
logger.info("*** Loading buffers ***")
self.set_up_send_buffering(self._partitioned_graph,
self._placements, self._tags)
# end of entire loading setup
if do_timing:
timer.take_sample()
if self._do_run is True:
logger.info("*** Running simulation... *** ")
if do_timing:
timer.start_timing()
# every thing is in sync0. load the initial buffers
self._send_buffer_manager.load_initial_buffers()
if do_timing:
timer.take_sample()
wait_on_confirmation = config.getboolean(
"Database", "wait_on_confirmation")
send_start_notification = config.getboolean(
"Database", "send_start_notification")
self.wait_for_cores_to_be_ready(executable_targets,
self._app_id)
# wait till external app is ready for us to start if required
if (self._database_interface is not None
and wait_on_confirmation):
self._database_interface.wait_for_confirmation()
self.start_all_cores(executable_targets, self._app_id)
if (self._database_interface is not None
and send_start_notification):
self._database_interface.send_start_notification()
if self._runtime is None:
logger.info("Application is set to run forever - exiting")
else:
self.wait_for_execution_to_complete(
executable_targets, self._app_id, self._runtime,
self._time_scale_factor)
self._has_ran = True
if self._retrieve_provance_data:
progress = ProgressBar(self._placements.n_placements + 1,
"getting provenance data")
# retrieve provence data from central
file_path = os.path.join(self._report_default_directory,
"provance_data")
# check the directory doesnt already exist
if not os.path.exists(file_path):
os.mkdir(file_path)
# write provanence data
self.write_provenance_data_in_xml(file_path, self._txrx)
progress.update()
# retrieve provenance data from any cores that provide data
for placement in self._placements.placements:
if isinstance(placement.subvertex,
AbstractProvidesProvenanceData):
core_file_path = os.path.join(
file_path,
"Provanence_data_for_{}_{}_{}_{}.xml".format(
placement.subvertex.label, placement.x,
placement.y, placement.p))
placement.subvertex.write_provenance_data_in_xml(
core_file_path, self.transceiver, placement)
progress.update()
progress.end()
elif isinstance(self._machine, VirtualMachine):
logger.info(
"*** Using a Virtual Machine so no simulation will occur")
else:
logger.info("*** No simulation requested: Stopping. ***")