def __init__(self,
presynaptic_population,
postsynaptic_population,
machine_time_step,
connector=None,
synapse_list=None,
synapse_dynamics=None,
label=None):
MultiCastPartitionableEdge.__init__(
self,
presynaptic_population._get_vertex,
postsynaptic_population._get_vertex,
label=label)
self._connector = connector
self._synapse_dynamics = synapse_dynamics
self._synapse_list = synapse_list
self._synapse_row_io = FixedSynapseRowIO()
self._stored_synaptic_data_from_machine = None
# If there are synapse dynamics for this connector, create a plastic
# synapse list
if synapse_dynamics is not None:
self._synapse_row_io = synapse_dynamics.get_synapse_row_io()
def __init__(self, presynaptic_population, postsynaptic_population,
machine_time_step, connector=None, synapse_list=None,
synapse_dynamics=None, label=None):
MultiCastPartitionableEdge.__init__(
self, presynaptic_population._get_vertex,
postsynaptic_population._get_vertex, label=label)
self._connector = connector
self._synapse_dynamics = synapse_dynamics
self._synapse_list = synapse_list
self._synapse_row_io = FixedSynapseRowIO()
self._stored_synaptic_data_from_machine = None
# If there are synapse dynamics for this connector, create a plastic
# synapse list
if synapse_dynamics is not None:
self._synapse_row_io = synapse_dynamics.get_synapse_row_io()
class ProjectionPartitionableEdge(MultiCastPartitionableEdge):
""" The partitionable edge for a projection (high level edge)
"""
def __init__(self, presynaptic_population, postsynaptic_population,
machine_time_step, connector=None, synapse_list=None,
synapse_dynamics=None, label=None):
MultiCastPartitionableEdge.__init__(
self, presynaptic_population._get_vertex,
postsynaptic_population._get_vertex, label=label)
self._connector = connector
self._synapse_dynamics = synapse_dynamics
self._synapse_list = synapse_list
self._synapse_row_io = FixedSynapseRowIO()
self._stored_synaptic_data_from_machine = None
# If there are synapse dynamics for this connector, create a plastic
# synapse list
if synapse_dynamics is not None:
self._synapse_row_io = synapse_dynamics.get_synapse_row_io()
def create_subedge(self, presubvertex, postsubvertex, constraints=None,
label=None):
""" Create a subedge from this edge
"""
if constraints is None:
constraints = list()
constraints.extend(self.constraints)
return ProjectionPartitionedEdge(presubvertex, postsubvertex,
constraints)
def get_max_n_words(self, vertex_slice=None):
""" Get the maximum number of words for a subvertex at the end of the\
connection
:param vertex_slice: the vertex slice for this vertex which contains \
the low and high atoms for this slice
"""
if vertex_slice is None:
return max([self._synapse_row_io.get_n_words(
synapse_row)
for synapse_row in self._synapse_list.get_rows()])
else:
return max([self._synapse_row_io.get_n_words(
synapse_row, vertex_slice)
for synapse_row in self._synapse_list.get_rows()])
def get_n_rows(self):
""" Get the number of synaptic rows coming in to a subvertex at the\
end of the connection
"""
return self._synapse_list.get_n_rows()
def get_synapse_row_io(self):
""" Gets the row reader and writer
"""
return self._synapse_row_io
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
@property
def synapse_dynamics(self):
return self._synapse_dynamics
@property
def synapse_list(self):
return self._synapse_list
def is_multi_cast_partitionable_edge(self):
return True
class ProjectionPartitionableEdge(MultiCastPartitionableEdge):
"""
the partitionable edge for a projection (high level edge)
"""
def __init__(self,
presynaptic_population,
postsynaptic_population,
machine_time_step,
connector=None,
synapse_list=None,
synapse_dynamics=None,
label=None):
MultiCastPartitionableEdge.__init__(
self,
presynaptic_population._get_vertex,
postsynaptic_population._get_vertex,
label=label)
self._connector = connector
self._synapse_dynamics = synapse_dynamics
self._synapse_list = synapse_list
self._synapse_row_io = FixedSynapseRowIO()
self._stored_synaptic_data_from_machine = None
# If there are synapse dynamics for this connector, create a plastic
# synapse list
if synapse_dynamics is not None:
self._synapse_row_io = synapse_dynamics.get_synapse_row_io()
def create_subedge(self,
presubvertex,
postsubvertex,
constraints=None,
label=None):
"""
Creates a subedge from this edge
"""
if constraints is None:
constraints = list()
constraints.extend(self.constraints)
return ProjectionPartitionedEdge(presubvertex, postsubvertex,
constraints)
def get_max_n_words(self, vertex_slice=None):
"""
Gets the maximum number of words for a subvertex at the end of the
connection
:param vertex_slice: the vertex slice for this vertex which contains \
the lo and hi atoms for this slice
"""
if vertex_slice is None:
return max([
self._synapse_row_io.get_n_words(synapse_row)
for synapse_row in self._synapse_list.get_rows()
])
else:
return max([
self._synapse_row_io.get_n_words(synapse_row, vertex_slice)
for synapse_row in self._synapse_list.get_rows()
])
def get_n_rows(self):
"""
Gets the number of synaptic rows coming in to a subvertex at the end of
the connection
"""
return self._synapse_list.get_n_rows()
def get_synapse_row_io(self):
"""
Gets the row reader and writer
"""
return self._synapse_row_io
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
@property
def synapse_dynamics(self):
"""
:return: returns the synapse_dynamics for the edge
"""
return self._synapse_dynamics
@property
def synapse_list(self):
"""
:return: returns the synaptic list for the edge
"""
return self._synapse_list
def is_multi_cast_partitionable_edge(self):
return True
