def interact(self):
dump_stacktraces()
from veles.interaction import Shell
Shell.fix_netcat_colors()
shell = Shell(self.workflow, name="Manhole")
shell.thread_pool.pause()
shell.initialize()
try:
shell.interact({
'dump_stacktraces': dump_stacktraces,
'sys': sys,
'os': os,
'socket': socket,
'traceback': traceback,
'pause': shell.thread_pool.pause,
'resume': shell.thread_pool.resume,
})
except (EOFError, BrokenPipeError):
cry("Client has been dropped.")
finally:
shell.workflow.del_ref(shell)
shell.thread_pool.resume()
"""
def interact(self):
dump_stacktraces()
from veles.interaction import Shell
Shell.fix_netcat_colors()
shell = Shell(self.workflow, name="Manhole")
shell.thread_pool.pause()
shell.initialize()
try:
shell.interact({
'dump_stacktraces': dump_stacktraces,
'sys': sys,
'os': os,
'socket': socket,
'traceback': traceback,
'pause': shell.thread_pool.pause,
'resume': shell.thread_pool.resume,
})
except (EOFError, BrokenPipeError):
cry("Client has been dropped.")
finally:
shell.workflow.del_ref(shell)
shell.thread_pool.resume()
"""
def __init__(self, workflow, **kwargs):
kwargs["name"] = kwargs.get("name", "Kohonen")
super(KohonenWorkflow, self).__init__(workflow, **kwargs)
self.downloader = Downloader(
self, url=root.kohonen.downloader.url,
directory=root.kohonen.downloader.directory,
files=root.kohonen.downloader.files)
self.downloader.link_from(self.start_point)
self.repeater.link_from(self.downloader)
self.loader = KohonenLoader(
self, name="Kohonen fullbatch loader",
minibatch_size=root.kohonen.loader.minibatch_size,
force_numpy=root.kohonen.loader.force_numpy)
self.loader.link_from(self.repeater)
# Kohonen training layer
self.trainer = kohonen.KohonenTrainer(
self, shape=root.kohonen.forward.shape,
weights_filling=root.kohonen.forward.weights_filling,
weights_stddev=root.kohonen.forward.weights_stddev,
gradient_decay=root.kohonen.train.gradient_decay,
radius_decay=root.kohonen.train.radius_decay)
self.trainer.link_from(self.loader)
self.trainer.link_attrs(self.loader, ("input", "minibatch_data"))
# Loop decision
self.decision = kohonen.KohonenDecision(
self, max_epochs=root.kohonen.decision.epochs)
self.decision.link_from(self.trainer)
self.decision.link_attrs(self.loader,
"minibatch_class",
"last_minibatch",
"class_lengths",
"epoch_ended",
"epoch_number")
self.decision.link_attrs(self.trainer, "weights", "winners")
self.ipython = Shell(self)
self.ipython.link_from(self.decision)
self.ipython.gate_skip = ~self.decision.epoch_ended
self.repeater.link_from(self.ipython)
self.ipython.gate_block = self.decision.complete
self.end_point.link_from(self.decision)
self.end_point.gate_block = ~self.decision.complete
self.loader.gate_block = self.decision.complete
# Error plotter
self.plotters = [nn_plotting_units.KohonenHits(self),
nn_plotting_units.KohonenInputMaps(self),
nn_plotting_units.KohonenNeighborMap(self)]
self.plotters[0].link_attrs(self.trainer, "shape") \
.link_from(self.ipython)
self.plotters[0].input = self.decision.winners_mem
self.plotters[0].gate_block = ~self.decision.epoch_ended
self.plotters[1].link_attrs(self.trainer, "shape") \
.link_from(self.ipython)
self.plotters[1].input = self.decision.weights_mem
self.plotters[1].gate_block = ~self.decision.epoch_ended
self.plotters[2].link_attrs(self.trainer, "shape") \
.link_from(self.ipython)
self.plotters[2].input = self.decision.weights_mem
self.plotters[2].gate_block = ~self.decision.epoch_ended
def __init__(self, workflow, **kwargs):
kwargs["name"] = kwargs.get("name", "Kohonen")
super(KohonenWorkflow, self).__init__(workflow, **kwargs)
self.downloader = Downloader(
self,
url=root.kohonen.downloader.url,
directory=root.kohonen.downloader.directory,
files=root.kohonen.downloader.files)
self.downloader.link_from(self.start_point)
self.repeater.link_from(self.downloader)
self.loader = KohonenLoader(
self,
name="Kohonen fullbatch loader",
minibatch_size=root.kohonen.loader.minibatch_size,
force_numpy=root.kohonen.loader.force_numpy)
self.loader.link_from(self.repeater)
# Kohonen training layer
self.trainer = kohonen.KohonenTrainer(
self,
shape=root.kohonen.forward.shape,
weights_filling=root.kohonen.forward.weights_filling,
weights_stddev=root.kohonen.forward.weights_stddev,
gradient_decay=root.kohonen.train.gradient_decay,
radius_decay=root.kohonen.train.radius_decay)
self.trainer.link_from(self.loader)
self.trainer.link_attrs(self.loader, ("input", "minibatch_data"))
# Loop decision
self.decision = kohonen.KohonenDecision(
self, max_epochs=root.kohonen.decision.epochs)
self.decision.link_from(self.trainer)
self.decision.link_attrs(self.loader, "minibatch_class",
"last_minibatch", "class_lengths",
"epoch_ended", "epoch_number")
self.decision.link_attrs(self.trainer, "weights", "winners")
self.ipython = Shell(self)
self.ipython.link_from(self.decision)
self.ipython.gate_skip = ~self.decision.epoch_ended
self.repeater.link_from(self.ipython)
self.ipython.gate_block = self.decision.complete
self.end_point.link_from(self.decision)
self.end_point.gate_block = ~self.decision.complete
self.loader.gate_block = self.decision.complete
# Error plotter
self.plotters = [
nn_plotting_units.KohonenHits(self),
nn_plotting_units.KohonenInputMaps(self),
nn_plotting_units.KohonenNeighborMap(self)
]
self.plotters[0].link_attrs(self.trainer, "shape") \
.link_from(self.ipython)
self.plotters[0].input = self.decision.winners_mem
self.plotters[0].gate_block = ~self.decision.epoch_ended
self.plotters[1].link_attrs(self.trainer, "shape") \
.link_from(self.ipython)
self.plotters[1].input = self.decision.weights_mem
self.plotters[1].gate_block = ~self.decision.epoch_ended
self.plotters[2].link_attrs(self.trainer, "shape") \
.link_from(self.ipython)
self.plotters[2].input = self.decision.weights_mem
self.plotters[2].gate_block = ~self.decision.epoch_ended
