def __init__(self, taskControl, model):
""" Constructor
taskControl: dictionary conforming to opfTaskControlSchema.json that defines
the actions to be performed on the given model.
model: instance of Model that this OPFTaskDriver
instance will drive.
"""
#validateOpfJsonValue(taskControl, "opfTaskControlSchema.json")
self.__reprstr = ("%s(" + \
"taskControl=%r, " + \
"model=%r)") % \
(self.__class__.__name__,
taskControl,
model)
# Init logging
#
self.logger = logging.getLogger(".".join(
['com.numenta', self.__class__.__module__, self.__class__.__name__]))
self.logger.info(("Instantiating %s; %r.") % \
(self.__class__.__name__,
self.__reprstr))
# -----------------------------------------------------------------------
# Save args of interest
#
self.__taskControl = taskControl
self.__model = model
# -----------------------------------------------------------------------
# Create Metrics Manager.
#
self.__metricsMgr = None
metrics = taskControl.get('metrics', None)
self.__metricsMgr = MetricsManager(metricSpecs=metrics,
inferenceType=model.getInferenceType(),
fieldInfo=model.getFieldInfo())
# -----------------------------------------------------------------------
# Figure out which metrics should be logged
#
# The logged metrics won't within the current task
self.__loggedMetricLabels = set([])
loggedMetricPatterns = taskControl.get('loggedMetrics', None)
# -----------------------------------------------------------------------
# Create our phase manager
#
self.__phaseManager = _PhaseManager(
model=model,
phaseSpecs=taskControl.get('iterationCycle', []))
# -----------------------------------------------------------------------
# Initialize the callbacks container
#
self.__userCallbacks = defaultdict(list, taskControl.get('callbacks', {}))
return
def __init__(self, taskControl, model):
""" Constructor
taskControl: dictionary conforming to opfTaskControlSchema.json that defines
the actions to be performed on the given model.
model: instance of Model that this OPFTaskDriver
instance will drive.
"""
#validateOpfJsonValue(taskControl, "opfTaskControlSchema.json")
self.__reprstr = ("%s(" + \
"taskControl=%r, " + \
"model=%r)") % \
(self.__class__.__name__,
taskControl,
model)
# Init logging
#
self.logger = logging.getLogger(".".join(
['com.numenta', self.__class__.__module__, self.__class__.__name__]))
self.logger.debug(("Instantiating %s; %r.") % \
(self.__class__.__name__,
self.__reprstr))
# -----------------------------------------------------------------------
# Save args of interest
#
self.__taskControl = taskControl
self.__model = model
# -----------------------------------------------------------------------
# Create Metrics Manager.
#
self.__metricsMgr = None
metrics = taskControl.get('metrics', None)
self.__metricsMgr = MetricsManager(metricSpecs=metrics,
inferenceType=model.getInferenceType(),
fieldInfo=model.getFieldInfo())
# -----------------------------------------------------------------------
# Figure out which metrics should be logged
#
# The logged metrics won't within the current task
self.__loggedMetricLabels = set([])
loggedMetricPatterns = taskControl.get('loggedMetrics', None)
# -----------------------------------------------------------------------
# Create our phase manager
#
self.__phaseManager = _PhaseManager(
model=model,
phaseSpecs=taskControl.get('iterationCycle', []))
# -----------------------------------------------------------------------
# Initialize the callbacks container
#
self.__userCallbacks = defaultdict(list, taskControl.get('callbacks', {}))
return
class OPFTaskDriver(object):
""" Task Phase Driver implementation
Conceptually, the client injects input records, one at a time, into
an OPFTaskDriver instance for execution according to the
current IterationPhase as maintained by the OPFTaskDriver instance.
"""
def __init__(self, taskControl, model):
""" Constructor
taskControl: dictionary conforming to opfTaskControlSchema.json that defines
the actions to be performed on the given model.
model: instance of Model that this OPFTaskDriver
instance will drive.
"""
#validateOpfJsonValue(taskControl, "opfTaskControlSchema.json")
self.__reprstr = ("%s(" + \
"taskControl=%r, " + \
"model=%r)") % \
(self.__class__.__name__,
taskControl,
model)
# Init logging
#
self.logger = logging.getLogger(".".join(
['com.numenta', self.__class__.__module__, self.__class__.__name__]))
self.logger.info(("Instantiating %s; %r.") % \
(self.__class__.__name__,
self.__reprstr))
# -----------------------------------------------------------------------
# Save args of interest
#
self.__taskControl = taskControl
self.__model = model
# -----------------------------------------------------------------------
# Create Metrics Manager.
#
self.__metricsMgr = None
metrics = taskControl.get('metrics', None)
self.__metricsMgr = MetricsManager(metricSpecs=metrics,
inferenceType=model.getInferenceType(),
fieldInfo=model.getFieldInfo())
# -----------------------------------------------------------------------
# Figure out which metrics should be logged
#
# The logged metrics won't within the current task
self.__loggedMetricLabels = set([])
loggedMetricPatterns = taskControl.get('loggedMetrics', None)
# -----------------------------------------------------------------------
# Create our phase manager
#
self.__phaseManager = _PhaseManager(
model=model,
phaseSpecs=taskControl.get('iterationCycle', []))
# -----------------------------------------------------------------------
# Initialize the callbacks container
#
self.__userCallbacks = defaultdict(list, taskControl.get('callbacks', {}))
return
def __repr__(self):
return self.__reprstr
def replaceIterationCycle(self, phaseSpecs):
""" Replaces the Iteration Cycle phases
phaseSpecs: Iteration cycle description consisting of a sequence of
IterationPhaseSpecXXXXX elements that are performed in the
given order
"""
# -----------------------------------------------------------------------
# Replace our phase manager
#
self.__phaseManager = _PhaseManager(
model=self.__model,
phaseSpecs=phaseSpecs)
return
def setup(self):
""" Performs initial setup activities, including 'setup' callbacks. This
method MUST be called once before the first call to handleInputRecord()
Returns: nothing
"""
# Execute task-setup callbacks
for cb in self.__userCallbacks['setup']:
cb(self.__model)
return
def finalize(self):
""" Perform final activities, including 'finish' callbacks. This
method MUST be called once after the last call to handleInputRecord()
Returns: nothing
"""
# Execute task-finish callbacks
for cb in self.__userCallbacks['finish']:
cb(self.__model)
return
def handleInputRecord(self, inputRecord):
""" Processes the given record according to the current iteration cycle phase
inputRecord: record object formatted according to
nupic.data.FileSource.getNext() result format.
Returns: An opfutils.ModelResult object
"""
assert inputRecord, "Invalid inputRecord: %r" % inputRecord
results = self.__phaseManager.handleInputRecord(inputRecord)
metrics = self.__metricsMgr.update(results)
# Execute task-postIter callbacks
for cb in self.__userCallbacks['postIter']:
cb(self.__model)
results.metrics = metrics
# Return the input and predictions for this record
return results
def getMetrics(self):
""" Gets the current metric values
Returns: A dictionary of metric values. The key for
each entry is the label for the metric spec, as generated by
MetricSpec.getLabel(). The value for each entry is a
dictonary containing the value of the metric as returned by the
metric module's getMetric() function (see metrics.py)
"""
return self.__metricsMgr.getMetrics()
def getMetricLabels(self):
""" Return the list of labels for the metrics that are being calculated"""
return self.__metricsMgr.getMetricLabels()
class OPFTaskDriver(object):
""" Task Phase Driver implementation
Conceptually, the client injects input records, one at a time, into
an OPFTaskDriver instance for execution according to the
current IterationPhase as maintained by the OPFTaskDriver instance.
"""
def __init__(self, taskControl, model):
""" Constructor
taskControl: dictionary conforming to opfTaskControlSchema.json that defines
the actions to be performed on the given model.
model: instance of Model that this OPFTaskDriver
instance will drive.
"""
#validateOpfJsonValue(taskControl, "opfTaskControlSchema.json")
self.__reprstr = ("%s(" + \
"taskControl=%r, " + \
"model=%r)") % \
(self.__class__.__name__,
taskControl,
model)
# Init logging
#
self.logger = logging.getLogger(".".join(
['com.numenta', self.__class__.__module__, self.__class__.__name__]))
self.logger.debug(("Instantiating %s; %r.") % \
(self.__class__.__name__,
self.__reprstr))
# -----------------------------------------------------------------------
# Save args of interest
#
self.__taskControl = taskControl
self.__model = model
# -----------------------------------------------------------------------
# Create Metrics Manager.
#
self.__metricsMgr = None
metrics = taskControl.get('metrics', None)
self.__metricsMgr = MetricsManager(metricSpecs=metrics,
inferenceType=model.getInferenceType(),
fieldInfo=model.getFieldInfo())
# -----------------------------------------------------------------------
# Figure out which metrics should be logged
#
# The logged metrics won't within the current task
self.__loggedMetricLabels = set([])
loggedMetricPatterns = taskControl.get('loggedMetrics', None)
# -----------------------------------------------------------------------
# Create our phase manager
#
self.__phaseManager = _PhaseManager(
model=model,
phaseSpecs=taskControl.get('iterationCycle', []))
# -----------------------------------------------------------------------
# Initialize the callbacks container
#
self.__userCallbacks = defaultdict(list, taskControl.get('callbacks', {}))
return
def __repr__(self):
return self.__reprstr
def replaceIterationCycle(self, phaseSpecs):
""" Replaces the Iteration Cycle phases
phaseSpecs: Iteration cycle description consisting of a sequence of
IterationPhaseSpecXXXXX elements that are performed in the
given order
"""
# -----------------------------------------------------------------------
# Replace our phase manager
#
self.__phaseManager = _PhaseManager(
model=self.__model,
phaseSpecs=phaseSpecs)
return
def setup(self):
""" Performs initial setup activities, including 'setup' callbacks. This
method MUST be called once before the first call to handleInputRecord()
Returns: nothing
"""
# Execute task-setup callbacks
for cb in self.__userCallbacks['setup']:
cb(self.__model)
return
def finalize(self):
""" Perform final activities, including 'finish' callbacks. This
method MUST be called once after the last call to handleInputRecord()
Returns: nothing
"""
# Execute task-finish callbacks
for cb in self.__userCallbacks['finish']:
cb(self.__model)
return
def handleInputRecord(self, inputRecord):
""" Processes the given record according to the current iteration cycle phase
inputRecord: record object formatted according to
nupic.data.FileSource.getNext() result format.
Returns: An opfutils.ModelResult object
"""
assert inputRecord, "Invalid inputRecord: %r" % inputRecord
results = self.__phaseManager.handleInputRecord(inputRecord)
metrics = self.__metricsMgr.update(results)
# Execute task-postIter callbacks
for cb in self.__userCallbacks['postIter']:
cb(self.__model)
results.metrics = metrics
# Return the input and predictions for this record
return results
def getMetrics(self):
""" Gets the current metric values
Returns: A dictionary of metric values. The key for
each entry is the label for the metric spec, as generated by
MetricSpec.getLabel(). The value for each entry is a
dictonary containing the value of the metric as returned by the
metric module's getMetric() function (see metrics.py)
"""
return self.__metricsMgr.getMetrics()
def getMetricLabels(self):
""" Return the list of labels for the metrics that are being calculated"""
return self.__metricsMgr.getMetricLabels()