def create_test_pmml_model(self, model_name):
if self.odps.exist_offline_model(model_name):
return
old_node_id = RunnerContext.instance()._dag._node_seq_id
old_dry_run = options.runner.dry_run
options.runner.dry_run = False
self.create_ionosphere(IONOSPHERE_TABLE)
from odps.ml import classifiers
df = DataFrame(self.odps.get_table(IONOSPHERE_TABLE)).roles(label='class')
lr = classifiers.LogisticRegression(epsilon=0.001).set_max_iter(50)
lr.train(df).persist(model_name)
options.runner.dry_run = old_dry_run
RunnerContext.instance()._dag._node_seq_id = old_node_id
def actual_exec(self):
in_tables = []
for in_name, in_port in six.iteritems(self._node.inputs):
if in_port.type != PortType.DATA:
continue
ep = RunnerContext.instance()._obj_container.get(in_port.obj_uuid)
if ep:
in_tables.append((in_name, ep.table))
msg = 'Message: %s Input tables: %s' % (self._node.message, ', '.join('%s<-%s' % ti for ti in in_tables))
if self._node.action is not None:
self._node.action(self._node)
else:
print(msg)
def actual_exec(self):
in_tables = []
for in_name, in_port in six.iteritems(self._node.inputs):
if in_port.type != PortType.DATA:
continue
ep = RunnerContext.instance()._obj_container.get(in_port.obj_uuid)
if ep:
in_tables.append((in_name, ep.table))
msg = 'Message: %s Input tables: %s' % (self._node.message, ', '.join(
'%s<-%s' % ti for ti in in_tables))
if self._node.action is not None:
self._node.action(self._node)
else:
print(msg)
def setUp(self):
super(Test, self).setUp()
self.ml_context = RunnerContext.instance()
self.create_ionosphere(IONOSPHERE_TABLE)
self.df = DataFrame(self.odps.get_table(IONOSPHERE_TABLE))
def setUp(self):
super(TestCore, self).setUp()
self.ml_context = RunnerContext.instance()
def setUp(self):
super(TestCore, self).setUp()
self.ml_context = RunnerContext.instance()
def after_exec(self):
from odps.runner import RunnerContext
context = RunnerContext.instance()
self._node.after_exec(self._odps, True)
context._node_outputs[self._node_hash] = dict((pn, self.get_output_object(p))
for pn, p in six.iteritems(self._node.outputs))