def test_can_format_data_config(self):
experimenter = Experimenter(
data_config={'train': {'tag1': '2344'}, 'test': {'tag1': '2344'}, 'select_sql': 'SELECT * FROM {tag2}'})
self.assertFalse(experimenter.can_format_data_config())
experimenter = Experimenter(
data_config={'train': {'tag1': '2344'}, 'test': {'tag1': '2344'}, 'select_sql': 'SELECT * FROM {tag1}'})
self.assertTrue(experimenter.can_format_data_config())
def test_build_data_config(self):
experimenter = Experimenter(
data_config={
'train': {
'table': 'train_data'
},
'test': {
'table': 'test_data'
},
'select_sql': 'SELECT * FROM {table}'
})
experimenter.build_data_config()
self.assertEqual(experimenter.data_config['train'],
'SELECT * FROM train_data')
self.assertEqual(experimenter.data_config['test'],
'SELECT * FROM test_data')
def test_if_has_valid_learner_config(self):
experimenter = Experimenter(learner_config={'vw': ['param']})
self.assertFalse(experimenter.has_valid_learner_config())
experimenter.learner_config = {'vw': {'param': 'value'}}
self.assertFalse(experimenter.has_valid_learner_config())
experimenter.learner_config = {'vw': {'param': ['value'], 'param2': 'value2'}}
self.assertFalse(experimenter.has_valid_learner_config())
experimenter.learner_config = {'vw': {'param': ['value'], 'param2': ['value2', 'value22']}}
self.assertTrue(experimenter.has_valid_learner_config())
def test_has_valid_model_config(self):
experimenter = Experimenter()
experimenter.model_config = [{
'ignore': [],
'features': {
'feat1': lambda x: x
},
'inherit': []
}]
self.assertFalse(experimenter.has_valid_model_config())
experimenter.model_config = {
'base_model': {
'ignore': [],
'features': {
'feat1': lambda x: x
},
'inherit': []
}
}
self.assertTrue(experimenter.has_valid_model_config())
experimenter.model_config = {
'derived_model': {
'ignore': [],
'features': {
'feat1': lambda x: x
},
'inherit': ['base_model']
}
}
self.assertFalse(experimenter.has_valid_model_config())
experimenter.model_config = {
'base_model': {
'ignore': [],
'features': {
'feat1': lambda x: x
},
'inherit': []
},
'derived_model': {
'ignore': [],
'features': {
'feat1': lambda x: x
},
'inherit': ['base_model']
}
}
self.assertTrue(experimenter.has_valid_model_config())
def test_has_valid_model_config(self):
experimenter = Experimenter()
experimenter.model_config = [{'ignore': [], 'features': {'feat1': lambda x: x}, 'inherit': []}]
self.assertFalse(experimenter.has_valid_model_config())
experimenter.model_config = {'base_model': {'ignore': [], 'features': {'feat1': lambda x: x}, 'inherit': []}}
self.assertTrue(experimenter.has_valid_model_config())
experimenter.model_config = {
'derived_model': {'ignore': [], 'features': {'feat1': lambda x: x}, 'inherit': ['base_model']}}
self.assertFalse(experimenter.has_valid_model_config())
experimenter.model_config = {'base_model': {'ignore': [], 'features': {'feat1': lambda x: x}, 'inherit': []},
'derived_model': {'ignore': [], 'features': {'feat1': lambda x: x},
'inherit': ['base_model']}}
self.assertTrue(experimenter.has_valid_model_config())
def test_build_learner_config(self):
experimenter = Experimenter(learner_config={'vw': {'param': ['1', '2']}})
experimenter.build_learner_config()
self.assertEquals(experimenter.learner_config, {'vw': [{'param': '1'}, {'param': '2'}]})
experimenter = Experimenter(
learner_config={'vw': {'param1': ['1', '2'], 'param2': [3, 4]}})
experimenter.build_learner_config()
print 'learner_config', experimenter.learner_config
self.assertEquals(experimenter.learner_config,
{'vw': [{'param1': '1', 'param2': 3}, {'param1': '2', 'param2': 3},
{'param1': '1', 'param2': 4}, {'param1': '2', 'param2': 4}]})
experimenter = Experimenter(
learner_config={'vw': {'param1': ['1', '2'], 'param2': [3, 4]}, 'fm': {'param3': ['5']}})
experimenter.build_learner_config()
print 'learner_config', experimenter.learner_config
self.assertEquals(experimenter.learner_config,
{'vw': [{'param1': '1', 'param2': 3}, {'param1': '2', 'param2': 3},
{'param1': '1', 'param2': 4}, {'param1': '2', 'param2': 4}],
'fm': [{'param3': '5'}]})
def test_if_has_valid_learner_config(self):
experimenter = Experimenter(learner_config={'vw': ['param']})
self.assertFalse(experimenter.has_valid_learner_config())
experimenter.learner_config = {'vw': {'param': 'value'}}
self.assertFalse(experimenter.has_valid_learner_config())
experimenter.learner_config = {
'vw': {
'param': ['value'],
'param2': 'value2'
}
}
self.assertFalse(experimenter.has_valid_learner_config())
experimenter.learner_config = {
'vw': {
'param': ['value'],
'param2': ['value2', 'value22']
}
}
self.assertTrue(experimenter.has_valid_learner_config())
def test_is_valid_model(self):
experimenter = Experimenter()
model = {'ignore': {}, 'features': {}, 'inherit': []}
self.assertFalse(experimenter.is_valid_model(model))
model = {'ignore': [], 'features': {}}
self.assertFalse(experimenter.is_valid_model(model))
model = {'ignore': [], 'features': {}, 'inherit': []}
self.assertTrue(experimenter.is_valid_model(model))
model = {'ignore': [], 'features': {'feat1': 2}, 'inherit': []}
self.assertFalse(experimenter.is_valid_model(model))
model = {'ignore': [], 'features': {'feat1': None}, 'inherit': []}
self.assertTrue(experimenter.is_valid_model(model))
model = {'ignore': [], 'features': {'feat1': lambda x: x}, 'inherit': []}
self.assertTrue(experimenter.is_valid_model(model))
def test_is_valid_model(self):
experimenter = Experimenter()
model = {'ignore': {}, 'features': {}, 'inherit': []}
self.assertFalse(experimenter.is_valid_model(model))
model = {'ignore': [], 'features': {}}
self.assertFalse(experimenter.is_valid_model(model))
model = {'ignore': [], 'features': {}, 'inherit': []}
self.assertTrue(experimenter.is_valid_model(model))
model = {'ignore': [], 'features': {'feat1': 2}, 'inherit': []}
self.assertFalse(experimenter.is_valid_model(model))
model = {'ignore': [], 'features': {'feat1': None}, 'inherit': []}
self.assertTrue(experimenter.is_valid_model(model))
model = {
'ignore': [],
'features': {
'feat1': lambda x: x
},
'inherit': []
}
self.assertTrue(experimenter.is_valid_model(model))
def test_can_format_data_config(self):
experimenter = Experimenter(
data_config={
'train': {
'tag1': '2344'
},
'test': {
'tag1': '2344'
},
'select_sql': 'SELECT * FROM {tag2}'
})
self.assertFalse(experimenter.can_format_data_config())
experimenter = Experimenter(
data_config={
'train': {
'tag1': '2344'
},
'test': {
'tag1': '2344'
},
'select_sql': 'SELECT * FROM {tag1}'
})
self.assertTrue(experimenter.can_format_data_config())
def test_build_data_config(self):
experimenter = Experimenter(data_config={'train': {'table': 'train_data'}, 'test': {'table': 'test_data'},
'select_sql': 'SELECT * FROM {table}'})
experimenter.build_data_config()
self.assertEqual(experimenter.data_config['train'], 'SELECT * FROM train_data')
self.assertEqual(experimenter.data_config['test'], 'SELECT * FROM test_data')
def test_if_has_valid_data_config(self):
experimenter = Experimenter(data_config=['a', 'b'])
self.assertFalse(experimenter.has_valid_data_config())
experimenter.data_config = {'A': 'a', 'B': 'b'}
self.assertFalse(experimenter.has_valid_data_config())
experimenter.data_config = {'Train': 'a', 'B': 'b'}
self.assertFalse(experimenter.has_valid_data_config())
experimenter.data_config = {'Train': 'a', 'Test': 'b'}
self.assertFalse(experimenter.has_valid_data_config())
experimenter.data_config = {'train': {'a': 1}, 'test': {'b': 2}}
self.assertFalse(experimenter.has_valid_data_config())
experimenter.data_config = {'train': {'a': 1}, 'test': {'b': 2}, 'select_sql': """SELECT hello FROM crap"""}
self.assertTrue(experimenter.has_valid_data_config())
experimenter.data_config = {'train': {'tag1': '2344'}, 'test': {'tag1': '2344'},
'select_sql': 'SELECT * FROM {tag2}'}
self.assertFalse(experimenter.has_valid_data_config())
experimenter.data_config = {'train': {'tag1': '2344'}, 'test': {'tag1': '2344'},
'select_sql': 'SELECT * FROM {tag1}'}
self.assertTrue(experimenter.has_valid_data_config())
lambda bad_visit_score_avg: bad_visit_score_avg.mean()
},
'learners': {
# The key is the learner name. Currently only VW is supported
'VW': {
'l1':
[14], # for example both l1=7.0 and 8.0 are evaluated here
'passes': [7],
'ftrl_alpha': [0.05623413251903491],
'ftrl_beta': [0.0],
'sort_features': [''],
'hash': ["strings"],
'bit_precision': [29],
'ftrl': [''],
'loss_function': ["logistic"],
'l2': [0.0],
'quiet': [''],
'sort_features': ['']
}
}
}
}
from Experiment import Experimenter
experiment = Experimenter(name=EXPERIMENT_NAME,
data_config=DATA_CONFIG,
model_config=MODEL_CONFIG,
threads=1,
greed_level=1)
experiment.run_experiment()
def test_if_has_valid_data_config(self):
experimenter = Experimenter(data_config=['a', 'b'])
self.assertFalse(experimenter.has_valid_data_config())
experimenter.data_config = {'A': 'a', 'B': 'b'}
self.assertFalse(experimenter.has_valid_data_config())
experimenter.data_config = {'Train': 'a', 'B': 'b'}
self.assertFalse(experimenter.has_valid_data_config())
experimenter.data_config = {'Train': 'a', 'Test': 'b'}
self.assertFalse(experimenter.has_valid_data_config())
experimenter.data_config = {'train': {'a': 1}, 'test': {'b': 2}}
self.assertFalse(experimenter.has_valid_data_config())
experimenter.data_config = {
'train': {
'a': 1
},
'test': {
'b': 2
},
'select_sql': """SELECT hello FROM crap"""
}
self.assertTrue(experimenter.has_valid_data_config())
experimenter.data_config = {
'train': {
'tag1': '2344'
},
'test': {
'tag1': '2344'
},
'select_sql': 'SELECT * FROM {tag2}'
}
self.assertFalse(experimenter.has_valid_data_config())
experimenter.data_config = {
'train': {
'tag1': '2344'
},
'test': {
'tag1': '2344'
},
'select_sql': 'SELECT * FROM {tag1}'
}
self.assertTrue(experimenter.has_valid_data_config())
def test_build_model_config(self):
experimenter = Experimenter()
func = lambda x: x
experimenter.model_config = {
'base_model': {
'ignore': [],
'features': {
'feat1': func
},
'inherit': []
}
}
experimenter.build_model_config()
self.assertEquals(experimenter.model_config,
{'base_model': {
'feat1': func
}})
experimenter.model_config = {
'base_model': {
'ignore': [],
'features': {
'feat1': func
},
'inherit': []
},
'derived_model': {
'ignore': [],
'features': {},
'inherit': ['base_model']
}
}
experimenter.build_model_config()
self.assertEquals(experimenter.model_config, {
'base_model': {
'feat1': func
},
'derived_model': {
'feat1': func
}
})
experimenter.model_config = {
'base_model': {
'ignore': [],
'features': {
'feat1': func
},
'inherit': []
},
'derived_model': {
'ignore': ['feat1'],
'features': {
'feat2': None
},
'inherit': ['base_model']
}
}
experimenter.build_model_config()
self.assertEquals(experimenter.model_config, {
'base_model': {
'feat1': func
},
'derived_model': {
'feat2': None
}
})
experimenter.model_config = {
'base_model': {
'ignore': [],
'features': {
'feat1': func
},
'inherit': ['derived_model']
},
'derived_model': {
'ignore': ['feat1'],
'features': {
'feat2': None
},
'inherit': ['base_model']
}
}
experimenter.build_model_config()
self.assertEquals(experimenter.model_config, {
'base_model': {
'feat2': None
},
'derived_model': {
'feat2': None
}
})
}
}
},
'with_browser and os and device_type ids': {
'inherit': ['with_os_id', 'with_browser_id', 'with_device_id'],
'features': {},
'learners': {
# The key is the learner name. Currently only VW is supported
'VW': {
'l1': [14], # for example both l1=7.0 and 8.0 are evaluated here
'passes': [7],
'ftrl_alpha': [0.05623413251903491],
'ftrl_beta': [0.0],
'sort_features': [''],
'hash': ["strings"],
'bit_precision': [29],
'ftrl': [''],
'loss_function': ["logistic"],
'l2': [0.0],
'quiet': [''],
'sort_features': ['']
}
}
}
}
from Experiment import Experimenter
experiment = Experimenter(datafile=EXPERIMENT_NAME + '.h5', data_config=DATA_CONFIG, model_config=MODEL_CONFIG,
learner_config=LEARNER_CONFIG)
experiment.run_experiment()
def test_build_model_config(self):
experimenter = Experimenter()
func = lambda x: x
experimenter.model_config = {'base_model': {'ignore': [], 'features': {'feat1': func}, 'inherit': []}}
experimenter.build_model_config()
self.assertEquals(experimenter.model_config, {'base_model': {'feat1': func}})
experimenter.model_config = {'base_model': {'ignore': [], 'features': {'feat1': func}, 'inherit': []},
'derived_model': {'ignore': [], 'features': {}, 'inherit': ['base_model']}}
experimenter.build_model_config()
self.assertEquals(experimenter.model_config, {'base_model': {'feat1': func}, 'derived_model': {'feat1': func}})
experimenter.model_config = {'base_model': {'ignore': [], 'features': {'feat1': func}, 'inherit': []},
'derived_model': {'ignore': ['feat1'], 'features': {'feat2': None},
'inherit': ['base_model']}}
experimenter.build_model_config()
self.assertEquals(experimenter.model_config, {'base_model': {'feat1': func}, 'derived_model': {'feat2': None}})
experimenter.model_config = {
'base_model': {'ignore': [], 'features': {'feat1': func}, 'inherit': ['derived_model']},
'derived_model': {'ignore': ['feat1'], 'features': {'feat2': None}, 'inherit': ['base_model']}}
experimenter.build_model_config()
self.assertEquals(experimenter.model_config, {'base_model': {'feat2': None}, 'derived_model': {'feat2': None}})
'VW': {
'l1': [14],
'passes': [7],
'ftrl_alpha': [0.05623413251903491],
'ftrl_beta': [0.0],
'sort_features': [''],
'hash': ["strings"],
'bit_precision': [29],
'ftrl': [''],
'loss_function': ["logistic"],
'l2': [0.0],
'quiet': [''],
'sort_features': ['']
}
}
}
}
from Experiment import Experimenter
experiment = Experimenter(name=EXPERIMENT_NAME,
data_config=DATA_CONFIG,
model_config=MODEL_CONFIG,
threads=1,
greed_level=4,
cache_data=True,
cache_features=True,
cache_results=True)
experiment.run_experiment()
def test_build_learner_config(self):
experimenter = Experimenter(
learner_config={'vw': {
'param': ['1', '2']
}})
experimenter.build_learner_config()
self.assertEquals(experimenter.learner_config,
{'vw': [{
'param': '1'
}, {
'param': '2'
}]})
experimenter = Experimenter(
learner_config={'vw': {
'param1': ['1', '2'],
'param2': [3, 4]
}})
experimenter.build_learner_config()
print 'learner_config', experimenter.learner_config
self.assertEquals(
experimenter.learner_config, {
'vw': [{
'param1': '1',
'param2': 3
}, {
'param1': '2',
'param2': 3
}, {
'param1': '1',
'param2': 4
}, {
'param1': '2',
'param2': 4
}]
})
experimenter = Experimenter(
learner_config={
'vw': {
'param1': ['1', '2'],
'param2': [3, 4]
},
'fm': {
'param3': ['5']
}
})
experimenter.build_learner_config()
print 'learner_config', experimenter.learner_config
self.assertEquals(
experimenter.learner_config, {
'vw': [{
'param1': '1',
'param2': 3
}, {
'param1': '2',
'param2': 3
}, {
'param1': '1',
'param2': 4
}, {
'param1': '2',
'param2': 4
}],
'fm': [{
'param3': '5'
}]
})
