def testInit(self):
p = base_model.MultiTaskModel.Params()
p.name = 'MultiTaskModel'
p0 = BaseTaskTest.TestParams()
p0.train.learner = (learner.Learner.Params().Set(name='loss'))
p1 = BaseTaskTest.TestParams()
p1.train.learner = (learner.Learner.Params().Set(name='loss'))
p.input = base_model_params.MultiTaskModelParams().Train()
p.input.Define(
'a', base_input_generator.BaseSequenceInputGenerator.Params(), '')
p.input.Define(
'b', base_input_generator.BaseSequenceInputGenerator.Params(), '')
p.task_params = hyperparams.Params()
p.task_params.Define('a', p0, '')
p.task_params.Define('b', p1, '')
p.task_probs = hyperparams.Params()
p.task_probs.Define('a', 0.5, '')
p.task_probs.Define('b', 0.5, '')
model = p.Instantiate()
self.assertEqual(len(model.tasks), 2)
self.assertEqual(set(model.task_names), {'a', 'b'})
self.assertEqual(
set(model.tasks),
{model.GetTask('a'), model.GetTask('b')})
self.assertEqual(model.params.task_params.a, model.GetTask('a').params)
self.assertEqual(model.params.task_params.b, model.GetTask('b').params)
def testSharedEncoderDecoderModel(self):
p = multitask_model.SharedEncoderDecoderModel.Params()
p.name = 'test'
p.encoder_to_share = 'p0'
p.decoder_to_share = 'p0'
p0 = MultiTaskModelTest._TestTask.Params()
p1 = MultiTaskModelTest._TestTask.Params()
p1.encoder = None
p1.decoder = None
p.input = base_model_params.MultiTaskModelParams().Train()
p.input.Define('p0', base_input_generator.BaseInputGenerator.Params(),
'')
p.input.Define('p1', base_input_generator.BaseInputGenerator.Params(),
'')
p.task_params = hyperparams.Params()
p.task_params.Define('p0', p0, '')
p.task_params.Define('p1', p1, '')
p.task_probs = hyperparams.Params()
p.task_probs.Define('p0', 0.5, '')
p.task_probs.Define('p1', 0.5, '')
model = p.Instantiate()
self.assertEqual(model.p0.encoder, model.p1.encoder)
self.assertEqual(model.p0.decoder, model.p1.decoder)
def testRegExSharedVariableModel(self):
p = multitask_model.RegExSharedVariableModel.Params()
p.name = 'test'
p.variable_renaming_rules = [('p./(.*)', 'shared/%s')]
p0 = MultiTaskModelTest._TestTaskWithVars.Params()
p1 = MultiTaskModelTest._TestTaskWithVars.Params()
p.input = base_model_params.MultiTaskModelParams().Train()
p.input.Define('p0', base_input_generator.BaseInputGenerator.Params(),
'')
p.input.Define('p1', base_input_generator.BaseInputGenerator.Params(),
'')
p.task_params = hyperparams.Params()
p.task_params.Define('p0', p0, '')
p.task_params.Define('p1', p1, '')
p.task_probs = hyperparams.Params()
p.task_probs.Define('p0', 0.5, '')
p.task_probs.Define('p1', 0.5, '')
model = p.Instantiate()
all_vars = model.vars
self.assertEqual('shared/weight/var:0', all_vars.p0.weight.name)
self.assertEqual('shared/weight/var:0', all_vars.p1.weight.name)
def testGetDatasetParams_MultiTaskModelParams(self):
dummy_model = base_model_params.MultiTaskModelParams()
self.assertEqual(dummy_model.Train(), dummy_model.GetDatasetParams('Train'))
self.assertEqual(dummy_model.Dev(), dummy_model.GetDatasetParams('Dev'))
self.assertEqual(dummy_model.Test(), dummy_model.GetDatasetParams('Test'))
with self.assertRaises(base_model_params.DatasetError):
dummy_model.GetDatasetParams('Invalid')
def _setUpTestSampleTask(self):
np.random.seed(_NUMPY_RANDOM_SEED)
# define and initialize tasks, model and params
p = base_model.MultiTaskModel.Params()
p.name = 'MultiTaskModel'
p0 = BaseTaskTest.TestParams()
p1 = BaseTaskTest.TestParams()
p.input = base_model_params.MultiTaskModelParams().Train()
p.input.Define(
'a', base_input_generator.BaseSequenceInputGenerator.Params(), '')
p.input.Define(
'b', base_input_generator.BaseSequenceInputGenerator.Params(), '')
p.task_params = hyperparams.Params()
p.task_params.Define('a', p0, '')
p.task_params.Define('b', p1, '')
return p
def testInitMissingInputParams(self):
p = base_model.MultiTaskModel.Params()
p.name = 'MultiTaskModel'
p0 = BaseTaskTest.TestParams()
p0.train.learner = (learner.Learner.Params().Set(name='loss'))
p1 = BaseTaskTest.TestParams()
p1.train.learner = (learner.Learner.Params().Set(name='loss'))
p.input = base_model_params.MultiTaskModelParams().Train()
p.input.Define(
'a', base_input_generator.BaseSequenceInputGenerator.Params(), '')
p.task_params = hyperparams.Params()
p.task_params.Define('a', p0, '')
p.task_params.Define('b', p1, '')
p.task_probs = hyperparams.Params()
p.task_probs.Define('a', 0.5, '')
p.task_probs.Define('b', 0.5, '')
self.assertRaises(AttributeError, p.Instantiate)