def values_single_test(self):
print("BinaryTest : Running values_single_test...")
Scan(self.x,
self.y,
params=self.values_single,
model=ta.templates.models.cervical_cancer)
def values_list_test(self):
print("MultiLabelTest : Running values_list_test...")
Scan(self.x,
self.y,
x_val=self.x_val,
y_val=self.y_val,
params=self.values_list,
round_limit=5,
dataset_name='MultiLabelTest',
experiment_no='000',
model=ta.templates.models.iris,
random_method='crypto_uniform',
seed=2423,
search_method='linear',
permutation_filter=lambda p: p['first_neuron'] * p['hidden_layers'] < 9,
reduction_method='correlation',
reduction_interval=2,
reduction_window=2,
reduction_threshold=0.2,
reduction_metric='val_loss',
reduce_loss=True,
last_epoch_value=True,
clear_tf_session=False,
disable_progress_bar=True,
debug=True)
def test_scan_iris_1(self):
print("Running Iris dataset test 1...")
Scan(self.x,
self.y,
params=p1,
dataset_name='testing',
experiment_no='000',
model=iris_model)
def test_scan_cancer_metric_reduction(self):
print("Running Cervical Cancer dataset test...")
Scan(self.x, self.y, grid_downsample=0.0005, params=p3,
dataset_name='testing', experiment_no='a',
model=self.model,
reduction_threshold=0.01,
reduction_method='correlation',
reduction_interval=2)
def test_scan_iris_2(self):
print("Running Iris dataset test 2...")
Scan(self.x,
self.y,
params=p2,
dataset_name='testing',
experiment_no='000',
model=iris_model,
last_epoch_value=True)
def test_scan_iris_2(self):
print("Running Iris dataset test 2...")
Scan(self.x,
self.y,
params=p2,
dataset_name='testing',
experiment_no='000',
model=iris_model)
Reporting('testing_000.csv')
def test_scan_iris_explicit_validation_set_force_fail(self):
print("Running explicit validation dataset test with loss reduction")
try:
Scan(self.x_train, self.y_train, params=p2,
dataset_name='testing',
experiment_no='000', model=iris_model,
y_val=self.y_dev)
except RuntimeError:
pass
def test_scan_iris_explicit_validation_set(self):
print("Running explicit validation dataset test with metric reduction")
Scan(self.x_train,
self.y_train,
params=p2,
dataset_name='testing',
experiment_no='000',
model=iris_model,
x_val=self.x_dev,
y_val=self.y_dev)
def test_reverse_method(self):
print("Testing reverse method on Cancer dataset...")
Scan(self.x,
self.y,
params=p3,
dataset_name='testing',
search_method='reverse',
grid_downsample=0.00025,
experiment_no='000',
model=self.model)
def test_linear_method(self):
print("Testing linear method on Cancer dataset...")
Scan(self.x,
self.y,
params=p3,
dataset_name='testing',
search_method='linear',
grid_downsample=0.0005,
experiment_no='000',
model=self.model)
def test_scan_cancer(self):
print("Running Cervical Cancer dataset test...")
Scan(self.x,
self.y,
grid_downsample=0.0005,
params=p3,
dataset_name='testing',
experiment_no='a',
model=self.model,
reduction_method='correlation',
reduction_interval=5)
Reporting('testing_a.csv')
def values_range_test(self):
print("MultiLabelTest : Running values_range_test...")
Scan(self.x,
self.y,
params=self.values_range,
model=ta.templates.models.iris,
grid_downsample=0.0001,
random_method='sobol',
reduction_method='correlation',
reduction_interval=2,
reduction_window=2,
reduction_threshold=0.2,
reduction_metric='val_acc',
reduce_loss=False,
debug=True)
def values_range_test(self):
print("BinaryTest : Running values_range_test...")
Scan(self.x_train,
self.y_train,
params=self.values_range,
model=ta.templates.models.cervical_cancer,
grid_downsample=0.0001,
permutation_filter=lambda p: p['first_neuron'] * p['hidden_layers'] < 220,
random_method='sobol',
reduction_method='correlation',
reduction_interval=2,
reduction_window=2,
reduction_threshold=0.2,
reduction_metric='val_acc',
reduce_loss=False,
debug=True)
def values_list_test(self):
print("BinaryTest : Running values_list_test...")
Scan(self.x_train,
self.y_train,
x_val=self.x_val,
y_val=self.y_val,
params=self.values_list,
round_limit=5,
dataset_name='BinaryTest',
experiment_no='000',
model=ta.templates.models.cervical_cancer,
random_method='crypto_uniform',
seed=2423,
search_method='linear',
reduction_method='correlation',
reduction_interval=2,
reduction_window=2,
reduction_threshold=0.2,
reduction_metric='val_loss',
reduce_loss=True,
last_epoch_value=True,
clear_tf_session=False,
disable_progress_bar=True,
debug=True)
def values_single_test(self):
print("MultiLabelTest : Running values_single_test...")
Scan(self.x,
self.y,
params=self.values_single,
model=ta.templates.models.iris)
