Ejemplo n.º 1
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 def test_29_load(self):
     global auto_lmgpip_regressor, auto_lmgpip_basic_regressor
     auto_lmgpip_regressor = AutoAdvanced(
         **auto_lmgpip_regressor_params).load()
     auto_lmgpip_basic_regressor = AutoBasic(
         **auto_lmgpip_regressor_params).load()
     self.assertIsInstance(auto_lmgpip_regressor, AutoAdvanced,
                           "Load failed")
     self.assertIsInstance(auto_lmgpip_basic_regressor, AutoBasic,
                           "Load failed")
Ejemplo n.º 2
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 def test_23_load(self):
     global auto_lmgpip_nn, auto_lmgpip_basic_nn
     auto_lmgpip_nn = AutoAdvanced(**auto_lmgpip_params).load()
     auto_lmgpip_basic_nn = AutoBasic(**auto_lmgpip_params).load()
     self.assertIsInstance(auto_lmgpip_nn, AutoAdvanced, "Load failed")
     self.assertIsInstance(auto_lmgpip_basic_nn, AutoBasic, "Load failed")
Ejemplo n.º 3
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 def test_11_load(self):
     global auto_mushroom_nn, auto_mushroom_basic_nn
     auto_mushroom_nn = AutoAdvanced(**auto_mushroom_params).load()
     auto_mushroom_basic_nn = AutoBasic(**auto_mushroom_params).load()
     self.assertIsInstance(auto_mushroom_nn, AutoAdvanced, "Load failed")
     self.assertIsInstance(auto_mushroom_basic_nn, AutoBasic, "Load failed")
Ejemplo n.º 4
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 def test_04_load(self):
     global nn, basic_nn
     nn = AutoAdvanced(**base_params).load()
     basic_nn = AutoBasic(**base_params).load()
     self.assertIsInstance(nn, AutoAdvanced, "Load failed")
     self.assertIsInstance(basic_nn, AutoBasic, "Load failed")
Ejemplo n.º 5
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from Util.Util import DataUtil
from _Dist.NeuralNetworks.b_TraditionalML.SVM import AutoLinearSVM
from _Dist.NeuralNetworks.f_AutoNN.NN import AutoBasic, AutoAdvanced
from _Dist.NeuralNetworks._Tests._UnitTests.UnitTestUtil import clear_cache

base_params = {
    "name": "UnitTest",
    "data_info": {},
    "model_param_settings": {
        "n_epoch": 1,
        "max_epoch": 2
    }
}
nn = AutoAdvanced(**copy.deepcopy(base_params))
basic_nn = AutoBasic(**copy.deepcopy(base_params))
linear_svm = AutoLinearSVM(**copy.deepcopy(base_params))
train_set, cv_set, test_set = DataUtil.gen_special_linear(1000,
                                                          2,
                                                          2,
                                                          2,
                                                          one_hot=False)

auto_mushroom_params = copy.deepcopy(base_params)
auto_mushroom_params["name"] = "mushroom"
auto_mushroom_params["data_info"]["file_type"] = "txt"
auto_mushroom_params["data_info"]["data_folder"] = "../_Data"
mushroom_labels = {"p", "e"}
mushroom_file = "../_Data/mushroom"
auto_mushroom_nn = AutoAdvanced(**copy.deepcopy(auto_mushroom_params))
auto_mushroom_basic_nn = AutoBasic(**copy.deepcopy(auto_mushroom_params))
Ejemplo n.º 6
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import os
import sys
root_path = os.path.abspath("../../../../")
if root_path not in sys.path:
    sys.path.append(root_path)

from _Dist.NeuralNetworks._Tests.TestUtil import draw_acc
from _Dist.NeuralNetworks.f_AutoNN.NN import AutoBasic, AutoAdvanced
from _Dist.NeuralNetworks._Tests.Madelon.MadelonUtil import get_madelon

x, y, x_test, y_test = get_madelon()

base_params = {
    "name": "Madelon",
    "model_param_settings": {"n_epoch": 200, "metric": "acc"},
    "model_structure_settings": {"hidden_units": [152, 153]}
}
basic = AutoBasic(**base_params).fit(x, y, x_test, y_test, snapshot_ratio=0)
advanced = AutoAdvanced(**base_params).fit(x, y, x_test, y_test, snapshot_ratio=0)
draw_acc(basic, advanced, ylim=(0.5, 1.05))