Refine automl import

pyzoo/test/zoo/automl/model/test_Seq2Seq.py

@@ -20,9 +20,12 @@
 import pytest
 
 from test.zoo.pipeline.utils.test_utils import ZooTestCase
-from zoo.automl.model.Seq2Seq import *
+from zoo.automl.model.Seq2Seq import LSTMSeq2Seq
 from zoo.automl.feature.time_sequence import TimeSequenceFeatureTransformer
 from numpy.testing import assert_array_almost_equal
+import pandas as pd
+import numpy as np
+from zoo.automl.common.util import save, restore
 
 
 class TestSeq2Seq(ZooTestCase):

pyzoo/test/zoo/automl/model/test_TCMF.py

@@ -17,7 +17,7 @@
 import pytest
 
 from test.zoo.pipeline.utils.test_utils import ZooTestCase
-from zoo.automl.model import TCMF
+from zoo.automl.model.tcmf_model import TCMF
 import numpy as np
 import os
 from numpy.testing import assert_array_almost_equal

pyzoo/test/zoo/automl/model/test_VanillaLSTM.py

@@ -17,9 +17,14 @@
 import pytest
 
 from test.zoo.pipeline.utils.test_utils import ZooTestCase
-from zoo.automl.model.VanillaLSTM import *
+from zoo.automl.model.VanillaLSTM import VanillaLSTM
 from zoo.automl.feature.time_sequence import TimeSequenceFeatureTransformer
 from numpy.testing import assert_array_almost_equal
+import numpy as np
+import pandas as pd
+from zoo.automl.common.util import save, restore
+import tempfile
+import shutil
 
 
 class TestVanillaLSTM(ZooTestCase):

pyzoo/test/zoo/automl/model/test_xgbregressor.py

@@ -23,7 +23,7 @@
 import os
 from numpy.testing import assert_array_almost_equal
 
-from zoo.automl.model import XGBoostRegressor
+from zoo.automl.model.XGBoostRegressor import XGBoostRegressor
 from zoo.automl.feature.identity_transformer import IdentityTransformer
 
 

pyzoo/test/zoo/automl/pipeline/test_time_sequence.py

@@ -19,12 +19,10 @@
 import pytest
 
 from test.zoo.pipeline.utils.test_utils import ZooTestCase
-from zoo.automl.model import BaseModel
 from zoo.automl.pipeline.time_sequence import *
 from zoo.automl.regression.time_sequence_predictor import *
 import numpy as np
 import pandas as pd
-import ray
 from pandas.util.testing import assert_frame_equal
 from numpy.testing import assert_array_almost_equal
 

pyzoo/test/zoo/automl/regression/test_time_sequence_predictor.py

@@ -16,8 +16,7 @@
 import pytest
 
 from test.zoo.pipeline.utils.test_utils import ZooTestCase
-from zoo.automl.config.recipe import *
-from zoo.automl.model import BaseModel
+from zoo.automl.model.abstract import BaseModel
 from zoo.automl.regression.time_sequence_predictor import *
 
 

pyzoo/zoo/automl/model/MTNet_keras.py

@@ -41,12 +41,9 @@
 from tensorflow.keras.layers import *
 from tensorflow.keras.initializers import TruncatedNormal, Constant
 import tensorflow.keras.backend as K
-import math
 
 import tensorflow as tf
-# _Linear = core_rnn_cell._Linear
 from zoo.automl.common.metrics import Evaluator
-import pandas as pd
 from zoo.automl.model.abstract import BaseModel
 from zoo.automl.common.util import save_config
 

pyzoo/zoo/automl/model/Seq2Seq.py

@@ -13,17 +13,11 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 #
-import json
 
-from time import time
-from tensorflow.keras.callbacks import TensorBoard
 from tensorflow.keras.models import Model
 from tensorflow.keras.layers import Input, LSTM, Dense
 import tensorflow.keras as keras
 
-import os
-
-from zoo.automl.feature.time_sequence import TimeSequenceFeatureTransformer
 from zoo.automl.model.abstract import BaseModel
 from zoo.automl.common.util import *
 from zoo.automl.common.metrics import Evaluator

pyzoo/zoo/automl/model/Seq2Seq_pytorch.py

@@ -18,11 +18,8 @@
 
 import torch
 import torch.nn as nn
-import torch.nn.functional as F
-import torch.optim as optim
 from torch.utils.data import TensorDataset, DataLoader
 
-from zoo.automl.feature.time_sequence import TimeSequenceFeatureTransformer
 from zoo.automl.model.abstract import BaseModel
 from zoo.automl.common.util import *
 from zoo.automl.common.metrics import Evaluator

pyzoo/zoo/automl/model/VanillaLSTM.py

@@ -14,10 +14,9 @@
 # limitations under the License.
 #
 
-from tensorflow.keras.models import Sequential, Model
+from tensorflow.keras.models import Model
 from tensorflow.keras.layers import Input, Dense, LSTM, Dropout
 import tensorflow.keras as keras
-import os
 
 from zoo.automl.model.abstract import BaseModel
 from zoo.automl.common.util import *
@@ -70,20 +69,6 @@ def _build(self, mc=False, **config):
         out = Dense(self.future_seq_len)(dropout_2)
         self.model = Model(inputs=inp, outputs=out)
 
-        # self.model = Sequential()
-        # self.model.add(LSTM(
-        #     # input_shape=(config.get('input_shape_x', 20),
-        #     #             config.get('input_shape_y', 20)),
-        #     units=config.get('lstm_1_units', 20),
-        #     return_sequences=True))
-        # self.model.add(Dropout(config.get('dropout_1', 0.2)))
-        #
-        # self.model.add(LSTM(
-        #     units=config.get('lstm_2_units', 10),
-        #     return_sequences=False))
-        # self.model.add(Dropout(config.get('dropout_2', 0.2)))
-
-        # self.model.add(Dense(self.future_seq_len))
         self.model.compile(loss=self.loss,
                            metrics=[self.metric],
                            optimizer=keras.optimizers.RMSprop(lr=config.get('lr', 0.001)))

pyzoo/zoo/automl/model/VanillaLSTM_pytorch.py

@@ -16,11 +16,8 @@
 
 import torch
 import torch.nn as nn
-import torch.nn.functional as F
-import torch.optim as optim
 from torch.utils.data import TensorDataset, DataLoader
 
-from zoo.automl.feature.time_sequence import TimeSequenceFeatureTransformer
 from zoo.automl.model.abstract import BaseModel
 from zoo.automl.common.util import *
 from zoo.automl.common.metrics import Evaluator

pyzoo/zoo/automl/model/__init__.py

@@ -13,10 +13,3 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 #
-
-from .abstract import *
-from .tcmf_model import *
-from .VanillaLSTM import *
-from .Seq2Seq import *
-from .time_sequence import *
-from .XGBoostRegressor import *

pyzoo/zoo/automl/model/tcmf_model.py

@@ -20,7 +20,6 @@
 from zoo.orca.data import SparkXShards, XShards
 import pickle
 import numpy as np
-import pandas as pd
 
 
 class TCMF(BaseModel):

pyzoo/zoo/automl/pipeline/time_sequence.py

@@ -13,15 +13,13 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 #
-import os
-import tempfile
 import time
 
 from zoo.automl.common.metrics import Evaluator
 from zoo.automl.pipeline.abstract import Pipeline
 from zoo.automl.common.util import *
 from zoo.automl.feature.time_sequence import TimeSequenceFeatureTransformer
-from zoo.automl.model import TimeSequenceModel
+from zoo.automl.model.time_sequence import TimeSequenceModel
 from zoo.automl.common.parameters import *
 
 
@@ -223,7 +221,7 @@ def load_ts_pipeline(file):
 
 def load_xgboost_pipeline(file):
     from zoo.automl.feature.identity_transformer import IdentityTransformer
-    from zoo.automl.model import XGBoostRegressor
+    from zoo.automl.model.XGBoostRegressor import XGBoostRegressor
     feature_transformers = IdentityTransformer()
     model = XGBoostRegressor()
 

pyzoo/zoo/automl/regression/time_sequence_predictor.py

@@ -15,21 +15,12 @@
 # limitations under the License.
 #
 
-
-import numpy as np
-import tempfile
-import zipfile
-import os
-import shutil
-import ray
-
-from zoo.automl.search.abstract import *
 from zoo.automl.search.RayTuneSearchEngine import RayTuneSearchEngine
 from zoo.automl.common.metrics import Evaluator
 from zoo.automl.feature.time_sequence import TimeSequenceFeatureTransformer
 
-from zoo.automl.model import TimeSequenceModel
-from zoo.automl.pipeline.time_sequence import TimeSequencePipeline, load_ts_pipeline
+from zoo.automl.model.time_sequence import TimeSequenceModel
+from zoo.automl.pipeline.time_sequence import TimeSequencePipeline
 from zoo.automl.common.util import *
 from zoo.automl.config.recipe import *
 

pyzoo/zoo/automl/regression/xgbregressor_predictor.py

@@ -15,19 +15,11 @@
 # limitations under the License.
 #
 
-
-import numpy as np
-import tempfile
-import zipfile
-import os
-import shutil
-
-from zoo.automl.search.abstract import *
 from zoo.automl.search.RayTuneSearchEngine import RayTuneSearchEngine
 from zoo.automl.common.metrics import Evaluator
 from zoo.automl.feature.identity_transformer import IdentityTransformer
 
-from zoo.automl.model import XGBoostRegressor
+from zoo.automl.model.XGBoostRegressor import XGBoostRegressor
 from zoo.automl.pipeline.time_sequence import TimeSequencePipeline
 from zoo.automl.common.util import *
 from zoo.automl.config.recipe import *

pyzoo/zoo/automl/search/RayTuneSearchEngine.py

@@ -16,7 +16,7 @@
 
 import ray
 from ray import tune
-from copy import copy, deepcopy
+from copy import deepcopy
 
 from zoo.automl.search.abstract import *
 from zoo.automl.common.util import *

pyzoo/zoo/zouwu/model/forecast.py

@@ -19,11 +19,10 @@
 from zoo.automl.model.MTNet_keras import MTNetKeras as MTNetKerasModel
 from zoo.automl.model.VanillaLSTM import VanillaLSTM as LSTMKerasModel
 from zoo.tfpark import KerasModel as TFParkKerasModel
-from zoo.automl.model import TCMFLocalModelWrapper, TCMFDistributedModelWrapper
+from zoo.automl.model.tcmf_model import TCMFLocalModelWrapper, TCMFDistributedModelWrapper
 from zoo.orca.data import SparkXShards
 
 import tensorflow as tf
-import pandas as pd
 
 
 class Forecaster(metaclass=ABCMeta):