Merge pull request #3030 from microsoft/v2.0

Merge v2.0 into master

src/sdk/pynni/nni/hyperband_advisor/hyperband_advisor.py → nni/algorithms/hpo/hyperband_advisor/hyperband_advisor.py

@@ -15,9 +15,9 @@ import numpy as np
 from schema import Schema, Optional
 
 from nni import ClassArgsValidator
-from nni.common import multi_phase_enabled
-from nni.msg_dispatcher_base import MsgDispatcherBase
-from nni.protocol import CommandType, send
+from nni.runtime.common import multi_phase_enabled
+from nni.runtime.msg_dispatcher_base import MsgDispatcherBase
+from nni.runtime.protocol import CommandType, send
 from nni.utils import NodeType, OptimizeMode, MetricType, extract_scalar_reward
 from nni import parameter_expressions
 

src/sdk/pynni/nni/metis_tuner/Regression_GMM/Selection.py → nni/algorithms/hpo/metis_tuner/Regression_GMM/Selection.py

@@ -5,8 +5,8 @@ import os
 import random
 import sys
 
-import nni.metis_tuner.lib_acquisition_function as lib_acquisition_function
-import nni.metis_tuner.lib_constraint_summation as lib_constraint_summation
+from .. import lib_acquisition_function
+from .. import lib_constraint_summation
 
 sys.path.insert(1, os.path.join(sys.path[0], '..'))
 

src/sdk/pynni/nni/metis_tuner/Regression_GP/OutlierDetection.py → nni/algorithms/hpo/metis_tuner/Regression_GP/OutlierDetection.py

@@ -9,8 +9,8 @@ import os
 import sys
 from multiprocessing.dummy import Pool as ThreadPool
 
-import nni.metis_tuner.Regression_GP.CreateModel as gp_create_model
-import nni.metis_tuner.Regression_GP.Prediction as gp_prediction
+from . import CreateModel as gp_create_model
+from . import Prediction as gp_prediction
 
 sys.path.insert(1, os.path.join(sys.path[0], '..'))
 

src/sdk/pynni/nni/metis_tuner/Regression_GP/Selection.py → nni/algorithms/hpo/metis_tuner/Regression_GP/Selection.py

@@ -5,10 +5,10 @@ import os
 import random
 import sys
 
-import nni.metis_tuner.lib_acquisition_function as lib_acquisition_function
-import nni.metis_tuner.lib_constraint_summation as lib_constraint_summation
-import nni.metis_tuner.lib_data as lib_data
-import nni.metis_tuner.Regression_GP.Prediction as gp_prediction
+from .. import lib_acquisition_function
+from .. import lib_constraint_summation
+from .. import lib_data
+from . import Prediction as gp_prediction
 
 sys.path.insert(1, os.path.join(sys.path[0], '..'))
 

src/sdk/pynni/nni/metis_tuner/lib_acquisition_function.py → nni/algorithms/hpo/metis_tuner/lib_acquisition_function.py

@@ -11,7 +11,7 @@ import numpy
 from scipy.stats import norm
 from scipy.optimize import minimize
 
-import nni.metis_tuner.lib_data as lib_data
+from . import lib_data
 
 
 def next_hyperparameter_expected_improvement(fun_prediction,