chore: change all Keras imports by tensorflow.keras imports to be com…

…patible with Keras-2.4 and tensorflow-2.3.

This does not break previous requirements or installations as Keras is part of TF since tensorflow-2.0.
Fixes: #35

conda/meta.yaml

@@ -16,4 +16,5 @@ requirements:
         - python>=3.6
         - nilmtk>=0.4
         - keras>=2.2.4
+        - tensorflow>=2.0
         - cvxpy>=1.0.0

nilmtk_contrib/disaggregate/WindowGRU.py

@@ -12,12 +12,12 @@
 import os
 import pickle
 
-from keras.models import Sequential
-from keras.layers import Dense, Conv1D, GRU, Bidirectional, Dropout
-from keras.utils import plot_model
+from tensorflow.keras.models import Sequential
+from tensorflow.keras.layers import Dense, Conv1D, GRU, Bidirectional, Dropout
+from tensorflow.keras.utils import plot_model
 from sklearn.model_selection import train_test_split
-from keras.callbacks import ModelCheckpoint
-import keras.backend as K
+from tensorflow.keras.callbacks import ModelCheckpoint
+import tensorflow.keras.backend as K
 from nilmtk.utils import find_nearest
 from nilmtk.feature_detectors import cluster
 from nilmtk.disaggregate import Disaggregator
@@ -188,4 +188,4 @@ def return_network(self):
         model.add(Dropout(0.5))
         model.add(Dense(1, activation='linear'))
         model.compile(loss='mse', optimizer='adam')
-        return model
+        return model

nilmtk_contrib/disaggregate/dae.py

@@ -1,16 +1,16 @@
 from __future__ import print_function, division
 from warnings import warn
 from nilmtk.disaggregate import Disaggregator
-from keras.layers import Conv1D, Dense, Dropout, Reshape, Flatten
+from tensorflow.keras.layers import Conv1D, Dense, Dropout, Reshape, Flatten
 import pandas as pd
 import numpy as np
 from collections import OrderedDict 
-from keras.optimizers import SGD
-from keras.models import Sequential
+from tensorflow.keras.optimizers import SGD
+from tensorflow.keras.models import Sequential
 import matplotlib.pyplot as  plt
 from sklearn.model_selection import train_test_split
-from keras.callbacks import ModelCheckpoint
-import keras.backend as K
+from tensorflow.keras.callbacks import ModelCheckpoint
+import tensorflow.keras.backend as K
 from statistics import mean
 import os
 import pickle

nilmtk_contrib/disaggregate/rnn.py

@@ -1,18 +1,18 @@
 from __future__ import print_function, division
 from warnings import warn
 from nilmtk.disaggregate import Disaggregator
-from keras.layers import Conv1D, Dense, Dropout, Reshape, Flatten, Bidirectional, LSTM
+from tensorflow.keras.layers import Conv1D, Dense, Dropout, Reshape, Flatten, Bidirectional, LSTM
 import os
 import pickle
 import pandas as pd
 import numpy as np
 from collections import OrderedDict
-from keras.optimizers import SGD
-from keras.models import Sequential, load_model
+from tensorflow.keras.optimizers import SGD
+from tensorflow.keras.models import Sequential, load_model
 import matplotlib.pyplot as plt
 from sklearn.model_selection import train_test_split
-from keras.callbacks import ModelCheckpoint
-import keras.backend as K
+from tensorflow.keras.callbacks import ModelCheckpoint
+import tensorflow.keras.backend as K
 import random
 import sys
 random.seed(10)
@@ -192,4 +192,4 @@ def set_appliance_params(self,train_appliances):
                 app_std = 100
             self.appliance_params.update({app_name:{'mean':app_mean,'std':app_std}})
         print (self.appliance_params)
-
+

nilmtk_contrib/disaggregate/seq2point.py

@@ -1,18 +1,18 @@
 from __future__ import print_function, division
 from warnings import warn
 from nilmtk.disaggregate import Disaggregator
-from keras.layers import Conv1D, Dense, Dropout, Reshape, Flatten
+from tensorflow.keras.layers import Conv1D, Dense, Dropout, Reshape, Flatten
 import os
 import pickle
 import pandas as pd
 import numpy as np
 from collections import OrderedDict
-from keras.optimizers import SGD
-from keras.models import Sequential, load_model
+from tensorflow.keras.optimizers import SGD
+from tensorflow.keras.models import Sequential, load_model
 import matplotlib.pyplot as plt
 from sklearn.model_selection import train_test_split
-from keras.callbacks import ModelCheckpoint
-import keras.backend as K
+from tensorflow.keras.callbacks import ModelCheckpoint
+import tensorflow.keras.backend as K
 import random
 import sys
 random.seed(10)
@@ -188,4 +188,4 @@ def set_appliance_params(self,train_appliances):
             if app_std<1:
                 app_std = 100
             self.appliance_params.update({app_name:{'mean':app_mean,'std':app_std}})
-        print (self.appliance_params)
+        print (self.appliance_params)

nilmtk_contrib/disaggregate/seq2seq.py

@@ -2,20 +2,20 @@
 from warnings import warn
 
 from nilmtk.disaggregate import Disaggregator
-from keras.layers import Conv1D, Dense, Dropout, Reshape, Flatten
+from tensorflow.keras.layers import Conv1D, Dense, Dropout, Reshape, Flatten
 
 import os
 import pandas as pd
 import numpy as np
 import pickle
 from collections import OrderedDict
 
-from keras.optimizers import SGD
-from keras.models import Sequential, load_model
+from tensorflow.keras.optimizers import SGD
+from tensorflow.keras.models import Sequential, load_model
 import matplotlib.pyplot as plt
 from sklearn.model_selection import train_test_split
-from keras.callbacks import ModelCheckpoint
-import keras.backend as K
+from tensorflow.keras.callbacks import ModelCheckpoint
+import tensorflow.keras.backend as K
 import random
 random.seed(10)
 np.random.seed(10)

setup.py

@@ -73,6 +73,7 @@ def write_version_py(filename=None):
     install_requires=[
         'nilmtk>=0.4',
         'keras>=2.2.4',
+        'tensorflow>=2.0',
         'cvxpy>=1.0.0'
     ],
     description="State-of-the-art algorithms for the task of energy disaggregation implemented using NILMTK's Rapid Experimentation API",