remove large keras import

BayesianCalibration_spm/cal_nosigma.py

@@ -3,11 +3,13 @@
 import os
 import sys
 
-import keras
 import numpy as np
 import tensorflow as tf
 import tf2jax
 from keras import layers
+from keras.backend import set_floatx
+
+set_floatx("float64")
 
 parser = argparse.ArgumentParser(description="BNN interface for pouch cells")
 parser.add_argument(

BayesianCalibration_spm/preprocess.py

@@ -41,12 +41,12 @@
 sys.path.append(args.utilFolder)
 
 import argument
-import keras
 import tensorflow as tf
 from keras import layers, regularizers
 from myNN import *
+from keras.backend import set_floatx
 
-keras.backend.set_floatx("float64")
+set_floatx("float64")
 
 # Read command line arguments
 args_spm = argument.initArg()

pinn_spm_param/postProcess/computeError.py

@@ -8,13 +8,13 @@
 from pathlib import Path
 
 import argument
-import keras
 import tensorflow as tf
 from keras import layers, regularizers
 from myNN import *
-from tensorflow import keras
+from keras.backend import set_floatx
+
+set_floatx("float64")
 
-keras.backend.set_floatx("float64")
 from forwardPass import (
     from_param_list_to_str,
     make_data_dict,

pinn_spm_param/postProcess/plotCorrelationPINNvsData.py

@@ -6,13 +6,13 @@
 
 sys.path.append("../util")
 import argument
-import keras
 import tensorflow as tf
 from keras import layers, regularizers
 from myNN import *
 from plotsUtil_batt import *
+from keras.backend import set_floatx
 
-keras.backend.set_floatx("float64")
+set_floatx("float64")
 
 from init_pinn import initialize_nn_from_params_config, safe_load
 

pinn_spm_param/postProcess/plotData.py

@@ -5,13 +5,13 @@
 
 sys.path.append("../util")
 import argument
-import keras
 import tensorflow as tf
 from keras import layers, regularizers
 from myNN import *
 from plotsUtil_batt import *
+from keras.backend import set_floatx
 
-keras.backend.set_floatx("float64")
+set_floatx("float64")
 
 print("\n\nINFO: PLOTTING DATA OBTAINED FROM FINITE DIFFERENCE\n\n")
 

pinn_spm_param/postProcess/plotPINNResult.py

@@ -6,7 +6,6 @@
 
 sys.path.append("../util")
 import argument
-import keras
 import tensorflow as tf
 from forwardPass import (
     from_param_list_to_str,
@@ -17,8 +16,9 @@
 from keras import layers, regularizers
 from myNN import *
 from plotsUtil_batt import *
+from keras.backend import set_floatx
 
-keras.backend.set_floatx("float64")
+set_floatx("float64")
 
 print("\n\nINFO: PLOTTING RESULTS OF THE PINN TRAINING\n\n")
 

pinn_spm_param/postProcess/plotPINNResult_movie.py

@@ -8,13 +8,13 @@
 from pathlib import Path
 
 import argument
-import keras
 import tensorflow as tf
 from keras import layers, regularizers
 from myNN import *
 from plotsUtil_batt import *
+from keras.backend import set_floatx
 
-keras.backend.set_floatx("float64")
+set_floatx("float64")
 
 from forwardPass import (
     from_param_list_to_str,

pinn_spm_param/util/_losses.py

@@ -1,10 +1,10 @@
 import argument
-import keras
 import numpy as np
 import tensorflow as tf
 from conditionalDecorator import conditional_decorator
+from keras.backend import set_floatx
 
-keras.backend.set_floatx("float64")
+set_floatx("float64")
 
 # Read command line arguments
 args = argument.initArg()

pinn_spm_param/util/_rescale.py

@@ -1,10 +1,10 @@
 import argument
-import keras
 import numpy as np
 import tensorflow as tf
 from conditionalDecorator import conditional_decorator
+from keras.backend import set_floatx
 
-keras.backend.set_floatx("float64")
+set_floatx("float64")
 
 # Read command line arguments
 args = argument.initArg()

pinn_spm_param/util/custom_activations.py

@@ -1,13 +1,12 @@
 import argument
-import keras
 import numpy as np
 import tensorflow as tf
 from conditionalDecorator import conditional_decorator
-from keras import backend as K
 from keras.layers import Activation
 from keras.utils import get_custom_objects
+from keras.backend import set_floatx
 
-keras.backend.set_floatx("float64")
+set_floatx("float64")
 
 # Read command line arguments
 args = argument.initArg()
@@ -24,7 +23,7 @@ def swish_activation(x):
     Swish activation - with beta not-traininable!
 
     """
-    return x * K.sigmoid(x)
+    return x * tf.math.sigmoid(x)
 
 
 class Bswish(keras.layers.Layer):

pinn_spm_param/util/forwardPass.py

@@ -5,12 +5,12 @@
 
 sys.path.append("../util")
 import argument
-import keras
 import tensorflow as tf
 from keras import layers, regularizers
 from myNN import *
+from keras.backend import set_floatx
 
-keras.backend.set_floatx("float64")
+set_floatx("float64")
 
 from init_pinn import initialize_nn_from_params_config
 

pinn_spm_param/util/init_pinn.py

@@ -516,7 +516,6 @@ def initialize_nn(args, input_params):
     )
 
     if not args.optimized:
-        import keras
         from keras.utils import plot_model
 
         try:

pinn_spm_param/util/myNN.py

@@ -4,7 +4,6 @@
 import time
 
 import argument
-import keras
 import numpy as np
 import tensorflow as tf
 from _losses import (
@@ -25,8 +24,9 @@
 from keras.layers import *
 from keras.models import Model
 from prettyPlot.progressBar import print_progress_bar
+from keras.backend import set_floatx
 
-keras.backend.set_floatx("float64")
+set_floatx("float64")
 
 # Read command line arguments
 args = argument.initArg()

pinn_spm_param/util/spm.py

@@ -1,11 +1,11 @@
 import sys
 
-import keras
 import numpy as np
 import tensorflow as tf
 from thermo import *
+from keras.backend import set_floatx
 
-keras.backend.set_floatx("float64")
+set_floatx("float64")
 
 print("INFO: USING REALISTIC SPM MODEL")
 

pinn_spm_param/util/spm_simpler.py

@@ -1,12 +1,12 @@
 import os
 import sys
 
-import keras
 import numpy as np
 import tensorflow as tf
 from thermo import *
+from keras.backend import set_floatx
 
-keras.backend.set_floatx("float64")
+set_floatx("float64")
 
 print("INFO: USING SIMPLE SPM MODEL")
 

pinn_spm_param/util/tf_lineInterp.py

@@ -19,11 +19,11 @@ def generateTFSpline(x, y, filename, funcname, precision="float64", mode="w+"):
     if mode == "w+":
         f.write("import argument\n")
         f.write("import numpy as np\n")
-        f.write("import keras\n")
         f.write("import tensorflow as tf\n")
         f.write("from conditionalDecorator import conditional_decorator\n")
+        f.write("from keras.backend import set_floatx\n")
         f.write("\n")
-        f.write(f'keras.backend.set_floatx("{precision}")\n')
+        f.write(f'set_floatx("{precision}")\n')
         f.write("\n")
         f.write("# Read command line arguments\n")
         f.write("args = argument.initArg()\n")
@@ -68,11 +68,11 @@ def generateTFPoly(coeffs, filename, funcname, precision="float64", mode="w+"):
     if mode == "w+":
         f.write("import argument\n")
         f.write("import numpy as np\n")
-        f.write("import keras\n")
         f.write("import tensorflow as tf\n")
         f.write("from conditionalDecorator import conditional_decorator\n")
+        f.write("from keras.backend import set_floatx\n")
         f.write("\n")
-        f.write(f'keras.backend.set_floatx("{precision}")\n')
+        f.write(f'set_floatx("{precision}")\n')
         f.write("\n")
         f.write("# Read command line arguments\n")
         f.write("args = argument.initArg()\n")

pinn_spm_param/util/thermo.py

@@ -1,11 +1,11 @@
 import sys
 
-import keras
 import numpy as np
 import tensorflow as tf
 from uocp_cs import uocp_a_fun_x, uocp_c_fun_x
+from keras.backend import set_floatx
 
-keras.backend.set_floatx("float64")
+set_floatx("float64")
 
 
 def uocp_a_simp(cs_a, csanmax):

pinn_spm_param/util/uocp_cs.py

@@ -1,10 +1,10 @@
 import argument
-import keras
 import numpy as np
 import tensorflow as tf
 from conditionalDecorator import conditional_decorator
+from keras.backend import set_floatx
 
-keras.backend.set_floatx("float64")
+set_floatx("float64")
 
 # Read command line arguments
 args = argument.initArg()