First commit

bigneurallife.py

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+#!/usr/bin/python
+# -*- coding: utf-8 -*- 
+
+__author__ = "Aleksey Lobanov"
+__copyright__ = "Copyright 2016, Aleksey Lobanov"
+__credits__ = ["Aleksey Lobanov"]
+__license__ = "MIT"
+__maintainer__ = "Aleksey Lobanov"
+__email__ = "i@likemath.ru"
+
+import sys
+from copy import deepcopy
+from datetime import datetime
+import logging
+
+import numpy as np
+
+from sklearn.cross_validation import train_test_split
+
+import keras
+from keras.models import Sequential
+from keras.layers import Dense, Dropout
+
+import matplotlib.pyplot as plt
+import matplotlib.cm as cm
+import matplotlib.patches as mpatches
+
+
+def initLogging():
+    logger = logging.getLogger()
+    logger.setLevel(logging.DEBUG)
+
+    formatter = logging.Formatter('%(asctime)s - %(levelname)s - %(message)s')
+    fh = logging.FileHandler('neurallife.log')
+    fh.setLevel(logging.DEBUG)
+    fh.setFormatter(formatter)
+    logger.addHandler(fh)
+    ch = logging.StreamHandler()
+    ch.setLevel(logging.DEBUG)
+    ch.setFormatter(formatter)
+    logger.addHandler(ch)
+
+
+def neighbors(field, i, j, fsize):
+    nsum = 0
+    for l in range(1, 10):
+        x = i - 1 + (l - 1) // 3
+        y = j - 1 + (l + 2) % 3
+        if -1 < x < fsize and -1 < y < fsize and field[x][y] == 1:
+            nsum += 1
+    nsum -= field[i][j]
+    return nsum
+
+
+def nextGen(field, fsize):
+    tmp_field = deepcopy(field)
+    for i in range(fsize):
+        for j in range(fsize):
+            neighb = neighbors(tmp_field, i, j, fsize)
+            if field[i][j] == 1 and not (2 <= neighb <= 3):
+                field[i][j] = 0
+            elif field[i][j] == 0 and neighb == 3:
+                field[i][j] = 1
+
+
+def uniqueRows(data):
+    uniq = np.unique(data.view(data.dtype.descr * data.shape[1]))
+    return uniq.view(data.dtype).reshape(-1, data.shape[1])
+
+
+def generateData(board_size, count=10**5):
+    assert(2**(board_size**2) >= count)
+    X = np.random.randint(2, size=(int(count*1.2),board_size*board_size))
+    X = uniqueRows(X)[:count]
+    Y = []
+    for row in X:
+        tmp_list = row.reshape((board_size,board_size)).tolist()
+        nextGen(tmp_list, board_size)
+        Y.append(tmp_list)
+    return (X, np.asarray(Y).reshape(X.shape))
+    
+
+def loadKeras(path):
+    model = keras.models.model_from_json(open(path + '.json').read())
+    model.load_weights(path + '.h5')
+    model.compile(loss='MSE', optimizer='nadam', metrics=[])
+
+    logging.debug("Keras model loaded from {}".format(path))
+    return model
+
+
+def saveKeras(model, path):
+    json_architecture = model.to_json()
+    json_path = path + '.json'
+    with open(json_path, 'w') as f:
+        f.write(json_architecture)
+    weights_path = path + '.h5'
+    model.save_weights(weights_path, overwrite=True)
+    
+
+def getModel(n):
+    nn = Sequential()
+    nn.add(Dense(8*n**2, input_dim=n**2, init="normal", activation="sigmoid"))
+    nn.add(Dense(5*n**2,init="normal", activation="sigmoid"))
+    nn.add(Dense(n**2,init="normal", activation="sigmoid"))
+    nn.compile(loss="MSE", optimizer="nadam", metrics=[])
+    return nn
+    
+    
+def getAccuracies(model,x_test,y_test):
+    preds = model.predict(x_test)
+    preds = np.rint(preds).astype("int")
+    acc_square = 1.0 * (preds == y_test).sum() / y_test.size
+    acc_boards = 0
+    for pred, real in zip(preds, y_test):
+        if (pred != real).sum() == 0:
+            acc_boards += 1
+    acc_boards = 1.0 * acc_boards / y_test.shape[0]
+    return (acc_square, acc_boards)
+
+
+
+META_PARAMETERS = {
+    9:[409600],
+}
+
+
+if __name__ == "__main__":
+    initLogging()
+
+    plt.title("Neural Life")
+
+    plt.xscale("log")
+
+    plt.xlabel("Train size")
+    plt.ylabel("Cell accuracy")
+
+    plt_patches = []
+    for meta_ind,N in enumerate(META_PARAMETERS):
+        points_x = []
+        points_y = []
+        for data_size in META_PARAMETERS[N]:
+            cur_time = datetime.now()        
+                    
+            X_train, X_test, Y_train, Y_test = train_test_split(
+                *generateData(N, data_size),  # X and Y
+                test_size=0.6,
+                random_state=23
+            )
+            
+            train_size = X_train.shape[0]
+            
+            nn = getModel(N)
+            
+            nn.fit(X_train, Y_train, nb_epoch=40, shuffle=False, verbose=1)
+        
+            cellAcc, boardAcc = getAccuracies(nn, X_test, Y_test)
+            
+            points_x.append(train_size)
+            points_y.append(cellAcc)
+            
+            logging.info(("BIG model: for board {}x{} with train size={} cell accuracy is {:.5f}%, " +
+            "board accuracy is {:.5f}% and delta with theoretical board accuracy " +
+            "is {:.8f}%  it takes {}").format(
+                N,
+                N,
+                train_size,
+                100 * cellAcc,
+                100 * boardAcc,
+                100 * abs(boardAcc - cellAcc**(N**2)),
+                datetime.now() - cur_time
+            ))
+            saveKeras(nn, "models/bigmodel_{}_{}".format(N,train_size))
+        plt.plot(points_x, points_y, "o", linestyle="-", color=cm.ocean(meta_ind/len(META_PARAMETERS)))
+        plt_patches.append(mpatches.Patch(color=cm.ocean(meta_ind/len(META_PARAMETERS)), label="N={}".format(N)))
+
+    plt.legend(handles=plt_patches)
+    plt.savefig("biggraphics.svg")

getconvolutional.py

@@ -0,0 +1,67 @@
+#!/usr/bin/python
+# -*- coding: utf-8 -*- 
+
+__author__ = "Aleksey Lobanov"
+__copyright__ = "Copyright 2016, Aleksey Lobanov"
+__credits__ = ["Aleksey Lobanov"]
+__license__ = "MIT"
+__maintainer__ = "Aleksey Lobanov"
+__email__ = "i@likemath.ru"
+
+from datetime import datetime
+
+from keras.models import Sequential
+from keras.layers import Dense, Dropout, Activation, Flatten
+from keras.layers import Convolution2D
+
+import numpy as np
+
+from sklearn.cross_validation import train_test_split
+
+from neurallife import generateData, getAccuracies, saveKeras
+
+
+def getModel(n):
+    nn = Sequential()
+    nn.add(Convolution2D(64, 3, 3, border_mode='same', input_shape=(1, n, n)))
+    nn.add(Activation('relu'))
+    nn.add(Dropout(0.25))
+    nn.add(Flatten())
+    nn.add(Dense(4*n**2,init="normal", activation="sigmoid"))
+    nn.add(Dropout(0.15))
+    nn.add(Dense(n**2,init="normal", activation="sigmoid"))
+    nn.compile(loss="MSE", optimizer="nadam", metrics=[])
+    return nn
+
+N = 9  # board size
+
+if __name__ == "__main__":
+
+    X_train, X_test, Y_train, Y_test = train_test_split(
+        *generateData(N, 2*10**5),
+        test_size=0.5,
+        random_state=23
+    )
+    X_train = X_train.reshape((X_train.shape[0], 1, N, N))
+    X_test = X_test.reshape((X_test.shape[0], 1, N, N))
+    
+    nn = getModel(N)
+    
+    cur_time = datetime.now()
+    
+    nn.fit(X_train, Y_train, nb_epoch=20, shuffle=False, verbose=1)
+    
+    cellAcc, boardAcc = getAccuracies(nn, X_test, Y_test)
+    
+    print(("for board {}x{} with train size={} cell accuracy is {:.5f}%, " +
+    "board accuracy is {:.5f}% and delta with theoretical board accuracy " +
+    "is {:.8f}%  it takes {}").format(
+        N,
+        N,
+        X_train.shape[0],
+        100 * cellAcc,
+        100 * boardAcc,
+        100 * abs(boardAcc - cellAcc**(N**2)),
+        datetime.now() - cur_time
+    ))
+    saveKeras(nn, "models/convolutional_{}_{}".format(N, X_train.shape[0]))

gifcreator.py

@@ -0,0 +1,157 @@
+#!/usr/bin/python
+# -*- coding: utf-8 -*- 
+
+__author__ = "Aleksey Lobanov"
+__copyright__ = "Copyright 2016, Aleksey Lobanov"
+__credits__ = ["Aleksey Lobanov"]
+__license__ = "MIT"
+__maintainer__ = "Aleksey Lobanov"
+__email__ = "i@likemath.ru"
+
+import sys
+from copy import deepcopy
+
+import numpy as np
+
+import keras
+from keras.models import Sequential
+from keras.layers import Dense
+
+import imageio  # for gifs
+
+from PIL import Image, ImageDraw
+
+from neurallife import nextGen
+
+
+"""
+# from original article
+start_pos = [
+    [0,0,0,0,1,0,1,0,0],
+    [0,1,0,0,1,0,0,1,0],
+    [0,1,1,0,1,1,0,1,0],
+    [1,0,0,1,1,0,0,0,0],
+    [0,1,1,1,0,1,0,1,0],
+    [0,0,1,0,1,0,0,0,0],
+    [0,0,1,1,0,0,1,0,0],
+    [0,1,1,0,1,1,0,0,0],
+    [0,0,0,0,0,0,0,0,0]
+]
+"""
+
+# about 27 original positions
+start_pos = [
+    [0, 0, 0, 0, 0, 0, 0, 1, 0],
+    [0, 0, 0, 0, 0, 0, 1, 1, 0],
+    [0, 0, 1, 0, 0, 1, 1, 1, 0],
+    [1, 0, 1, 0, 1, 0, 0, 0, 0],
+    [1, 0, 1, 0, 1, 1, 0, 0, 0],
+    [0, 1, 0, 0, 0, 0, 0, 0, 0],
+    [0, 0, 0, 0, 0, 0, 0, 0, 0],
+    [0, 0, 0, 0, 0, 1, 0, 0, 0],
+    [0, 0, 0, 0, 0, 1, 1, 0, 0]
+]
+
+
+"""
+Code for good, long start positions:
+
+def getBest(max_cnt):
+    cur_max = 0
+    cur_best = None
+    for i in range(max_cnt):
+        cur_field = np.random.randint(2, size=(9,9)).tolist()
+        cur_cnt = getCnt(cur_field)
+        if cur_cnt > cur_max:
+            cur_max = getCnt(cur_field, 200)
+            cur_best = cur_field
+    return (cur_best,cur_max)
+
+
+def getCnt(pos, max_cnt=100):
+    cnt = 0
+    ker_pred = pos
+    cur_pos = pos
+    while True:
+        cnt += 1
+        ker_pred = nn.predict(np.asarray(ker_pred).reshape((1,1,9,9)))
+        ker_pred = np.rint(ker_pred).astype("int").reshape((9,9)).tolist()
+
+        old_cur_pos = deepcopy(cur_pos)
+        next_gen(cur_pos, len(cur_pos))
+        if np.asarray(old_cur_pos).sum() == np.asarray(cur_pos).sum():
+            break
+        if ker_pred != cur_pos:
+            break
+        if cnt > max_cnt:
+            return 0
+    return cnt
+"""
+
+LINE_SIZE = 2
+SQUARE_SIZE = 18
+FRAME_COUNT = 30
+FRAME_DELAY = 0.3  # in seconds
+
+
+def loadKeras(path):
+    model = keras.models.model_from_json(open(path + '.json').read())
+    model.load_weights(path + '.h5')
+    model.compile(loss='MSE', optimizer='nadam', metrics=[ ])
+    return model
+
+
+def imageFromList(l):
+    global LINE_SIZE, SQUARE_SIZE
+    height = LINE_SIZE * (len(l) + 1) + SQUARE_SIZE * len(l)  # =height
+    width = LINE_SIZE * (len(l[0]) + 1) + SQUARE_SIZE * len(l[0])
+    tmp_img = Image.new('RGB', (width, height), (0, 0, 0))
+    pil_draw = ImageDraw.Draw(tmp_img)
+    for y in range(len(l)):
+        for x in range(len(l[0])):
+            if l[y][x] == 0:
+                pil_draw.rectangle((
+                    x * (LINE_SIZE + SQUARE_SIZE) + LINE_SIZE,
+                    y * (LINE_SIZE + SQUARE_SIZE) + LINE_SIZE,
+                    (x + 1) * (LINE_SIZE + SQUARE_SIZE)-1,
+                    (y + 1) * (LINE_SIZE + SQUARE_SIZE)-1,
+                ), fill=(255, 255, 255))
+    return tmp_img
+
+N = 9  # board size
+
+if __name__ == '__main__':
+    nn = loadKeras(sys.argv[1])
+    nn_frames = []
+    real_frames = []
+    ker_pred = cur_pos = start_pos
+    
+    for i in range(FRAME_COUNT):
+        #ker_pred = cur_pos
+        
+        nn_frames.append(imageFromList(ker_pred))
+        ker_pred = nn.predict(np.asarray(ker_pred).reshape((1, N**2)))
+        ker_pred = np.rint(ker_pred).astype("int").reshape((N, N)).tolist()
+        
+        real_frames.append(imageFromList(cur_pos))
+        old_pos = deepcopy(cur_pos)
+        nextGen(cur_pos, len(start_pos))
+        
+        # because need some pause at end
+        #if cur_pos == old_pos:
+        #    break
+    width, height = nn_frames[0].size
+    
+    imageio.mimsave(
+        'gif_neural.gif',
+        [np.asarray(img.getdata()).reshape((width, height, 3)) for img in nn_frames],
+        fps=1/FRAME_DELAY
+        )
+    imageio.mimsave(
+        'gif_real.gif',
+        [np.asarray(img.getdata()).reshape((width, height, 3)) for img in real_frames],
+        fps=1/FRAME_DELAY
+        )
+
+    
+

models/bigmodel_9_163840.json

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+{"keras_version": "1.0.5", "sample_weight_mode": null, "class_name": "Sequential", "optimizer": {"name": "Nadam", "beta_1": 0.8999999761581421, "beta_2": 0.9990000128746033, "lr": 0.0020000000949949026, "epsilon": 1e-08, "schedule_decay": 0.004}, "loss": "MSE", "config": [{"class_name": "Dense", "config": {"init": "normal", "b_constraint": null, "input_dim": 81, "trainable": true, "batch_input_shape": [null, 81], "W_regularizer": null, "b_regularizer": null, "W_constraint": null, "name": "dense_1", "activation": "sigmoid", "input_dtype": "float32", "output_dim": 648, "bias": true, "activity_regularizer": null}}, {"class_name": "Dense", "config": {"init": "normal", "b_constraint": null, "input_dim": null, "trainable": true, "b_regularizer": null, "W_regularizer": null, "W_constraint": null, "name": "dense_2", "activation": "sigmoid", "output_dim": 405, "bias": true, "activity_regularizer": null}}, {"class_name": "Dense", "config": {"init": "normal", "b_constraint": null, "input_dim": null, "trainable": true, "b_regularizer": null, "W_regularizer": null, "W_constraint": null, "name": "dense_3", "activation": "sigmoid", "output_dim": 81, "bias": true, "activity_regularizer": null}}]}

models/convolution_8_51200.json

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+{"config": [{"class_name": "Convolution2D", "config": {"W_regularizer": null, "nb_row": 3, "name": "convolution2d_6", "input_dtype": "float32", "b_regularizer": null, "nb_col": 3, "trainable": true, "subsample": [1, 1], "bias": true, "W_constraint": null, "border_mode": "same", "activity_regularizer": null, "b_constraint": null, "activation": "linear", "batch_input_shape": [null, 1, 8, 8], "init": "glorot_uniform", "nb_filter": 40, "dim_ordering": "th"}}, {"class_name": "Activation", "config": {"activation": "relu", "trainable": true, "name": "activation_4"}}, {"class_name": "Dropout", "config": {"p": 0.25, "trainable": true, "name": "dropout_4"}}, {"class_name": "Flatten", "config": {"trainable": true, "name": "flatten_5"}}, {"class_name": "Dense", "config": {"input_dim": null, "W_regularizer": null, "output_dim": 256, "name": "dense_6", "b_regularizer": null, "trainable": true, "bias": true, "W_constraint": null, "init": "normal", "activity_regularizer": null, "activation": "sigmoid", "b_constraint": null}}, {"class_name": "Dense", "config": {"input_dim": null, "W_regularizer": null, "output_dim": 64, "name": "dense_7", "b_regularizer": null, "trainable": true, "bias": true, "W_constraint": null, "init": "normal", "activity_regularizer": null, "activation": "sigmoid", "b_constraint": null}}], "sample_weight_mode": null, "loss": "MSE", "class_name": "Sequential", "keras_version": "1.0.5", "optimizer": {"lr": 0.0020000000949949026, "name": "Nadam", "beta_1": 0.8999999761581421, "epsilon": 1e-08, "beta_2": 0.9990000128746033, "schedule_decay": 0.004}}

models/convolutional_9_100000.json

@@ -0,0 +1 @@
+{"optimizer": {"epsilon": 1e-08, "beta_1": 0.8999999761581421, "lr": 0.0020000000949949026, "name": "Nadam", "schedule_decay": 0.004, "beta_2": 0.9990000128746033}, "class_name": "Sequential", "keras_version": "1.0.5", "loss": "MSE", "sample_weight_mode": null, "config": [{"class_name": "Convolution2D", "config": {"batch_input_shape": [null, 1, 9, 9], "bias": true, "init": "glorot_uniform", "nb_row": 3, "W_constraint": null, "name": "convolution2d_1", "b_constraint": null, "activity_regularizer": null, "b_regularizer": null, "activation": "linear", "nb_col": 3, "trainable": true, "nb_filter": 64, "W_regularizer": null, "subsample": [1, 1], "input_dtype": "float32", "border_mode": "same", "dim_ordering": "th"}}, {"class_name": "Activation", "config": {"activation": "relu", "name": "activation_1", "trainable": true}}, {"class_name": "Dropout", "config": {"name": "dropout_1", "p": 0.25, "trainable": true}}, {"class_name": "Flatten", "config": {"name": "flatten_1", "trainable": true}}, {"class_name": "Dense", "config": {"bias": true, "init": "normal", "b_regularizer": null, "name": "dense_1", "b_constraint": null, "activity_regularizer": null, "W_constraint": null, "activation": "sigmoid", "input_dim": null, "trainable": true, "W_regularizer": null, "output_dim": 324}}, {"class_name": "Dropout", "config": {"name": "dropout_2", "p": 0.15, "trainable": true}}, {"class_name": "Dense", "config": {"bias": true, "init": "normal", "b_regularizer": null, "name": "dense_2", "b_constraint": null, "activity_regularizer": null, "W_constraint": null, "activation": "sigmoid", "input_dim": null, "trainable": true, "W_regularizer": null, "output_dim": 81}}]}

models/model_10_12800.json

@@ -0,0 +1 @@
+{"config": [{"class_name": "Dense", "config": {"name": "dense_43", "b_regularizer": null, "input_dtype": "float32", "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": 100, "activation": "sigmoid", "W_constraint": null, "batch_input_shape": [null, 100], "bias": true, "activity_regularizer": null, "output_dim": 400, "trainable": true}}, {"class_name": "Dense", "config": {"name": "dense_44", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 400}}, {"class_name": "Dense", "config": {"name": "dense_45", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 100}}], "sample_weight_mode": null, "keras_version": "1.0.5", "optimizer": {"name": "Nadam", "epsilon": 1e-08, "beta_2": 0.9990000128746033, "schedule_decay": 0.004, "beta_1": 0.8999999761581421, "lr": 0.0020000000949949026}, "class_name": "Sequential", "loss": "MSE"}

models/model_10_204800.json

@@ -0,0 +1 @@
+{"config": [{"class_name": "Dense", "config": {"name": "dense_49", "b_regularizer": null, "input_dtype": "float32", "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": 100, "activation": "sigmoid", "W_constraint": null, "batch_input_shape": [null, 100], "bias": true, "activity_regularizer": null, "output_dim": 400, "trainable": true}}, {"class_name": "Dense", "config": {"name": "dense_50", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 400}}, {"class_name": "Dense", "config": {"name": "dense_51", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 100}}], "sample_weight_mode": null, "keras_version": "1.0.5", "optimizer": {"name": "Nadam", "epsilon": 1e-08, "beta_2": 0.9990000128746033, "schedule_decay": 0.004, "beta_1": 0.8999999761581421, "lr": 0.0020000000949949026}, "class_name": "Sequential", "loss": "MSE"}

models/model_10_3200.json

@@ -0,0 +1 @@
+{"config": [{"class_name": "Dense", "config": {"name": "dense_40", "b_regularizer": null, "input_dtype": "float32", "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": 100, "activation": "sigmoid", "W_constraint": null, "batch_input_shape": [null, 100], "bias": true, "activity_regularizer": null, "output_dim": 400, "trainable": true}}, {"class_name": "Dense", "config": {"name": "dense_41", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 400}}, {"class_name": "Dense", "config": {"name": "dense_42", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 100}}], "sample_weight_mode": null, "keras_version": "1.0.5", "optimizer": {"name": "Nadam", "epsilon": 1e-08, "beta_2": 0.9990000128746033, "schedule_decay": 0.004, "beta_1": 0.8999999761581421, "lr": 0.0020000000949949026}, "class_name": "Sequential", "loss": "MSE"}

models/model_10_51200.json

@@ -0,0 +1 @@
+{"config": [{"class_name": "Dense", "config": {"name": "dense_46", "b_regularizer": null, "input_dtype": "float32", "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": 100, "activation": "sigmoid", "W_constraint": null, "batch_input_shape": [null, 100], "bias": true, "activity_regularizer": null, "output_dim": 400, "trainable": true}}, {"class_name": "Dense", "config": {"name": "dense_47", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 400}}, {"class_name": "Dense", "config": {"name": "dense_48", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 100}}], "sample_weight_mode": null, "keras_version": "1.0.5", "optimizer": {"name": "Nadam", "epsilon": 1e-08, "beta_2": 0.9990000128746033, "schedule_decay": 0.004, "beta_1": 0.8999999761581421, "lr": 0.0020000000949949026}, "class_name": "Sequential", "loss": "MSE"}

models/model_10_800.json

@@ -0,0 +1 @@
+{"config": [{"class_name": "Dense", "config": {"name": "dense_37", "b_regularizer": null, "input_dtype": "float32", "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": 100, "activation": "sigmoid", "W_constraint": null, "batch_input_shape": [null, 100], "bias": true, "activity_regularizer": null, "output_dim": 400, "trainable": true}}, {"class_name": "Dense", "config": {"name": "dense_38", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 400}}, {"class_name": "Dense", "config": {"name": "dense_39", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 100}}], "sample_weight_mode": null, "keras_version": "1.0.5", "optimizer": {"name": "Nadam", "epsilon": 1e-08, "beta_2": 0.9990000128746033, "schedule_decay": 0.004, "beta_1": 0.8999999761581421, "lr": 0.0020000000949949026}, "class_name": "Sequential", "loss": "MSE"}

models/model_10_819200.json

@@ -0,0 +1 @@
+{"config": [{"class_name": "Dense", "config": {"name": "dense_52", "b_regularizer": null, "input_dtype": "float32", "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": 100, "activation": "sigmoid", "W_constraint": null, "batch_input_shape": [null, 100], "bias": true, "activity_regularizer": null, "output_dim": 400, "trainable": true}}, {"class_name": "Dense", "config": {"name": "dense_53", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 400}}, {"class_name": "Dense", "config": {"name": "dense_54", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 100}}], "sample_weight_mode": null, "keras_version": "1.0.5", "optimizer": {"name": "Nadam", "epsilon": 1e-08, "beta_2": 0.9990000128746033, "schedule_decay": 0.004, "beta_1": 0.8999999761581421, "lr": 0.0020000000949949026}, "class_name": "Sequential", "loss": "MSE"}

models/model_5_12800.json

@@ -0,0 +1 @@
+{"config": [{"class_name": "Dense", "config": {"name": "dense_61", "b_regularizer": null, "input_dtype": "float32", "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": 25, "activation": "sigmoid", "W_constraint": null, "batch_input_shape": [null, 25], "bias": true, "activity_regularizer": null, "output_dim": 100, "trainable": true}}, {"class_name": "Dense", "config": {"name": "dense_62", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 100}}, {"class_name": "Dense", "config": {"name": "dense_63", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 25}}], "sample_weight_mode": null, "keras_version": "1.0.5", "optimizer": {"name": "Nadam", "epsilon": 1e-08, "beta_2": 0.9990000128746033, "schedule_decay": 0.004, "beta_1": 0.8999999761581421, "lr": 0.0020000000949949026}, "class_name": "Sequential", "loss": "MSE"}

models/model_5_204800.json

@@ -0,0 +1 @@
+{"config": [{"class_name": "Dense", "config": {"name": "dense_67", "b_regularizer": null, "input_dtype": "float32", "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": 25, "activation": "sigmoid", "W_constraint": null, "batch_input_shape": [null, 25], "bias": true, "activity_regularizer": null, "output_dim": 100, "trainable": true}}, {"class_name": "Dense", "config": {"name": "dense_68", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 100}}, {"class_name": "Dense", "config": {"name": "dense_69", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 25}}], "sample_weight_mode": null, "keras_version": "1.0.5", "optimizer": {"name": "Nadam", "epsilon": 1e-08, "beta_2": 0.9990000128746033, "schedule_decay": 0.004, "beta_1": 0.8999999761581421, "lr": 0.0020000000949949026}, "class_name": "Sequential", "loss": "MSE"}

models/model_5_3200.json

@@ -0,0 +1 @@
+{"config": [{"class_name": "Dense", "config": {"name": "dense_58", "b_regularizer": null, "input_dtype": "float32", "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": 25, "activation": "sigmoid", "W_constraint": null, "batch_input_shape": [null, 25], "bias": true, "activity_regularizer": null, "output_dim": 100, "trainable": true}}, {"class_name": "Dense", "config": {"name": "dense_59", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 100}}, {"class_name": "Dense", "config": {"name": "dense_60", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 25}}], "sample_weight_mode": null, "keras_version": "1.0.5", "optimizer": {"name": "Nadam", "epsilon": 1e-08, "beta_2": 0.9990000128746033, "schedule_decay": 0.004, "beta_1": 0.8999999761581421, "lr": 0.0020000000949949026}, "class_name": "Sequential", "loss": "MSE"}

models/model_5_51200.json

@@ -0,0 +1 @@
+{"config": [{"class_name": "Dense", "config": {"name": "dense_64", "b_regularizer": null, "input_dtype": "float32", "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": 25, "activation": "sigmoid", "W_constraint": null, "batch_input_shape": [null, 25], "bias": true, "activity_regularizer": null, "output_dim": 100, "trainable": true}}, {"class_name": "Dense", "config": {"name": "dense_65", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 100}}, {"class_name": "Dense", "config": {"name": "dense_66", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 25}}], "sample_weight_mode": null, "keras_version": "1.0.5", "optimizer": {"name": "Nadam", "epsilon": 1e-08, "beta_2": 0.9990000128746033, "schedule_decay": 0.004, "beta_1": 0.8999999761581421, "lr": 0.0020000000949949026}, "class_name": "Sequential", "loss": "MSE"}

models/model_5_800.json

@@ -0,0 +1 @@
+{"config": [{"class_name": "Dense", "config": {"name": "dense_55", "b_regularizer": null, "input_dtype": "float32", "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": 25, "activation": "sigmoid", "W_constraint": null, "batch_input_shape": [null, 25], "bias": true, "activity_regularizer": null, "output_dim": 100, "trainable": true}}, {"class_name": "Dense", "config": {"name": "dense_56", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 100}}, {"class_name": "Dense", "config": {"name": "dense_57", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 25}}], "sample_weight_mode": null, "keras_version": "1.0.5", "optimizer": {"name": "Nadam", "epsilon": 1e-08, "beta_2": 0.9990000128746033, "schedule_decay": 0.004, "beta_1": 0.8999999761581421, "lr": 0.0020000000949949026}, "class_name": "Sequential", "loss": "MSE"}

models/model_5_819200.json

@@ -0,0 +1 @@
+{"config": [{"class_name": "Dense", "config": {"name": "dense_70", "b_regularizer": null, "input_dtype": "float32", "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": 25, "activation": "sigmoid", "W_constraint": null, "batch_input_shape": [null, 25], "bias": true, "activity_regularizer": null, "output_dim": 100, "trainable": true}}, {"class_name": "Dense", "config": {"name": "dense_71", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 100}}, {"class_name": "Dense", "config": {"name": "dense_72", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 25}}], "sample_weight_mode": null, "keras_version": "1.0.5", "optimizer": {"name": "Nadam", "epsilon": 1e-08, "beta_2": 0.9990000128746033, "schedule_decay": 0.004, "beta_1": 0.8999999761581421, "lr": 0.0020000000949949026}, "class_name": "Sequential", "loss": "MSE"}

models/model_6_12800.json

@@ -0,0 +1 @@
+{"config": [{"class_name": "Dense", "config": {"name": "dense_79", "b_regularizer": null, "input_dtype": "float32", "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": 36, "activation": "sigmoid", "W_constraint": null, "batch_input_shape": [null, 36], "bias": true, "activity_regularizer": null, "output_dim": 144, "trainable": true}}, {"class_name": "Dense", "config": {"name": "dense_80", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 144}}, {"class_name": "Dense", "config": {"name": "dense_81", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 36}}], "sample_weight_mode": null, "keras_version": "1.0.5", "optimizer": {"name": "Nadam", "epsilon": 1e-08, "beta_2": 0.9990000128746033, "schedule_decay": 0.004, "beta_1": 0.8999999761581421, "lr": 0.0020000000949949026}, "class_name": "Sequential", "loss": "MSE"}

models/model_6_204800.json

@@ -0,0 +1 @@
+{"config": [{"class_name": "Dense", "config": {"name": "dense_85", "b_regularizer": null, "input_dtype": "float32", "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": 36, "activation": "sigmoid", "W_constraint": null, "batch_input_shape": [null, 36], "bias": true, "activity_regularizer": null, "output_dim": 144, "trainable": true}}, {"class_name": "Dense", "config": {"name": "dense_86", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 144}}, {"class_name": "Dense", "config": {"name": "dense_87", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 36}}], "sample_weight_mode": null, "keras_version": "1.0.5", "optimizer": {"name": "Nadam", "epsilon": 1e-08, "beta_2": 0.9990000128746033, "schedule_decay": 0.004, "beta_1": 0.8999999761581421, "lr": 0.0020000000949949026}, "class_name": "Sequential", "loss": "MSE"}

models/model_6_3200.json

@@ -0,0 +1 @@
+{"config": [{"class_name": "Dense", "config": {"name": "dense_76", "b_regularizer": null, "input_dtype": "float32", "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": 36, "activation": "sigmoid", "W_constraint": null, "batch_input_shape": [null, 36], "bias": true, "activity_regularizer": null, "output_dim": 144, "trainable": true}}, {"class_name": "Dense", "config": {"name": "dense_77", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 144}}, {"class_name": "Dense", "config": {"name": "dense_78", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 36}}], "sample_weight_mode": null, "keras_version": "1.0.5", "optimizer": {"name": "Nadam", "epsilon": 1e-08, "beta_2": 0.9990000128746033, "schedule_decay": 0.004, "beta_1": 0.8999999761581421, "lr": 0.0020000000949949026}, "class_name": "Sequential", "loss": "MSE"}

models/model_6_51200.json

@@ -0,0 +1 @@
+{"config": [{"class_name": "Dense", "config": {"name": "dense_82", "b_regularizer": null, "input_dtype": "float32", "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": 36, "activation": "sigmoid", "W_constraint": null, "batch_input_shape": [null, 36], "bias": true, "activity_regularizer": null, "output_dim": 144, "trainable": true}}, {"class_name": "Dense", "config": {"name": "dense_83", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 144}}, {"class_name": "Dense", "config": {"name": "dense_84", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 36}}], "sample_weight_mode": null, "keras_version": "1.0.5", "optimizer": {"name": "Nadam", "epsilon": 1e-08, "beta_2": 0.9990000128746033, "schedule_decay": 0.004, "beta_1": 0.8999999761581421, "lr": 0.0020000000949949026}, "class_name": "Sequential", "loss": "MSE"}

models/model_6_800.json

@@ -0,0 +1 @@
+{"config": [{"class_name": "Dense", "config": {"name": "dense_73", "b_regularizer": null, "input_dtype": "float32", "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": 36, "activation": "sigmoid", "W_constraint": null, "batch_input_shape": [null, 36], "bias": true, "activity_regularizer": null, "output_dim": 144, "trainable": true}}, {"class_name": "Dense", "config": {"name": "dense_74", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 144}}, {"class_name": "Dense", "config": {"name": "dense_75", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 36}}], "sample_weight_mode": null, "keras_version": "1.0.5", "optimizer": {"name": "Nadam", "epsilon": 1e-08, "beta_2": 0.9990000128746033, "schedule_decay": 0.004, "beta_1": 0.8999999761581421, "lr": 0.0020000000949949026}, "class_name": "Sequential", "loss": "MSE"}

models/model_6_819200.json

@@ -0,0 +1 @@
+{"config": [{"class_name": "Dense", "config": {"name": "dense_88", "b_regularizer": null, "input_dtype": "float32", "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": 36, "activation": "sigmoid", "W_constraint": null, "batch_input_shape": [null, 36], "bias": true, "activity_regularizer": null, "output_dim": 144, "trainable": true}}, {"class_name": "Dense", "config": {"name": "dense_89", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 144}}, {"class_name": "Dense", "config": {"name": "dense_90", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 36}}], "sample_weight_mode": null, "keras_version": "1.0.5", "optimizer": {"name": "Nadam", "epsilon": 1e-08, "beta_2": 0.9990000128746033, "schedule_decay": 0.004, "beta_1": 0.8999999761581421, "lr": 0.0020000000949949026}, "class_name": "Sequential", "loss": "MSE"}

models/model_8_12800.json

@@ -0,0 +1 @@
+{"config": [{"class_name": "Dense", "config": {"name": "dense_7", "b_regularizer": null, "input_dtype": "float32", "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": 64, "activation": "sigmoid", "W_constraint": null, "batch_input_shape": [null, 64], "bias": true, "activity_regularizer": null, "output_dim": 256, "trainable": true}}, {"class_name": "Dense", "config": {"name": "dense_8", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 256}}, {"class_name": "Dense", "config": {"name": "dense_9", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 64}}], "sample_weight_mode": null, "keras_version": "1.0.5", "optimizer": {"name": "Nadam", "epsilon": 1e-08, "beta_2": 0.9990000128746033, "schedule_decay": 0.004, "beta_1": 0.8999999761581421, "lr": 0.0020000000949949026}, "class_name": "Sequential", "loss": "MSE"}

models/model_8_204800.json

@@ -0,0 +1 @@
+{"config": [{"class_name": "Dense", "config": {"name": "dense_13", "b_regularizer": null, "input_dtype": "float32", "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": 64, "activation": "sigmoid", "W_constraint": null, "batch_input_shape": [null, 64], "bias": true, "activity_regularizer": null, "output_dim": 256, "trainable": true}}, {"class_name": "Dense", "config": {"name": "dense_14", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 256}}, {"class_name": "Dense", "config": {"name": "dense_15", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 64}}], "sample_weight_mode": null, "keras_version": "1.0.5", "optimizer": {"name": "Nadam", "epsilon": 1e-08, "beta_2": 0.9990000128746033, "schedule_decay": 0.004, "beta_1": 0.8999999761581421, "lr": 0.0020000000949949026}, "class_name": "Sequential", "loss": "MSE"}

models/model_8_3200.json

@@ -0,0 +1 @@
+{"config": [{"class_name": "Dense", "config": {"name": "dense_4", "b_regularizer": null, "input_dtype": "float32", "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": 64, "activation": "sigmoid", "W_constraint": null, "batch_input_shape": [null, 64], "bias": true, "activity_regularizer": null, "output_dim": 256, "trainable": true}}, {"class_name": "Dense", "config": {"name": "dense_5", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 256}}, {"class_name": "Dense", "config": {"name": "dense_6", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 64}}], "sample_weight_mode": null, "keras_version": "1.0.5", "optimizer": {"name": "Nadam", "epsilon": 1e-08, "beta_2": 0.9990000128746033, "schedule_decay": 0.004, "beta_1": 0.8999999761581421, "lr": 0.0020000000949949026}, "class_name": "Sequential", "loss": "MSE"}

models/model_8_51200.json

@@ -0,0 +1 @@
+{"config": [{"class_name": "Dense", "config": {"name": "dense_10", "b_regularizer": null, "input_dtype": "float32", "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": 64, "activation": "sigmoid", "W_constraint": null, "batch_input_shape": [null, 64], "bias": true, "activity_regularizer": null, "output_dim": 256, "trainable": true}}, {"class_name": "Dense", "config": {"name": "dense_11", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 256}}, {"class_name": "Dense", "config": {"name": "dense_12", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 64}}], "sample_weight_mode": null, "keras_version": "1.0.5", "optimizer": {"name": "Nadam", "epsilon": 1e-08, "beta_2": 0.9990000128746033, "schedule_decay": 0.004, "beta_1": 0.8999999761581421, "lr": 0.0020000000949949026}, "class_name": "Sequential", "loss": "MSE"}

models/model_8_800.json

@@ -0,0 +1 @@
+{"config": [{"class_name": "Dense", "config": {"name": "dense_1", "b_regularizer": null, "input_dtype": "float32", "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": 64, "activation": "sigmoid", "W_constraint": null, "batch_input_shape": [null, 64], "bias": true, "activity_regularizer": null, "output_dim": 256, "trainable": true}}, {"class_name": "Dense", "config": {"name": "dense_2", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 256}}, {"class_name": "Dense", "config": {"name": "dense_3", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 64}}], "sample_weight_mode": null, "keras_version": "1.0.5", "optimizer": {"name": "Nadam", "epsilon": 1e-08, "beta_2": 0.9990000128746033, "schedule_decay": 0.004, "beta_1": 0.8999999761581421, "lr": 0.0020000000949949026}, "class_name": "Sequential", "loss": "MSE"}

models/model_8_819200.json

@@ -0,0 +1 @@
+{"config": [{"class_name": "Dense", "config": {"name": "dense_16", "b_regularizer": null, "input_dtype": "float32", "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": 64, "activation": "sigmoid", "W_constraint": null, "batch_input_shape": [null, 64], "bias": true, "activity_regularizer": null, "output_dim": 256, "trainable": true}}, {"class_name": "Dense", "config": {"name": "dense_17", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 256}}, {"class_name": "Dense", "config": {"name": "dense_18", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 64}}], "sample_weight_mode": null, "keras_version": "1.0.5", "optimizer": {"name": "Nadam", "epsilon": 1e-08, "beta_2": 0.9990000128746033, "schedule_decay": 0.004, "beta_1": 0.8999999761581421, "lr": 0.0020000000949949026}, "class_name": "Sequential", "loss": "MSE"}

models/model_9_12800.json

@@ -0,0 +1 @@
+{"config": [{"class_name": "Dense", "config": {"name": "dense_25", "b_regularizer": null, "input_dtype": "float32", "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": 81, "activation": "sigmoid", "W_constraint": null, "batch_input_shape": [null, 81], "bias": true, "activity_regularizer": null, "output_dim": 324, "trainable": true}}, {"class_name": "Dense", "config": {"name": "dense_26", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 324}}, {"class_name": "Dense", "config": {"name": "dense_27", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 81}}], "sample_weight_mode": null, "keras_version": "1.0.5", "optimizer": {"name": "Nadam", "epsilon": 1e-08, "beta_2": 0.9990000128746033, "schedule_decay": 0.004, "beta_1": 0.8999999761581421, "lr": 0.0020000000949949026}, "class_name": "Sequential", "loss": "MSE"}

models/model_9_204800.json

@@ -0,0 +1 @@
+{"config": [{"class_name": "Dense", "config": {"name": "dense_31", "b_regularizer": null, "input_dtype": "float32", "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": 81, "activation": "sigmoid", "W_constraint": null, "batch_input_shape": [null, 81], "bias": true, "activity_regularizer": null, "output_dim": 324, "trainable": true}}, {"class_name": "Dense", "config": {"name": "dense_32", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 324}}, {"class_name": "Dense", "config": {"name": "dense_33", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 81}}], "sample_weight_mode": null, "keras_version": "1.0.5", "optimizer": {"name": "Nadam", "epsilon": 1e-08, "beta_2": 0.9990000128746033, "schedule_decay": 0.004, "beta_1": 0.8999999761581421, "lr": 0.0020000000949949026}, "class_name": "Sequential", "loss": "MSE"}

models/model_9_3200.json

@@ -0,0 +1 @@
+{"config": [{"class_name": "Dense", "config": {"name": "dense_22", "b_regularizer": null, "input_dtype": "float32", "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": 81, "activation": "sigmoid", "W_constraint": null, "batch_input_shape": [null, 81], "bias": true, "activity_regularizer": null, "output_dim": 324, "trainable": true}}, {"class_name": "Dense", "config": {"name": "dense_23", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 324}}, {"class_name": "Dense", "config": {"name": "dense_24", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 81}}], "sample_weight_mode": null, "keras_version": "1.0.5", "optimizer": {"name": "Nadam", "epsilon": 1e-08, "beta_2": 0.9990000128746033, "schedule_decay": 0.004, "beta_1": 0.8999999761581421, "lr": 0.0020000000949949026}, "class_name": "Sequential", "loss": "MSE"}

models/model_9_51200.json

@@ -0,0 +1 @@
+{"config": [{"class_name": "Dense", "config": {"name": "dense_28", "b_regularizer": null, "input_dtype": "float32", "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": 81, "activation": "sigmoid", "W_constraint": null, "batch_input_shape": [null, 81], "bias": true, "activity_regularizer": null, "output_dim": 324, "trainable": true}}, {"class_name": "Dense", "config": {"name": "dense_29", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 324}}, {"class_name": "Dense", "config": {"name": "dense_30", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 81}}], "sample_weight_mode": null, "keras_version": "1.0.5", "optimizer": {"name": "Nadam", "epsilon": 1e-08, "beta_2": 0.9990000128746033, "schedule_decay": 0.004, "beta_1": 0.8999999761581421, "lr": 0.0020000000949949026}, "class_name": "Sequential", "loss": "MSE"}

models/model_9_800.json

@@ -0,0 +1 @@
+{"config": [{"class_name": "Dense", "config": {"name": "dense_19", "b_regularizer": null, "input_dtype": "float32", "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": 81, "activation": "sigmoid", "W_constraint": null, "batch_input_shape": [null, 81], "bias": true, "activity_regularizer": null, "output_dim": 324, "trainable": true}}, {"class_name": "Dense", "config": {"name": "dense_20", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 324}}, {"class_name": "Dense", "config": {"name": "dense_21", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 81}}], "sample_weight_mode": null, "keras_version": "1.0.5", "optimizer": {"name": "Nadam", "epsilon": 1e-08, "beta_2": 0.9990000128746033, "schedule_decay": 0.004, "beta_1": 0.8999999761581421, "lr": 0.0020000000949949026}, "class_name": "Sequential", "loss": "MSE"}

models/model_9_819200.json

@@ -0,0 +1 @@
+{"config": [{"class_name": "Dense", "config": {"name": "dense_34", "b_regularizer": null, "input_dtype": "float32", "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": 81, "activation": "sigmoid", "W_constraint": null, "batch_input_shape": [null, 81], "bias": true, "activity_regularizer": null, "output_dim": 324, "trainable": true}}, {"class_name": "Dense", "config": {"name": "dense_35", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 324}}, {"class_name": "Dense", "config": {"name": "dense_36", "b_regularizer": null, "init": "normal", "b_constraint": null, "W_regularizer": null, "input_dim": null, "trainable": true, "W_constraint": null, "activation": "sigmoid", "bias": true, "activity_regularizer": null, "output_dim": 81}}], "sample_weight_mode": null, "keras_version": "1.0.5", "optimizer": {"name": "Nadam", "epsilon": 1e-08, "beta_2": 0.9990000128746033, "schedule_decay": 0.004, "beta_1": 0.8999999761581421, "lr": 0.0020000000949949026}, "class_name": "Sequential", "loss": "MSE"}

modelsCyclo/model_10_12800.json

@@ -0,0 +1 @@
+{"class_name": "Sequential", "sample_weight_mode": null, "keras_version": "1.0.5", "config": [{"class_name": "Dense", "config": {"output_dim": 500, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "trainable": true, "init": "normal", "name": "dense_43", "batch_input_shape": [null, 100], "activation": "sigmoid", "b_regularizer": null, "input_dim": 100, "input_dtype": "float32", "W_constraint": null}}, {"class_name": "Dense", "config": {"output_dim": 500, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "name": "dense_44", "init": "normal", "trainable": true, "activation": "sigmoid", "b_regularizer": null, "input_dim": null, "W_constraint": null}}, {"class_name": "Dense", "config": {"output_dim": 100, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "name": "dense_45", "init": "normal", "trainable": true, "activation": "sigmoid", "b_regularizer": null, "input_dim": null, "W_constraint": null}}], "optimizer": {"epsilon": 1e-08, "name": "Nadam", "beta_2": 0.9990000128746033, "lr": 0.0020000000949949026, "beta_1": 0.8999999761581421, "schedule_decay": 0.004}, "loss": "MSE"}

modelsCyclo/model_10_204800.json

@@ -0,0 +1 @@
+{"class_name": "Sequential", "sample_weight_mode": null, "keras_version": "1.0.5", "config": [{"class_name": "Dense", "config": {"output_dim": 500, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "trainable": true, "init": "normal", "name": "dense_49", "batch_input_shape": [null, 100], "activation": "sigmoid", "b_regularizer": null, "input_dim": 100, "input_dtype": "float32", "W_constraint": null}}, {"class_name": "Dense", "config": {"output_dim": 500, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "name": "dense_50", "init": "normal", "trainable": true, "activation": "sigmoid", "b_regularizer": null, "input_dim": null, "W_constraint": null}}, {"class_name": "Dense", "config": {"output_dim": 100, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "name": "dense_51", "init": "normal", "trainable": true, "activation": "sigmoid", "b_regularizer": null, "input_dim": null, "W_constraint": null}}], "optimizer": {"epsilon": 1e-08, "name": "Nadam", "beta_2": 0.9990000128746033, "lr": 0.0020000000949949026, "beta_1": 0.8999999761581421, "schedule_decay": 0.004}, "loss": "MSE"}

modelsCyclo/model_10_3200.json

@@ -0,0 +1 @@
+{"class_name": "Sequential", "sample_weight_mode": null, "keras_version": "1.0.5", "config": [{"class_name": "Dense", "config": {"output_dim": 500, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "trainable": true, "init": "normal", "name": "dense_40", "batch_input_shape": [null, 100], "activation": "sigmoid", "b_regularizer": null, "input_dim": 100, "input_dtype": "float32", "W_constraint": null}}, {"class_name": "Dense", "config": {"output_dim": 500, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "name": "dense_41", "init": "normal", "trainable": true, "activation": "sigmoid", "b_regularizer": null, "input_dim": null, "W_constraint": null}}, {"class_name": "Dense", "config": {"output_dim": 100, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "name": "dense_42", "init": "normal", "trainable": true, "activation": "sigmoid", "b_regularizer": null, "input_dim": null, "W_constraint": null}}], "optimizer": {"epsilon": 1e-08, "name": "Nadam", "beta_2": 0.9990000128746033, "lr": 0.0020000000949949026, "beta_1": 0.8999999761581421, "schedule_decay": 0.004}, "loss": "MSE"}

modelsCyclo/model_10_51200.json

@@ -0,0 +1 @@
+{"class_name": "Sequential", "sample_weight_mode": null, "keras_version": "1.0.5", "config": [{"class_name": "Dense", "config": {"output_dim": 500, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "trainable": true, "init": "normal", "name": "dense_46", "batch_input_shape": [null, 100], "activation": "sigmoid", "b_regularizer": null, "input_dim": 100, "input_dtype": "float32", "W_constraint": null}}, {"class_name": "Dense", "config": {"output_dim": 500, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "name": "dense_47", "init": "normal", "trainable": true, "activation": "sigmoid", "b_regularizer": null, "input_dim": null, "W_constraint": null}}, {"class_name": "Dense", "config": {"output_dim": 100, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "name": "dense_48", "init": "normal", "trainable": true, "activation": "sigmoid", "b_regularizer": null, "input_dim": null, "W_constraint": null}}], "optimizer": {"epsilon": 1e-08, "name": "Nadam", "beta_2": 0.9990000128746033, "lr": 0.0020000000949949026, "beta_1": 0.8999999761581421, "schedule_decay": 0.004}, "loss": "MSE"}

modelsCyclo/model_10_800.json

@@ -0,0 +1 @@
+{"class_name": "Sequential", "sample_weight_mode": null, "keras_version": "1.0.5", "config": [{"class_name": "Dense", "config": {"output_dim": 500, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "trainable": true, "init": "normal", "name": "dense_37", "batch_input_shape": [null, 100], "activation": "sigmoid", "b_regularizer": null, "input_dim": 100, "input_dtype": "float32", "W_constraint": null}}, {"class_name": "Dense", "config": {"output_dim": 500, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "name": "dense_38", "init": "normal", "trainable": true, "activation": "sigmoid", "b_regularizer": null, "input_dim": null, "W_constraint": null}}, {"class_name": "Dense", "config": {"output_dim": 100, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "name": "dense_39", "init": "normal", "trainable": true, "activation": "sigmoid", "b_regularizer": null, "input_dim": null, "W_constraint": null}}], "optimizer": {"epsilon": 1e-08, "name": "Nadam", "beta_2": 0.9990000128746033, "lr": 0.0020000000949949026, "beta_1": 0.8999999761581421, "schedule_decay": 0.004}, "loss": "MSE"}

modelsCyclo/model_8_12800.json

@@ -0,0 +1 @@
+{"class_name": "Sequential", "sample_weight_mode": null, "keras_version": "1.0.5", "config": [{"class_name": "Dense", "config": {"output_dim": 320, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "trainable": true, "init": "normal", "name": "dense_7", "batch_input_shape": [null, 64], "activation": "sigmoid", "b_regularizer": null, "input_dim": 64, "input_dtype": "float32", "W_constraint": null}}, {"class_name": "Dense", "config": {"output_dim": 320, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "name": "dense_8", "init": "normal", "trainable": true, "activation": "sigmoid", "b_regularizer": null, "input_dim": null, "W_constraint": null}}, {"class_name": "Dense", "config": {"output_dim": 64, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "name": "dense_9", "init": "normal", "trainable": true, "activation": "sigmoid", "b_regularizer": null, "input_dim": null, "W_constraint": null}}], "optimizer": {"epsilon": 1e-08, "name": "Nadam", "beta_2": 0.9990000128746033, "lr": 0.0020000000949949026, "beta_1": 0.8999999761581421, "schedule_decay": 0.004}, "loss": "MSE"}

modelsCyclo/model_8_204800.json

@@ -0,0 +1 @@
+{"class_name": "Sequential", "sample_weight_mode": null, "keras_version": "1.0.5", "config": [{"class_name": "Dense", "config": {"output_dim": 320, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "trainable": true, "init": "normal", "name": "dense_13", "batch_input_shape": [null, 64], "activation": "sigmoid", "b_regularizer": null, "input_dim": 64, "input_dtype": "float32", "W_constraint": null}}, {"class_name": "Dense", "config": {"output_dim": 320, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "name": "dense_14", "init": "normal", "trainable": true, "activation": "sigmoid", "b_regularizer": null, "input_dim": null, "W_constraint": null}}, {"class_name": "Dense", "config": {"output_dim": 64, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "name": "dense_15", "init": "normal", "trainable": true, "activation": "sigmoid", "b_regularizer": null, "input_dim": null, "W_constraint": null}}], "optimizer": {"epsilon": 1e-08, "name": "Nadam", "beta_2": 0.9990000128746033, "lr": 0.0020000000949949026, "beta_1": 0.8999999761581421, "schedule_decay": 0.004}, "loss": "MSE"}

modelsCyclo/model_8_3200.json

@@ -0,0 +1 @@
+{"class_name": "Sequential", "sample_weight_mode": null, "keras_version": "1.0.5", "config": [{"class_name": "Dense", "config": {"output_dim": 320, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "trainable": true, "init": "normal", "name": "dense_4", "batch_input_shape": [null, 64], "activation": "sigmoid", "b_regularizer": null, "input_dim": 64, "input_dtype": "float32", "W_constraint": null}}, {"class_name": "Dense", "config": {"output_dim": 320, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "name": "dense_5", "init": "normal", "trainable": true, "activation": "sigmoid", "b_regularizer": null, "input_dim": null, "W_constraint": null}}, {"class_name": "Dense", "config": {"output_dim": 64, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "name": "dense_6", "init": "normal", "trainable": true, "activation": "sigmoid", "b_regularizer": null, "input_dim": null, "W_constraint": null}}], "optimizer": {"epsilon": 1e-08, "name": "Nadam", "beta_2": 0.9990000128746033, "lr": 0.0020000000949949026, "beta_1": 0.8999999761581421, "schedule_decay": 0.004}, "loss": "MSE"}

modelsCyclo/model_8_51200.json

@@ -0,0 +1 @@
+{"class_name": "Sequential", "sample_weight_mode": null, "keras_version": "1.0.5", "config": [{"class_name": "Dense", "config": {"output_dim": 320, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "trainable": true, "init": "normal", "name": "dense_10", "batch_input_shape": [null, 64], "activation": "sigmoid", "b_regularizer": null, "input_dim": 64, "input_dtype": "float32", "W_constraint": null}}, {"class_name": "Dense", "config": {"output_dim": 320, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "name": "dense_11", "init": "normal", "trainable": true, "activation": "sigmoid", "b_regularizer": null, "input_dim": null, "W_constraint": null}}, {"class_name": "Dense", "config": {"output_dim": 64, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "name": "dense_12", "init": "normal", "trainable": true, "activation": "sigmoid", "b_regularizer": null, "input_dim": null, "W_constraint": null}}], "optimizer": {"epsilon": 1e-08, "name": "Nadam", "beta_2": 0.9990000128746033, "lr": 0.0020000000949949026, "beta_1": 0.8999999761581421, "schedule_decay": 0.004}, "loss": "MSE"}

modelsCyclo/model_8_800.json

@@ -0,0 +1 @@
+{"class_name": "Sequential", "sample_weight_mode": null, "keras_version": "1.0.5", "config": [{"class_name": "Dense", "config": {"output_dim": 320, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "trainable": true, "init": "normal", "name": "dense_1", "batch_input_shape": [null, 64], "activation": "sigmoid", "b_regularizer": null, "input_dim": 64, "input_dtype": "float32", "W_constraint": null}}, {"class_name": "Dense", "config": {"output_dim": 320, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "name": "dense_2", "init": "normal", "trainable": true, "activation": "sigmoid", "b_regularizer": null, "input_dim": null, "W_constraint": null}}, {"class_name": "Dense", "config": {"output_dim": 64, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "name": "dense_3", "init": "normal", "trainable": true, "activation": "sigmoid", "b_regularizer": null, "input_dim": null, "W_constraint": null}}], "optimizer": {"epsilon": 1e-08, "name": "Nadam", "beta_2": 0.9990000128746033, "lr": 0.0020000000949949026, "beta_1": 0.8999999761581421, "schedule_decay": 0.004}, "loss": "MSE"}

modelsCyclo/model_8_819200.json

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+{"class_name": "Sequential", "sample_weight_mode": null, "keras_version": "1.0.5", "config": [{"class_name": "Dense", "config": {"output_dim": 320, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "trainable": true, "init": "normal", "name": "dense_16", "batch_input_shape": [null, 64], "activation": "sigmoid", "b_regularizer": null, "input_dim": 64, "input_dtype": "float32", "W_constraint": null}}, {"class_name": "Dense", "config": {"output_dim": 320, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "name": "dense_17", "init": "normal", "trainable": true, "activation": "sigmoid", "b_regularizer": null, "input_dim": null, "W_constraint": null}}, {"class_name": "Dense", "config": {"output_dim": 64, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "name": "dense_18", "init": "normal", "trainable": true, "activation": "sigmoid", "b_regularizer": null, "input_dim": null, "W_constraint": null}}], "optimizer": {"epsilon": 1e-08, "name": "Nadam", "beta_2": 0.9990000128746033, "lr": 0.0020000000949949026, "beta_1": 0.8999999761581421, "schedule_decay": 0.004}, "loss": "MSE"}

modelsCyclo/model_9_12800.json

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+{"class_name": "Sequential", "sample_weight_mode": null, "keras_version": "1.0.5", "config": [{"class_name": "Dense", "config": {"output_dim": 405, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "trainable": true, "init": "normal", "name": "dense_25", "batch_input_shape": [null, 81], "activation": "sigmoid", "b_regularizer": null, "input_dim": 81, "input_dtype": "float32", "W_constraint": null}}, {"class_name": "Dense", "config": {"output_dim": 405, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "name": "dense_26", "init": "normal", "trainable": true, "activation": "sigmoid", "b_regularizer": null, "input_dim": null, "W_constraint": null}}, {"class_name": "Dense", "config": {"output_dim": 81, "bias": true, "b_constraint": null, "activity_regularizer": null, "W_regularizer": null, "name": "dense_27", "init": "normal", "trainable": true, "activation": "sigmoid", "b_regularizer": null, "input_dim": null, "W_constraint": null}}], "optimizer": {"epsilon": 1e-08, "name": "Nadam", "beta_2": 0.9990000128746033, "lr": 0.0020000000949949026, "beta_1": 0.8999999761581421, "schedule_decay": 0.004}, "loss": "MSE"}