text_plain_output_1.png
import os

import numpy as np
import pandas as pd
import os
for dirname, _, filenames in os.walk('/kaggle/input'):
    for filename in filenames:
        print(os.path.join(dirname, filename))
import pandas as pd
import numpy as np
from keras import backend as K
from keras.models import Model
from keras.callbacks import EarlyStopping
from keras.layers import Input, LSTM, Dense, BatchNormalization, Lambda, Flatten, Reshape
from sklearn.preprocessing import MinMaxScaler
from keras.layers.normalization import BatchNormalization
from keras import backend as K
from keras.layers import Input, Dense, Flatten, Dropout, Lambda, TimeDistributed, Permute, RepeatVector, LSTM, GRU, Add, Concatenate, Reshape, Multiply, merge, Dot, Activation, concatenate, dot, Subtract
from keras.initializers import Identity
from keras.activations import sigmoid
from keras.layers.advanced_activations import LeakyReLU
from keras.layers.convolutional import Conv1D
from keras.models import Sequential, Model
from keras.optimizers import Adam, SGD, RMSprop
from sklearn.neighbors import KernelDensity
from scipy.stats import ks_2samp, trim_mean, shapiro, normaltest, anderson
from keras.losses import mse, binary_crossentropy, sparse_categorical_crossentropy
from keras import backend as K
import matplotlib.pyplot as plt