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import numpy as np

import numpy as np

import numpy as np # linear algebra

import numpy as np # linear algebra

import math
import random
import pickle
import itertools
import numpy as np
import pandas as pd
from sklearn.metrics import accuracy_score, classification_report, confusion_matrix, label_ranking_average_precision_score, label_ranking_loss, coverage_error
from sklearn.utils import shuffle
from scipy.signal import resample
import matplotlib.pyplot as plt
np.random.seed(42)
import pickle
from sklearn.preprocessing import OneHotEncoder
from keras.models import Model
from keras.layers import Input, Dense, Conv1D, MaxPooling1D, Softmax, Add, Flatten, Activation
from keras import backend as K
from keras.optimizers import Adam
from keras.callbacks import LearningRateScheduler, ModelCheckpoint
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from sklearn.metrics import classification_report
from sklearn.model_selection import train_test_split
from sklearn.metrics import f1_score
from sklearn.metrics import confusion_matrix
import math
import random
import pickle
import itertools
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
np.random.seed(42)
import tensorflow as tf
import tensorflow.keras as keras