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from tensorflow.keras.layers import Dropout, Dense, Activation, Flatten, Conv2D, MaxPool2D, BatchNormalization

from tensorflow.keras.models import Sequential

import pandas as pd

import visualkeras as vk

train = pd.read_csv('/kaggle/input/hackerearth/dataset/train.csv')

num = len(train['Class'].unique())

model = Sequential()
model.add(Conv2D(16, kernel_size=(5, 5), activation='relu', input_shape=(150, 150, 3)))
model.add(MaxPool2D((2, 2)))
model.add(Conv2D(32, kernel_size=(5, 5), activation='relu'))
model.add(MaxPool2D((2, 2)))
model.add(Conv2D(64, kernel_size=(5, 5), activation='relu'))
model.add(MaxPool2D((2, 2)))
model.add(Conv2D(128, kernel_size=(3, 3), activation='relu'))
model.add(MaxPool2D((2, 2)))
model.add(Flatten())
model.add(Dense(512, activation='relu'))
model.add(Dense(128, activation='relu'))
model.add(Dense(64, activation='relu'))
model.add(Dense(num, activation='softmax'))

model.summary()

vk.layered_view(model, legend=True)