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# TensorFlow and tf.keras
import tensorflow as tf
from tensorflow import keras

# Import numpy, Pandas, Regex & Visualisation libraries
import numpy as np
import pandas as pd
import re
from matplotlib import pyplot as plt

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# unzip the test file to read images
!unzip /content/drive/My\ Drive/test_ScVgIM0.zip

# Read test file names
test = pd.read_csv('test.csv')
test_copy = test.copy()

# Read test images and preprocess
test_image = []
for i in tqdm(range(test.shape[0])):

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model.compile(optimizer='adam',
              loss='categorical_crossentropy',
              metrics=['accuracy'])

model.fit(X_train, y_train, epochs=10, validation_data=(X_test, y_test))

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# Create Train and validation data to check the performance at each epoch
X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=42, test_size=0.2)

# Using Keras Sequential API to add neural network layers
model = keras.Sequential()
model.add(keras.layers.Conv2D(32, kernel_size=(3, 3),activation='relu',input_shape=(28,28,1)))
model.add(keras.layers.Conv2D(64, (3, 3), activation='relu'))
model.add(keras.layers.MaxPooling2D(pool_size=(2, 2)))
model.add(keras.layers.Dropout(0.25))
model.add(keras.layers.Flatten())

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# We have grayscale images, so while loading the images we will keep grayscale=True, if you have RGB images, you should set grayscale as False
train_image = []
for i in tqdm(range(train.shape[0])):
    img = image.load_img('train/'+train['id'][i].astype('str')+'.png', target_size=(28,28,1), color_mode="grayscale")
    img = image.img_to_array(img)
    img = img/255
    train_image.append(img)
X = np.array(train_image)

# Preprocessing the Target

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!unzip /content/drive/My\ Drive/train_LbELtWX.zip
train = pd.read_csv('train.csv')

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from google.colab import drive
drive.mount('/content/drive')

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# TensorFlow and tf.keras
import tensorflow as tf
from tensorflow import keras

# Helper libraries
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from tqdm import tqdm
from keras.preprocessing import image

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try:
  # %tensorflow_version only exists in Colab.
  %tensorflow_version 2.x
except Exception:
  pass

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import tensorflow as tf

x = tf.constant([1,2,3,4,5])
y = tf.constant([1,1,1,1,1])

a = tf.add(x,y)
print(a)