<reponame>crazysuryaa/Deeplearning_PlayGround
import tensorflow as tf
import numpy as np
 
def mymodel():
model.compile(optimizer=Adam, loss=mse, metrics=[accuracy])
history = model.fit(train_data2,
train_labels_cat2, epochs=15, batch_size=64,
validation_data=(val_data, val_labels_cat))
model.compile(optimizer=Adam, loss=mse, metrics=[accuracy])
history = model.fit(train_data2,
train_labels_cat2, epochs=15, batch_size=64,
validation_data=(val_data, val_labels_cat))
model.compile(optimizer=Adam, loss=mse, metrics=[accuracy])
history = model.fit(train_data2,
train_labels_cat2, epochs=15, batch_size=64,
validation_data=(val_data, val_labels_cat))

import tensorflow as tf
import numpy as np
 
def mymodel():
model.compile(optimizer=Adam, loss=mse, metrics=[accuracy])
history = model.fit(train_data2,
train_labels_cat2, epochs=15, batch_size=64,
validation_data=(val_data, val_labels_cat))
model.compile(optimizer=Adam, loss=mse, metrics=[accuracy])
history = model.fit(train_data2,
train_labels_cat2, epochs=15, batch_size=64,
validation_data=(val_data, val_labels_cat))
model.compile(optimizer=Adam, loss=mse, metrics=[accuracy])
history = model.fit(train_data2,
train_labels_cat2, epochs=15, batch_size=64,
validation_data=(val_data, val_labels_cat))