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@Rishit-dagli

Rishit-dagli/random-tf.py

Last active Apr 23, 2021
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Random Search in TensorFlow
import kerastuner as kt
import tensorflow as tf
def model_builder(hp):
model = tf.keras.Sequential()
model.add(tf.keras.layers.Flatten(input_shape=(28, 28)))
# Tune the number of units in the first Dense layer
# Choose an optimal value between 32-512
hp_units = hp.Int('units', min_value = 32, max_value = 512, step = 32)
model.add(tf.keras.layers.Dense(units = hp_units, activation = 'relu'))
model.add(tf.keras.layers.Dense(10))
# Tune the learning rate for the optimizer
# Choose an optimal value from 0.01, 0.001, or 0.0001
hp_learning_rate = hp.Choice('learning_rate', values = [1e-2, 1e-3, 1e-4])
model.compile(optimizer = tf.keras.optimizers.Adam(learning_rate = hp_learning_rate),
loss = tf.keras.losses.SparseCategoricalCrossentropy(from_logits = True),
metrics = ['accuracy'])
return model
tuner = kt.RandomSearch(model_builder,
objective = 'val_accuracy',
max_trials = 10,
directory = 'random_search_starter',
project_name = 'intro_to_kt')
tuner.search(img_train, label_train, epochs = 10, validation_data = (img_test, label_test))
# Which was the best model?
best_model = tuner.get_best_models(1)[0]
# What were the best hyperparameters?
best_hyperparameters = tuner.get_best_hyperparameters(1)[0]
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