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@kishida

kishida/tensorflowtut.py

Last active Dec 14, 2020
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TensorFlow Tutrial
import tensorflow as tf
import time
# from tensorflow.python.compiler.mlcompute import mlcompute
# mlcompute.set_mlc_device(device_name='any')
mnist = tf.keras.datasets.mnist
(x_train, y_train), (x_test, y_test) = mnist.load_data()
x_train, x_test = x_train / 255.0, x_test / 255.0
model = tf.keras.models.Sequential([
tf.keras.layers.Flatten(input_shape=(28, 28)),
tf.keras.layers.Dense(512, activation='relu'),
tf.keras.layers.Dropout(0.2),
tf.keras.layers.Dense(10)
])
predictions = model(x_train[:1]).numpy()
loss_fn = tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True)
model.compile(optimizer='adam',
loss=loss_fn,
metrics=['accuracy'])
start = time.perf_counter()
model.fit(x_train, y_train, epochs=5)
end = time.perf_counter()
print(f"time: {end - start:.3f}")
model.evaluate(x_test, y_test)
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