AI开发平台ModelArts-TensorFlow 2.1:训练并保存模型

时间：2023-11-01 16:20:34

AI开发平台ModelArts

训练并保存模型

from __future__ import absolute_import, division, print_function, unicode_literalsimport tensorflow as tfmnist = 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 / 255.0model = tf.keras.models.Sequential([    tf.keras.layers.Flatten(input_shape=(28, 28)),    tf.keras.layers.Dense(128, activation='relu'),    tf.keras.layers.Dense(256, activation='relu'),    tf.keras.layers.Dropout(0.2),    # 对输出层命名output，在模型推理时通过该命名取结果    tf.keras.layers.Dense(10, activation='softmax', name="output")])model.compile(optimizer='adam',              loss='sparse_categorical_crossentropy',              metrics=['accuracy'])model.fit(x_train, y_train, epochs=10)tf.keras.models.save_model(model, "./mnist")

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