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import tensorflow as tf
LAYERS = [tf.keras.layers.Flatten(input_shape=[28,28], name="inputlayer"),
tf.keras.layers.Dense(300, activation='relu', name="hiddenlayer1"),
tf.keras.layers.Dense(100, activation='relu', name="hiddenlayer2"),
tf.keras.layers.Dense(10, activation='softmax', name="outputlayer")]
model = tf.keras.models.Sequential(LAYERS)
model.load_weights('./checkpoint')
LOSS_FUNCTION = tf.keras.losses.SparseCategoricalCrossentropy() # HERE
OPTIMIZER = "ADAM"
METRICS = ["accuracy"]
model.compile(loss=LOSS_FUNCTION,
optimizer=OPTIMIZER,
metrics=METRICS)
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