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@NMZivkovic

NMZivkovic/loss.py

Created Aug 30, 2019
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loss_objective_function = SparseCategoricalCrossentropy(from_logits=True, reduction='none')
def padded_loss_function(real, prediction):
mask = tf.math.logical_not(tf.math.equal(real, 0))
loss = loss_objective_function(real, prediction)
mask = tf.cast(mask, dtype=loss.dtype)
loss *= mask
return tf.reduce_mean(loss)
training_loss = Mean(name='training_loss')
training_accuracy = SparseCategoricalAccuracy(name='training_accuracy')
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