loss.py

from keras import backend as K
def masked_categorical_crossentropy(y_true, y_pred):
    mask = K.cast(K.not_equal(y_true, -1), K.floatx())
    return K.categorical_crossentropy(y_true * mask, y_pred * mask)

def masked_categorical_accuracy(y_true, y_pred):
    mask = K.cast(K.not_equal(y_true, -1), K.floatx())
    return metrics.categorical_accuracy(y_true * mask, y_pred * mask)


model = build_model()
model = ModelMGPU(model, 2)
model.compile(
    loss=masked_categorical_crossentropy, 
    optimizer=optimizers.Nadam(0.01),
    metrics=[masked_categorical_accuracy]
)