Example #1
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 def loss_Lagrangian_Re(_, y):
     return tf.reduce_mean(lambla_Re * y)
Example #2
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 def loss_Lagrangian_Im(_, y):
     return tf.reduce_mean(lambla_Im * y)
Example #3
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def loss_volume(_, y):
    return tf.math.square(tf.math.maximum(0.0, tf.reduce_mean(y) - GAMMA))
Example #4
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def loss_power(_, y):
    return tf.reduce_mean(y)
Example #5
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 def loss_V2(_, y):
     return tf.reduce_mean(y) - GAMMA
Example #6
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 def loss_V1(_, y):
     if lambdaV > 0:
         return tf.math.square(tf.reduce_mean(y) - GAMMA)
     return loss_volume(None, y)
Example #7
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 def loss_PDE3(_, y):
     return tf.reduce_mean(lambla3 * y)
Example #8
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 def loss_PDE2(_, y):
     return tf.reduce_mean(lambla2 * y)
Example #9
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 def loss_PDE1(_, y):
     return tf.reduce_mean(lambla1 * y)