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celldice: actually do log(cosh())
....just wow.
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@ -38,6 +38,9 @@ class LossCrossEntropyDice(tf.keras.losses.Loss):
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cel = tf.nn.sigmoid_cross_entropy_with_logits(y_true, y_pred)
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cel = tf.nn.sigmoid_cross_entropy_with_logits(y_true, y_pred)
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dice = dice_loss(y_true, y_pred)
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dice = dice_loss(y_true, y_pred)
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if self.param_log_cosh:
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dice = tf.math.log(tf.math.cosh(dice))
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o = cel + dice
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o = cel + dice
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return tf.reduce_mean(o)
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return tf.reduce_mean(o)
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