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Combine LAR+L1 regularization

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This commit is contained in:
Jean-Marc Valin 2021-10-13 02:33:35 -04:00
parent 054d984bf3
commit fe7b54c0e8
4 changed files with 33 additions and 8 deletions
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10
dnn/training_tf2/lossfuncs.py
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@ -83,3 +83,13 @@ def metric_exc_sd(y_true,y_pred):
e_gt = tf_l2u(tf_u2l(y_true) - tf_u2l(p))
sd_egt = tf.keras.losses.MeanSquaredError(reduction=tf.keras.losses.Reduction.NONE)(e_gt,128)
return sd_egt
def loss_matchlar():
def loss(y_true,y_pred):
model_rc = y_pred[:,:,:16]
#y_true = lpc2rc(y_true)
loss_lar_diff = K.log((1.01 + model_rc)/(1.01 - model_rc)) - K.log((1.01 + y_true)/(1.01 - y_true))
loss_lar_diff = tf.square(loss_lar_diff)
return tf.reduce_mean(loss_lar_diff, axis=-1)
return loss