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Merged Tiago de Freitas Pereira requested to merge updates into master
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@@ -13,8 +13,7 @@ slim = tf.contrib.slim
@@ -13,8 +13,7 @@ slim = tf.contrib.slim
class BaseLoss(object):
class BaseLoss(object):
"""
"""
Base loss function.
Base loss function.
Stupid class. Don't know why I did that.
One exam
"""
"""
def __init__(self, loss, operation, name="loss"):
def __init__(self, loss, operation, name="loss"):
@@ -28,20 +27,17 @@ class BaseLoss(object):
@@ -28,20 +27,17 @@ class BaseLoss(object):
class MeanSoftMaxLoss(object):
class MeanSoftMaxLoss(object):
"""
"""
Mean softmax loss. Basically it wrapps the function tf.nn.sparse_softmax_cross_entropy_with_logits.
Simple CrossEntropy loss.
 
Basically it wrapps the function tf.nn.sparse_softmax_cross_entropy_with_logits.
 
 
**Parameters**
 
 
name: Scope name
 
add_regularization_losses: Regulize the loss???
 
"""
"""
def __init__(self, name="loss", add_regularization_losses=True):
def __init__(self, name="loss", add_regularization_losses=True):
"""
Constructor
**Parameters**
name:
Scope name
"""
self.name = name
self.name = name
self.add_regularization_losses = add_regularization_losses
self.add_regularization_losses = add_regularization_losses
@@ -58,20 +54,17 @@ class MeanSoftMaxLoss(object):
@@ -58,20 +54,17 @@ class MeanSoftMaxLoss(object):
class MeanSoftMaxLossCenterLoss(object):
class MeanSoftMaxLossCenterLoss(object):
"""
"""
Mean softmax loss. Basically it wrapps the function tf.nn.sparse_softmax_cross_entropy_with_logits.
Implementation of the CrossEntropy + Center Loss from the paper
"""
"A Discriminative Feature Learning Approach for Deep Face Recognition"(http://ydwen.github.io/papers/WenECCV16.pdf)
 
 
**Parameters**
 
name: Scope name
 
alpha: Alpha factor ((1-alpha)*centers-prelogits)
 
factor: Weight factor of the center loss
 
n_classes: Number of classes of your task
 
"""
def __init__(self, name="loss", alpha=0.9, factor=0.01, n_classes=10):
def __init__(self, name="loss", alpha=0.9, factor=0.01, n_classes=10):
"""
Constructor
**Parameters**
name:
Scope name
"""
self.name = name
self.name = name
self.n_classes = n_classes
self.n_classes = n_classes
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