Commit 9deb39b8 authored by Tiago de Freitas Pereira's avatar Tiago de Freitas Pereira
Browse files

[sphinx] Documented some classes [skip ci]

parent 0c5be077
Pipeline #13009 skipped
...@@ -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.
def __init__(self, name="loss", add_regularization_losses=True):
"""
Constructor
**Parameters** **Parameters**
name: name: Scope name
Scope name add_regularization_losses: Regulize the loss???
""" """
def __init__(self, name="loss", add_regularization_losses=True):
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)
def __init__(self, name="loss", alpha=0.9, factor=0.01, n_classes=10):
"""
Constructor
**Parameters** **Parameters**
name: name: Scope 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):
self.name = name self.name = name
self.n_classes = n_classes self.n_classes = n_classes
......
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