def compute(self, input, label):
"""
compute loss
"""
cross_entropy = layers.CrossEntropyLayer()
reduce_mean = layers.ReduceMeanLayer()
loss = reduce_mean.ops(cross_entropy.ops(input, label))
return loss
def compute(self, pos, neg):
"""
compute loss
"""
sigmoid = layers.SigmoidLayer()
reduce_mean = layers.ReduceMeanLayer()
loss = reduce_mean.ops(sigmoid.ops(neg - pos))
return loss
def compute(self, input, label):
"""
compute loss
"""
reduce_mean = layers.ReduceMeanLayer()
cost = fluid.layers.cross_entropy(input=input, label=label)
avg_cost = reduce_mean.ops(cost)
return avg_cost
def compute(self, input, label):
"""
compute loss
"""
softmax_with_cross_entropy = layers.SoftmaxWithCrossEntropyLayer()
reduce_mean = layers.ReduceMeanLayer()
cost = softmax_with_cross_entropy.ops(input, label)
avg_cost = reduce_mean.ops(cost)
return avg_cost
def compute(self, pos, neg):
"""
compute loss
"""
elementwise_max = layers.ElementwiseMaxLayer()
elementwise_add = layers.ElementwiseAddLayer()
elementwise_sub = layers.ElementwiseSubLayer()
constant = layers.ConstantLayer()
reduce_mean = layers.ReduceMeanLayer()
loss = reduce_mean.ops(
elementwise_max.ops(
constant.ops(neg, neg.shape, "float32", 0.0),
elementwise_add.ops(
elementwise_sub.ops(neg, pos),
constant.ops(neg, neg.shape, "float32", self.margin))))
return loss