You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
54 lines
1.9 KiB
54 lines
1.9 KiB
from __future__ import absolute_import |
|
from __future__ import division |
|
from __future__ import print_function |
|
import paddle |
|
import paddle.nn as nn |
|
import paddle.nn.functional as F |
|
|
|
|
|
class CenterLoss(nn.Layer): |
|
def __init__(self, num_classes=5013, feat_dim=2048): |
|
super(CenterLoss, self).__init__() |
|
self.num_classes = num_classes |
|
self.feat_dim = feat_dim |
|
self.centers = paddle.randn( |
|
shape=[self.num_classes, self.feat_dim]).astype( |
|
"float64") #random center |
|
|
|
def __call__(self, input, target): |
|
""" |
|
inputs: network output: {"features: xxx", "logits": xxxx} |
|
target: image label |
|
""" |
|
feats = input["features"] |
|
labels = target |
|
batch_size = feats.shape[0] |
|
|
|
#calc feat * feat |
|
dist1 = paddle.sum(paddle.square(feats), axis=1, keepdim=True) |
|
dist1 = paddle.expand(dist1, [batch_size, self.num_classes]) |
|
|
|
#dist2 of centers |
|
dist2 = paddle.sum(paddle.square(self.centers), axis=1, |
|
keepdim=True) #num_classes |
|
dist2 = paddle.expand(dist2, |
|
[self.num_classes, batch_size]).astype("float64") |
|
dist2 = paddle.transpose(dist2, [1, 0]) |
|
|
|
#first x * x + y * y |
|
distmat = paddle.add(dist1, dist2) |
|
tmp = paddle.matmul(feats, paddle.transpose(self.centers, [1, 0])) |
|
distmat = distmat - 2.0 * tmp |
|
|
|
#generate the mask |
|
classes = paddle.arange(self.num_classes).astype("int64") |
|
labels = paddle.expand( |
|
paddle.unsqueeze(labels, 1), (batch_size, self.num_classes)) |
|
mask = paddle.equal( |
|
paddle.expand(classes, [batch_size, self.num_classes]), |
|
labels).astype("float64") #get mask |
|
|
|
dist = paddle.multiply(distmat, mask) |
|
loss = paddle.sum(paddle.clip(dist, min=1e-12, max=1e+12)) / batch_size |
|
|
|
return {'CenterLoss': loss}
|
|
|