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Showing posts from March 13, 2019

Forward pass output of a pertained network changes without back propagation

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2 I am using Chainer's pertained model vgg (here named net). Every time I run the following code, I get a different result: img = Image.open("/Users/macintosh/Desktop/Code/Ger.jpg") img = Variable(vgg.prepare(img)) img = img.reshape((1,) + img.shape) print(net(img,layers=['prob'])['prob']) I have checked vgg.prepare() several times but its output is the same, and there is no random initialization here (net is a pre-trained vgg network). So why is this happening? python neural-network pre-trained-model chainer vgg-net share | improve this question asked Nov 15 '18 at 17:09 sama

Desert Studies Center

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Not to be confused with the Desert Laboratory in Arizona. Main building of the Desert Studies Center at Zzyzx, California. Petroglyph at the DSC The Desert Studies Center (DSC) is a field station of the California State University located in Zzyzx, California, United States in the Mojave Desert. The purpose of the Center is to provide opportunities to conduct research, receive instruction and experience the Mojave Desert environment. It is officially operated by the California Desert Studies Consortium, a consortium of 7 CSU campuses: Dominguez Hills, Fullerton, Long Beach, Los Angeles, Northridge, San Bernardino and Cal Poly Pomona. Before the Center, the site was the Zzyzx Mineral Springs and Health Spa, run by Curtis Howe Springer from 1944 to 1974 without federal permission. After Springer was ejected, the CSU negotiated usage of the abandoned buildings of the health spa with the Bureau of Land Management, and in 1976, they signed a five-year cooperative manageme