Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet, NasNet, Residual Attention Network, SENet)
deep-learning
pytorch
image-classification
densenet
resnet
squeezenet
inceptionv3
googlenet
resnext
cifar100
mobilenet
inceptionv4
shufflenet
xception
nasnet
inception-resnet-v2
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Updated
Aug 27, 2019 - Python
The 2x down-sampling is one of the important operations in reference models. But, a convolution or a pooling with
stride=2, padding='SAME'may result in different outputs over different deep learning libraries (e.g., TensorFlow, CNTK, Theano, Caffe, Torch, ...) due to their different padding behaviors.For example (TensorNets syntax; but can be regarded as pseudo codes for other libraries),