What deeplearning networks does pretrained models belongs to?

25×1 Layer array with layers: 1 'data' Image Input 227×227×3 images with 'zerocenter' normalization 2 'conv1' Convolution 96 11×11×3 convolutions with stride [4 4] and padding [0 0 0 0] 3 'relu1' ReLU ReLU 4 'norm1' Cross Channel Normalization cross channel normalization with 5 channels per element 5 'pool1' Max Pooling 3×3 max pooling with stride [2 2] and padding [0 0 0 0] 6 'conv2' Grouped Convolution 2 groups of 128 5×5×48 convolutions with stride [1 1] and padding [2 2 2 2] 7 'relu2' ReLU ReLU 8 'norm2' Cross Channel Normalization cross channel normalization with 5 channels per element 9 'pool2' Max Pooling 3×3 max pooling with stride [2 2] and padding [0 0 0 0] 10 'conv3' Convolution 384 3×3×256 convolutions with stride [1 1] and padding [1 1 1 1] 11 'relu3' ReLU ReLU 12 'conv4' Grouped Convolution 2 groups of 192 3×3×192 convolutions with stride [1 1] and padding [1 1 1 1] 13 'relu4' ReLU ReLU 14 'conv5' Grouped Convolution 2 groups of 128 3×3×192 convolutions with stride [1 1] and padding [1 1 1 1] 15 'relu5' ReLU ReLU 16 'pool5' Max Pooling 3×3 max pooling with stride [2 2] and padding [0 0 0 0] 17 'fc6' Fully Connected 4096 fully connected layer 18 'relu6' ReLU ReLU 19 'drop6' Dropout 50% dropout 20 'fc7' Fully Connected 4096 fully connected layer 21 'relu7' ReLU ReLU 22 'drop7' Dropout 50% dropout 23 'fc8' Fully Connected 1000 fully connected layer 24 'prob' Softmax softmax 25 'output' Classification Output crossentropyex with 'tench' and 999 other classes