Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_200_lr_0.01_model_type_vgg19_rand_seed_265358_test_samples_None_train_samples_None_weight_decay_0.02.pth.tar
Training Set:
Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.01989092119038105
Inter Cos: 0.10477276891469955
Norm Quadratic Average: 27.597177505493164
Nearest Class Center Accuracy: 0.26968

Layer 1: Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 2: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 3: Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 4: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 5: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 6: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 7: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 8: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 9: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 10: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 11: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 12: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 13: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 14: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 15: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 16: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 0.0
Linear Weight Rank: 4031
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 17: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 0.0
Linear Weight Rank: 3671
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 18: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 0.0
Linear Weight Rank: 10
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Output Layer:
Intra Cos: 0.9999998807907104
Inter Cos: 1.0000009536743164
Norm Quadratic Average: 9.68016888869272e-10
Nearest Class Center Accuracy: 0.1

Test Set:
Average Loss: 2.3025852577209474
Accuracy: 0.1
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: nan, Weights: nan
NC2 Equiangle: Features: nan, Weights: nan
NC3 Self-Duality: nan
NC4 NCC Mismatch: 1.0

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018526073545217514
Inter Cos: 0.1042705774307251
Norm Quadratic Average: 27.55013656616211
Nearest Class Center Accuracy: 0.284

Layer 1: Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 2: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 3: Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 4: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 5: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 6: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 7: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 8: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 9: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 10: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 11: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 12: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 13: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 14: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 15: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 16: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 0.0
Linear Weight Rank: 4031
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 17: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 0.0
Linear Weight Rank: 3671
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Layer 18: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 0.0
Linear Weight Rank: 10
Intra Cos: nan
Inter Cos: nan
Norm Quadratic Average: 0.0
Nearest Class Center Accuracy: 0.1

Output Layer:
Intra Cos: 0.9999996423721313
Inter Cos: 1.000000238418579
Norm Quadratic Average: 2.377802676978291e-10
Nearest Class Center Accuracy: 0.1

