Aur*_*hie 4 python tensorflow google-colaboratory
几天前，我在第 12 纪元时遇到了同样的错误。这次，它发生在 1 号。我不知道为什么会发生这种情况，因为我没有对模型进行任何更改。X_train.max()我只是在按应有的比例缩放后将输入标准化为 1。
和贴片大小有关系吗？我应该减少它吗？
为什么会出现此错误以及如何修复它？
my_model.summary()
Model: "U-Net"
__________________________________________________________________________________________________
Layer (type) Output Shape Param # Connected to
==================================================================================================
input_6 (InputLayer) [(None, 64, 64, 64, 0 []
3)]
conv3d_95 (Conv3D) (None, 64, 64, 64, 5248 ['input_6[0][0]']
64)
batch_normalization_90 (BatchN (None, 64, 64, 64, 256 ['conv3d_95[0][0]']
ormalization) 64)
activation_90 (Activation) (None, 64, 64, 64, 0 ['batch_normalization_90[0][0]']
64)
conv3d_96 (Conv3D) (None, 64, 64, 64, 110656 ['activation_90[0][0]']
64)
batch_normalization_91 (BatchN (None, 64, 64, 64, 256 ['conv3d_96[0][0]']
ormalization) 64)
activation_91 (Activation) (None, 64, 64, 64, 0 ['batch_normalization_91[0][0]']
64)
max_pooling3d_20 (MaxPooling3D (None, 32, 32, 32, 0 ['activation_91[0][0]']
) 64)
conv3d_97 (Conv3D) (None, 32, 32, 32, 221312 ['max_pooling3d_20[0][0]']
128)
batch_normalization_92 (BatchN (None, 32, 32, 32, 512 ['conv3d_97[0][0]']
ormalization) 128)
activation_92 (Activation) (None, 32, 32, 32, 0 ['batch_normalization_92[0][0]']
128)
conv3d_98 (Conv3D) (None, 32, 32, 32, 442496 ['activation_92[0][0]']
128)
batch_normalization_93 (BatchN (None, 32, 32, 32, 512 ['conv3d_98[0][0]']
ormalization) 128)
activation_93 (Activation) (None, 32, 32, 32, 0 ['batch_normalization_93[0][0]']
128)
max_pooling3d_21 (MaxPooling3D (None, 16, 16, 16, 0 ['activation_93[0][0]']
) 128)
conv3d_99 (Conv3D) (None, 16, 16, 16, 884992 ['max_pooling3d_21[0][0]']
256)
batch_normalization_94 (BatchN (None, 16, 16, 16, 1024 ['conv3d_99[0][0]']
ormalization) 256)
activation_94 (Activation) (None, 16, 16, 16, 0 ['batch_normalization_94[0][0]']
256)
conv3d_100 (Conv3D) (None, 16, 16, 16, 1769728 ['activation_94[0][0]']
256)
batch_normalization_95 (BatchN (None, 16, 16, 16, 1024 ['conv3d_100[0][0]']
ormalization) 256)
activation_95 (Activation) (None, 16, 16, 16, 0 ['batch_normalization_95[0][0]']
256)
max_pooling3d_22 (MaxPooling3D (None, 8, 8, 8, 256 0 ['activation_95[0][0]']
) )
conv3d_101 (Conv3D) (None, 8, 8, 8, 512 3539456 ['max_pooling3d_22[0][0]']
)
batch_normalization_96 (BatchN (None, 8, 8, 8, 512 2048 ['conv3d_101[0][0]']
ormalization) )
activation_96 (Activation) (None, 8, 8, 8, 512 0 ['batch_normalization_96[0][0]']
)
conv3d_102 (Conv3D) (None, 8, 8, 8, 512 7078400 ['activation_96[0][0]']
)
batch_normalization_97 (BatchN (None, 8, 8, 8, 512 2048 ['conv3d_102[0][0]']
ormalization) )
activation_97 (Activation) (None, 8, 8, 8, 512 0 ['batch_normalization_97[0][0]']
)
max_pooling3d_23 (MaxPooling3D (None, 4, 4, 4, 512 0 ['activation_97[0][0]']
) )
conv3d_103 (Conv3D) (None, 4, 4, 4, 102 14156800 ['max_pooling3d_23[0][0]']
4)
batch_normalization_98 (BatchN (None, 4, 4, 4, 102 4096 ['conv3d_103[0][0]']
ormalization) 4)
activation_98 (Activation) (None, 4, 4, 4, 102 0 ['batch_normalization_98[0][0]']
4)
conv3d_104 (Conv3D) (None, 4, 4, 4, 102 28312576 ['activation_98[0][0]']
4)
batch_normalization_99 (BatchN (None, 4, 4, 4, 102 4096 ['conv3d_104[0][0]']
ormalization) 4)
activation_99 (Activation) (None, 4, 4, 4, 102 0 ['batch_normalization_99[0][0]']
4)
conv3d_transpose_20 (Conv3DTra (None, 8, 8, 8, 512 4194816 ['activation_99[0][0]']
nspose) )
concatenate_20 (Concatenate) (None, 8, 8, 8, 102 0 ['conv3d_transpose_20[0][0]',
4) 'activation_97[0][0]']
conv3d_105 (Conv3D) (None, 8, 8, 8, 512 14156288 ['concatenate_20[0][0]']
)
batch_normalization_100 (Batch (None, 8, 8, 8, 512 2048 ['conv3d_105[0][0]']
Normalization) )
activation_100 (Activation) (None, 8, 8, 8, 512 0 ['batch_normalization_100[0][0]']
)
conv3d_106 (Conv3D) (None, 8, 8, 8, 512 7078400 ['activation_100[0][0]']
)
batch_normalization_101 (Batch (None, 8, 8, 8, 512 2048 ['conv3d_106[0][0]']
Normalization) )
activation_101 (Activation) (None, 8, 8, 8, 512 0 ['batch_normalization_101[0][0]']
)
conv3d_transpose_21 (Conv3DTra (None, 16, 16, 16, 1048832 ['activation_101[0][0]']
nspose) 256)
concatenate_21 (Concatenate) (None, 16, 16, 16, 0 ['conv3d_transpose_21[0][0]',
512) 'activation_95[0][0]']
conv3d_107 (Conv3D) (None, 16, 16, 16, 3539200 ['concatenate_21[0][0]']
256)
batch_normalization_102 (Batch (None, 16, 16, 16, 1024 ['conv3d_107[0][0]']
Normalization) 256)
activation_102 (Activation) (None, 16, 16, 16, 0 ['batch_normalization_102[0][0]']
256)
conv3d_108 (Conv3D) (None, 16, 16, 16, 1769728 ['activation_102[0][0]']
256)
batch_normalization_103 (Batch (None, 16, 16, 16, 1024 ['conv3d_108[0][0]']
Normalization) 256)
activation_103 (Activation) (None, 16, 16, 16, 0 ['batch_normalization_103[0][0]']
256)
conv3d_transpose_22 (Conv3DTra (None, 32, 32, 32, 262272 ['activation_103[0][0]']
nspose) 128)
concatenate_22 (Concatenate) (None, 32, 32, 32, 0 ['conv3d_transpose_22[0][0]',
256) 'activation_93[0][0]']
conv3d_109 (Conv3D) (None, 32, 32, 32, 884864 ['concatenate_22[0][0]']
128)
batch_normalization_104 (Batch (None, 32, 32, 32, 512 ['conv3d_109[0][0]']
Normalization) 128)
activation_104 (Activation) (None, 32, 32, 32, 0 ['batch_normalization_104[0][0]']
128)
conv3d_110 (Conv3D) (None, 32, 32, 32, 442496 ['activation_104[0][0]']
128)
batch_normalization_105 (Batch (None, 32, 32, 32, 512 ['conv3d_110[0][0]']
Normalization) 128)
activation_105 (Activation) (None, 32, 32, 32, 0 ['batch_normalization_105[0][0]']
128)
conv3d_transpose_23 (Conv3DTra (None, 64, 64, 64, 65600 ['activation_105[0][0]']
nspose) 64)
concatenate_23 (Concatenate) (None, 64, 64, 64, 0 ['conv3d_transpose_23[0][0]',
128) 'activation_91[0][0]']
conv3d_111 (Conv3D) (None, 64, 64, 64, 221248 ['concatenate_23[0][0]']
64)
batch_normalization_106 (Batch (None, 64, 64, 64, 256 ['conv3d_111[0][0]']
Normalization) 64)
activation_106 (Activation) (None, 64, 64, 64, 0 ['batch_normalization_106[0][0]']
64)
conv3d_112 (Conv3D) (None, 64, 64, 64, 110656 ['activation_106[0][0]']
64)
batch_normalization_107 (Batch (None, 64, 64, 64, 256 ['conv3d_112[0][0]']
Normalization) 64)
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