Layer (type) Output Shape Param #
=================================================================
conv2d_1 (Conv2D) (None, 3, 32, 96) 2688
_________________________________________________________________
activation_1 (Activation) (None, 3, 32, 96) 0
_________________________________________________________________
conv2d_2 (Conv2D) (None, 3, 32, 96) 83040
_________________________________________________________________
activation_2 (Activation) (None, 3, 32, 96) 0
_________________________________________________________________
conv2d_3 (Conv2D) (None, 2, 16, 96) 83040
_________________________________________________________________
dropout_1 (Dropout) (None, 2, 16, 96) 0
_________________________________________________________________
conv2d_4 (Conv2D) (None, 2, 16, 192) 166080
_________________________________________________________________
activation_3 (Activation) (None, 2, 16, 192) 0
_________________________________________________________________
conv2d_5 (Conv2D) (None, 2, 16, 192) 331968
_________________________________________________________________
activation_4 (Activation) (None, 2, 16, 192) 0
_________________________________________________________________
conv2d_6 (Conv2D) (None, 1, 8, 192) 331968
_________________________________________________________________
dropout_2 (Dropout) (None, 1, 8, 192) 0
_________________________________________________________________
conv2d_7 (Conv2D) (None, 1, 8, 192) 331968
_________________________________________________________________
activation_5 (Activation) (None, 1, 8, 192) 0
_________________________________________________________________
conv2d_8 (Conv2D) (None, 1, 8, 192) 37056
_________________________________________________________________
activation_6 (Activation) (None, 1, 8, 192) 0
_________________________________________________________________
conv2d_9 (Conv2D) (None, 1, 8, 10) 1930
_________________________________________________________________
global_average_pooling2d_1 ( (None, 10) 0
_________________________________________________________________
activation_7 (Activation) (None, 10) 0
=================================================================
Total params: 1,369,738
Trainable params: 1,369,738
Non-trainable params: 0
_________________________________________________________________
None
ValueError：
内核中输入通道的数量应指定数量 1组频道的数量
在处理上述异常期间，发生了另一个异常：
ValueError
内向追踪（最近通话最近一次） （）
----> 1个分数= model.evaluate（X_test，Y_test，verbose = 1）
ValueError：
内核中输入通道的数量应指定数量 1组频道的数量
应用导致错误的节点：
AbstractConv2d{convdim=2, border_mode='half', subsample=(1, 1), filter_flip=True, imshp=(None, 32, 3, 32), kshp=(96, 32, 3, 3), filter_dilation=(1, 1), num_groups=1, unshared=False}(InplaceDimShuffle{0,3,1,2}.0, InplaceDimShuffle{3,2,0,1}.0)