Keras输出形状和模型摘要(Xception)

时间:2018-02-03 04:01:58

标签: deep-learning keras

我的问题与这些问题有所不同,因为它与内置模型有关。

Keras cnn model output shape doesn't match model summary

Keras - CNN Model Summary Diemension Interpretation

我试图检查用于转移学习的内置Xception模型并使用 model.summary():

以下是Xception模型的前几层

 Layer (type)                    Output Shape         Param      Connected to                     
==================================================================================================
input_1 (InputLayer)            (None, None, None, 3 0                                            
__________________________________________________________________________________________________
block1_conv1 (Conv2D)           (None, None, None, 3 864         input_1[0][0]                    
__________________________________________________________________________________________________
block1_conv1_bn (BatchNormaliza (None, None, None, 3 128         block1_conv1[0][0]               
______________________________________________________________________________________

我关心的是深度渠道。 不应该将block1_conv1(Conv2D)的深度输出设为32而不是3?

如果我通过get_layer找出输出,我得到正确的输出:

base_model.get_layer(index = 1).output
<tf.Tensor 'block1_conv1/convolution:0' shape=(?, ?, ?, 32) dtype=float32>



base_model = Xception(weights='imagenet', include_top=False)
print(base_model.summary())

0 个答案:

没有答案
相关问题