如何解决"ValueError:"Concatenate"层需要除concat轴以外具有匹配形状的输入"? [英] How to resolve "ValueError: A `Concatenate` layer requires inputs with matching shapes except for the concat axis"?

问题描述

我正在尝试实现3D CNN，但是由于输入形状不匹配，我收到了一条值错误消息.我要怎么做才能得到此错误，以及如何解决此类问题?

I am trying to implement a 3D CNN, but I am getting a value error message because the input shapes do not match. What am I doing wrong to get this error and how do I fix this kind of issue?

回溯中引用的部分代码如下:

The part of the code referenced in the traceback is as follows:

    x = conv3d_bn(img_input, 32, 3, 3, 3, strides=(2, 2, 2), padding='same', name='Conv3d_1b_3x3')
    x = conv3d_bn(img_input, 64, 3, 3, 3, strides=(2, 2, 2), padding='same', name='Conv3d_1c_3x3')

    branch_0 = MaxPooling3D((1, 3, 3), strides=(1, 2, 2), padding='same', name='MaxPool2d_2a_3x3')(x)

    branch_1 = conv3d_bn(branch_0, 96, 3, 3, 3, padding='same', name='Conv3d_2b_3x3')

    x = layers.concatenate([branch_0, branch_1], axis=channel_axis, name='mixed_2a')

    branch_0 = conv3d_bn(x, 64, 1, 1, 1, padding='same', name='Conv3d_3_0a_1x1')
    branch_0 = conv3d_bn(branch_0, 96, 3, 3, 3, padding='same', name='Conv3d_3c_0b_3x3')

    branch_1 = conv3d_bn(x, 64, 1, 1, 1, padding='same', name='Conv3d_3_1a_1x1')
    branch_1 = conv3d_bn(branch_1, 64, 7, 1, 1, padding='same', name='Conv3d_3c_1b_3x3')
    branch_1 = conv3d_bn(branch_1, 64, 1, 7, 7, padding='same', name='Conv3d_3c_1c_3x3')
    branch_1 = conv3d_bn(branch_1, 96, 3, 3, 3, padding='same', name='Conv3d_3c_1d_3x3')

    x = layers.concatenate([branch_0, branch_1], axis=channel_axis, name='mixed_3a')

    branch_0 = conv3d_bn(x, 192, 1, 1, 1, padding='same', name='Conv3d_3_0a_1x1')

    branch_1 = MaxPooling3D((1, 3, 3), strides=(1, 2, 2), padding='same', name='MaxPool2d_0b_3x3')(x)

    x = layers.concatenate([branch_0, branch_1], axis=channel_axis, name='mixed_4a')

这是回溯:

Traceback (most recent call last):
  File "train.py", line 292, in <module>
    main(**vars(p.parse_args()))
  File "train.py", line 155, in main
    400, spatial_squeeze=True, endpoint_logit='Logits')
  File "/home/larry/Documents/Projekt/i3dv2.py", line 241, in InceptionI3DV2
    x = layers.concatenate([branch_0, branch_1], axis=channel_axis, name='mixed_4a')
  File "/home/larry/anaconda3/lib/python3.7/site-packages/keras/layers/merge.py", line 649, in concatenate
    return Concatenate(axis=axis, **kwargs)(inputs)
  File "/home/larry/anaconda3/lib/python3.7/site-packages/keras/engine/base_layer.py", line 463, in __call__
    self.build(unpack_singleton(input_shapes))
  File "/home/larry/anaconda3/lib/python3.7/site-packages/keras/layers/merge.py", line 362, in build
    'Got inputs shapes: %s' % (input_shape))
ValueError: A `Concatenate` layer requires inputs with matching shapes except for the concat axis. Got inputs shapes: [(None, 32, 75, 75, 192), (None, 32, 38, 38, 192)]

我尝试过

 branch_0 = conv3d_bn(x, 192, 1, 3, 3, padding='same', name='Conv3d_3_0a_1x1')
 branch_1 = MaxPooling3D((1, 3, 3), strides=(1, 2, 2), padding='same', name='MaxPool2d_0b_3x3')(x) 
 x = layers.concatenate([branch_0, branch_1], axis=channel_axis, name='mixed_4a') 

仍然出现相同的错误.

期待您的评论.

推荐答案

基本上是这样.

考虑串联轴，例如追加更多行.其余部分必须具有相同的形状.在我的图中，串联轴是垂直箭头.

Think of concatenation axis like appending more rows. The rest must be of equal shape. In my drawing, the concatenation axis are the vertical arrows.

这篇关于如何解决"ValueError:"Concatenate"层需要除concat轴以外具有匹配形状的输入"?的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！