ValueError：“连接”层需要具有匹配形状（连接轴除外）的输入。获得输入形状：[(无、523、523、32)等

Question

我正在尝试使用以下代码使用 tensorflow 连接层，但出现意外错误。我是张量流新手

inp = Input(shape=(1050,1050,3))
x1= layers.Conv2D(16 ,(3,3), activation='relu')(inp)
x1= layers.Conv2D(32,(3,3), activation='relu')(x1)
x1= layers.MaxPooling2D(2,2)(x1)
x2= layers.Conv2D(32,(3,3), activation='relu')(x1)
x2= layers.Conv2D(64,(3,3), activation='relu')(x2)
x2= layers.MaxPooling2D(3,3)(x2)
x3= layers.Conv2D(64,(3,3), activation='relu')(x2)
x3= layers.Conv2D(64,(2,2), activation='relu')(x3)
x3= layers.Conv2D(64,(3,3), activation='relu')(x3)
x3= layers.Dropout(0.2)(x3)
x3= layers.MaxPooling2D(2,2)(x3)
x4= layers.Conv2D(64,(3,3), activation='relu')(x3)
x4= layers.MaxPooling2D(2,2)(x4)
x = layers.Dropout(0.2)(x4)
o = layers.Concatenate(axis=3)([x1, x2, x3, x4, x])
y = layers.Flatten()(o)
y = layers.Dense(1024, activation='relu')(y)
y = layers.Dense(5, activation='softmax')(y) 

model = Model(inp, y)
model.summary()
model.compile(loss='sparse_categorical_crossentropy',optimizer=RMSprop(lr=0.001),metrics=['accuracy'])

主要错误可以在标题中看到但是我提供了回溯错误以供参考并且错误是

ValueError                                Traceback (most recent call last)
<ipython-input-12-31a1fcec98a4> in <module>
     14 x4= layers.MaxPooling2D(2,2)(x4)
     15 x = layers.Dropout(0.2)(x4)
---> 16 o = layers.Concatenate(axis=3)([x1, x2, x3, x4, x])
     17 y = layers.Flatten()(o)
     18 y = layers.Dense(1024, activation='relu')(y)

/opt/conda/lib/python3.6/site-packages/tensorflow/python/keras/engine/base_layer.py in __call__(self, inputs, *args, **kwargs)
    589           # Build layer if applicable (if the `build` method has been
    590           # overridden).
--> 591           self._maybe_build(inputs)
    592 
    593           # Wrapping `call` function in autograph to allow for dynamic control

/opt/conda/lib/python3.6/site-packages/tensorflow/python/keras/engine/base_layer.py in _maybe_build(self, inputs)
   1879       # operations.
   1880       with tf_utils.maybe_init_scope(self):
-> 1881         self.build(input_shapes)
   1882     # We must set self.built since user defined build functions are not
   1883     # constrained to set self.built.

/opt/conda/lib/python3.6/site-packages/tensorflow/python/keras/utils/tf_utils.py in wrapper(instance, input_shape)
    293     if input_shape is not None:
    294       input_shape = convert_shapes(input_shape, to_tuples=True)
--> 295     output_shape = fn(instance, input_shape)
    296     # Return shapes from `fn` as TensorShapes.
    297     if output_shape is not None:

/opt/conda/lib/python3.6/site-packages/tensorflow/python/keras/layers/merge.py in build(self, input_shape)
    389                        'inputs with matching shapes '
    390                        'except for the concat axis. '
--> 391                        'Got inputs shapes: %s' % (input_shape))
    392 
    393   def _merge_function(self, inputs):

ValueError: A `Concatenate` layer requires inputs with matching shapes except for the concat axis. Got inputs shapes: [(None, 523, 523, 32), (None, 173, 173, 64), (None, 84, 84, 64), (None, 41, 41, 64), (None, 41, 41, 64)]

我已经使用导入了运行代码所需的所有必要文件tensorflow.keras

Answer 1

您无法对具有不同尺寸（即高度和宽度）的输入执行串联操作。layers.Concatenate(axis=3)([x1, x2, x3, x4, x])在您的情况下，您正在尝试执行此操作

x1 has dimension = (None, 523, 523, 32)
x2 has dimension = (None, 173, 173, 64)
x3 has dimension = (None, 84, 84, 64)
x4 has dimension = (None, 41, 41, 64)
and x has dimension = (None, 41, 41, 64)

发生错误的原因是，所有输入尺寸（即要连接的高度和宽度）都不同。要解决该错误，您必须将所有输入获取到相同的维度，即相同的高度和宽度，这可以通过将层采样到固定维度来实现。根据您的用例，您可以下采样或上采样以达到所需的尺寸。

ValueError: A `Concatenate` layer requires inputs with matching shapes except for the concat axis. Got inputs shapes: [(None, 523, 523, 32), (None, 173, 173, 64), (None, 84, 84, 64), (None, 41, 41, 64), (None, 41, 41, 64)]

错误指出layer requires inputs with matching shapes，这只是输入的高度和宽度。