这个二维卷积conv2d模型哪里出错了？

Question

xs = tf.keras.Input([None,None])

conv_3 = tf.keras.layers.Conv2D(12, [3, 64],activation=tf.nn.relu)(xs)
conv_5 = tf.keras.layers.Conv2D(12, [5, 64],activation=tf.nn.relu)(conv_3)
conv_7 = tf.keras.layers.Conv2D(12, [7, 64],activation=tf.nn.relu)(conv_5)

conv_3_mean = tf.keras.layers.Flatten(tf.reduce_max(conv_3, axis=1, keep_dims=True))
conv_5_mean = tf.keras.layers.Flatten(tf.reduce_max(conv_5, axis=1, keep_dims=True))
conv_7_mean = tf.keras.layers.Flatten(tf.reduce_max(conv_7, axis=1, keep_dims=True))

flatten = tf.concat([conv_3_mean, conv_5_mean, conv_7_mean], axis=1)
fc_1 = tf.keras.layers.Dense(128,activation=tf.nn.relu)(flatten)
logits = tf.keras.layers.Dense(5,activation=tf.nn.softmax)(fc_1)

model = tf.keras.Model(inputs=xs, outputs=logits)

错误如下：

ValueError                                Traceback (most recent call last)
<ipython-input-254-34baec62c8bc> in <module>
      1 xs = tf.keras.Input([None,None])
      2 
----> 3 conv_3 = tf.keras.layers.Conv2D(12, [3, 64],activation=tf.nn.relu)(xs)
      4 
      5 conv_5 = tf.keras.layers.Conv2D(12, [5, 64],activation=tf.nn.relu)(conv_3)

D:\anaconda\lib\site-packages\tensorflow\python\keras\engine\base_layer.py in __call__(self, *args, **kwargs)
    949     # >> model = tf.keras.Model(inputs, outputs)
    950     if _in_functional_construction_mode(self, inputs, args, kwargs, input_list):
--> 951       return self._functional_construction_call(inputs, args, kwargs,
    952                                                 input_list)
    953 

D:\anaconda\lib\site-packages\tensorflow\python\keras\engine\base_layer.py in _functional_construction_call(self, inputs, args, kwargs, input_list)
   1088           layer=self, inputs=inputs, build_graph=True, training=training_value):
   1089         # Check input assumptions set after layer building, e.g. input shape.
-> 1090         outputs = self._keras_tensor_symbolic_call(
   1091             inputs, input_masks, args, kwargs)
   1092 

D:\anaconda\lib\site-packages\tensorflow\python\keras\engine\base_layer.py in _keras_tensor_symbolic_call(self, inputs, input_masks, args, kwargs)
    820       return nest.map_structure(keras_tensor.KerasTensor, output_signature)
    821     else:
--> 822       return self._infer_output_signature(inputs, args, kwargs, input_masks)
    823 
    824   def _infer_output_signature(self, inputs, args, kwargs, input_masks):

D:\anaconda\lib\site-packages\tensorflow\python\keras\engine\base_layer.py in _infer_output_signature(self, inputs, args, kwargs, input_masks)
    860           # overridden).
    861           # TODO(kaftan): do we maybe_build here, or have we already done it?
--> 862           self._maybe_build(inputs)
    863           outputs = call_fn(inputs, *args, **kwargs)
    864 

D:\anaconda\lib\site-packages\tensorflow\python\keras\engine\base_layer.py in _maybe_build(self, inputs)
   2682     # Check input assumptions set before layer building, e.g. input rank.
   2683     if not self.built:
-> 2684       input_spec.assert_input_compatibility(
   2685           self.input_spec, inputs, self.name)
   2686       input_list = nest.flatten(inputs)

D:\anaconda\lib\site-packages\tensorflow\python\keras\engine\input_spec.py in assert_input_compatibility(input_spec, inputs, layer_name)
    232       ndim = x.shape.rank
    233       if ndim is not None and ndim < spec.min_ndim:
--> 234         raise ValueError('Input ' + str(input_index) + ' of layer ' +
    235                          layer_name + ' is incompatible with the layer: '
    236                          ': expected min_ndim=' + str(spec.min_ndim) +

ValueError: Input 0 of layer conv2d_46 is incompatible with the layer: : expected min_ndim=4, found ndim=3. Full shape received: (None, None, None)

 请问，哪里错了，我该 如何修改？

 

Answer 1

xs = tf.keras.Input(shape=(640,640,3))改成你自己的xs = tf.keras.Input(shape=(12,64,1))啊，你的Shape少了一个channel维度