我正在使用以下代码，但会遇到以下错误。请帮助解决它。
我试图在没有Lambda层的情况下使用空间来深度功能，但有一个错误，如下
'NoneType' object has no attribute '_inbound_nodes'
def my_model(input_shape, output):
if K.image_dim_ordering() == 'tf':
input_shape= (input_shape[1], input_shape[2], input_shape[0])
input = Input(input_shape)
# First convolution Block
conv_1 =bn_conv("x", 32, (5,5), 1, padding ="same")(input)
conv_2 =bn_conv("conv", 64, (5,5), 1, padding ="same")(conv_1)
conv_3 =bn_conv("conv", 128, (5,5), 1, padding ="same")(conv_2)
concat1_3 = concatenate([conv_1, conv_3])
conv_4 =bn_conv("x", 256, (5,5), 1, padding ="same")(concat1_3)
concat1_4 = concatenate([conv_1, conv_4])
# skip connections of first Blcock
conv1_1 = Lambda(space_to_depth_x2)(conv_1)
conv1_2 = Lambda(space_to_depth_x4)(conv_1)
conv2_1 = Lambda(space_to_depth_x4)(conv_2)
conv3_1 = Lambda(space_to_depth_x2)(conv_3)
conv3_2 = Lambda(space_to_depth_x4)(conv_3)
conv4_1 = Lambda(space_to_depth_x2)(conv_4)
conv4_2 = Lambda(space_to_depth_x4)(conv_4)
# First transition Block
conv_t1 = bn_conv("conv",32, (1,1), 1)(concat1_4)
max1 = MaxPooling2D(2,2)(conv_t1)
# Second convolution Block
conv_5 =bn_conv("x", 32, (3,3), 1, padding ="same")(max1)
conv5_1 = Lambda(space_to_depth_x2)(conv_5)
concat4_5 = concatenate([conv4_1, conv_5])
conv_6 =bn_conv("conv", 64, (5,5), 1, padding ="same")(concat4_5)
conv6_1 = Lambda(space_to_depth_x2)(conv_6)
concat3_4_5 = concatenate([conv3_1,conv4_1,conv_5,conv_6])
conv_7 =bn_conv("x", 128, (3,3), 1, padding ="same")(concat3_4_5)
conv7_2 = Lambda(space_to_depth_x2)(conv_7)
concat6_3_5_4_1 = concatenate([conv_7, conv_5, conv_6, conv1_1, conv3_1, conv4_1])
conv_8 =bn_conv("conv", 256, (5,5), 1, padding ="same")(concat6_3_5_4_1)
concat7_5_4_1 = concatenate([conv_8,conv_7,conv_5,conv4_1,conv1_1])
# Second transition Block
conv_t2 = bn_conv("conv",32, (1,1), 1)(concat7_5_4_1)
max2 = MaxPooling2D(2,2)(conv_t2)
concat6 = concatenate([conv6_1, max2])
# Second convolution Block
conv_9 =bn_conv("conv", 32, (5,5), 1, padding ="same")(concat6)
concat2_7_5 = concatenate([conv_9, conv2_1,conv7_2, conv5_1])
conv_10 =bn_conv("x", 64, (5,5), 1, padding ="same")(concat2_7_5)
concat5_9_3_2 = concatenate([conv_10,conv5_1,conv_9,conv3_2,conv2_1])
conv_11 =bn_conv("conv", 128, (3,3), 1, padding ="same")(concat5_9_3_2)
concat3_7_10_5_4 = concatenate([conv_11,conv3_2,conv7_2,conv_10,conv5_1,conv4_2])
conv_12 =bn_conv("x", 256, (5,5), 1, padding ="same")(concat3_7_10_5_4)
concat7_10_4 = concatenate([conv_12,conv7_2,conv_10,conv4_2 ])
# Prediction layer
conv_13 = Conv2D(10,(8,8))(concat7_10_4)
flat = Flatten() (conv_13)
act = Activation("softmax")(flat)
model = Model(inputs=input, outputs=act)
return model
model = my_model([3, 32, 32], 10)
当我使用Lambda功能避免'NoneType' object has no attribute '_inbound_nodes'时，我会出现以下错误，因此请建议一些解决方案。
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-17-ca5cd7c7032e> in <module>()
89 return model
90
---> 91 model = my_model([3, 32, 32], 10)
92 from keras.optimizers import Adam
93
6 frames
<ipython-input-17-ca5cd7c7032e> in my_model(input_shape, output)
36 # skip connections of first Blcock
37
---> 38 conv1_1 = Lambda(space_to_depth_x2)(conv_1)
39 conv1_2 = Lambda(space_to_depth_x4)(conv_1)
40 conv2_1 = Lambda(space_to_depth_x4)(conv_2)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/base_layer.py in __call__(self, inputs, *args, **kwargs)
661 kwargs.pop('training')
662 inputs, outputs = self._set_connectivity_metadata_(
--> 663 inputs, outputs, args, kwargs)
664 self._handle_activity_regularization(inputs, outputs)
665 self._set_mask_metadata(inputs, outputs, previous_mask)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/base_layer.py in _set_connectivity_metadata_(self, inputs, outputs, args, kwargs)
1706 kwargs.pop('mask', None) # `mask` should not be serialized.
1707 self._add_inbound_node(
-> 1708 input_tensors=inputs, output_tensors=outputs, arguments=kwargs)
1709 return inputs, outputs
1710
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/base_layer.py in _add_inbound_node(self, input_tensors, output_tensors, arguments)
1793 """
1794 inbound_layers = nest.map_structure(lambda t: t._keras_history.layer,
-> 1795 input_tensors)
1796 node_indices = nest.map_structure(lambda t: t._keras_history.node_index,
1797 input_tensors)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/util/nest.py in map_structure(func, *structure, **kwargs)
513
514 return pack_sequence_as(
--> 515 structure[0], [func(*x) for x in entries],
516 expand_composites=expand_composites)
517
/usr/local/lib/python3.6/dist-packages/tensorflow/python/util/nest.py in <listcomp>(.0)
513
514 return pack_sequence_as(
--> 515 structure[0], [func(*x) for x in entries],
516 expand_composites=expand_composites)
517
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/base_layer.py in <lambda>(t)
1792 `call` method of the layer at the call that created the node.
1793 """
-> 1794 inbound_layers = nest.map_structure(lambda t: t._keras_history.layer,
1795 input_tensors)
1796 node_indices = nest.map_structure(lambda t: t._keras_history.node_index,
AttributeError: 'tuple' object has no attribute 'layer'
我得到了答案。
我正在使用
from tensorflow.nn import space_to_depth
是上述错误。