ValueError：层激活_1的输入不是符号张量

Posted 2021-03-31

from keras.layers import AveragePooling2D
from keras.models import Sequential
from keras.layers.normalization import BatchNormalization
from keras.layers.convolutional import Conv2D
from keras.layers.convolutional import MaxPooling2D
from keras.layers.core import Activation
from keras.layers.core import Flatten
from keras.layers.core import Dropout
from keras.layers.core import Dense
from keras import backend as K


class SmallerVGGNet:
    @staticmethod
    def build(width, height, depth, classes, finalAct="softmax"):

        x = (height, width, depth)
        output = -1


        # CONV => RELU => POOL
        x = (Conv2D(16, (3, 3), padding="same", input_shape=x))
        x = (Activation("relu")(x))
        x = (BatchNormalization(axis=output)(x))
        x = (MaxPooling2D(pool_size=(3, 3))(x))

        x = (Conv2D(32, (3, 3), padding="same")(x))
        x = (Activation("relu")(x))
        x = (BatchNormalization(axis=output)(x))
        x = (MaxPooling2D(pool_size=(3, 3))(x))
        x = (BatchNormalization(axis=output)(x))

        # (CONV => RELU) * 2 => POOL
        x = (Conv2D(64, (3, 3), padding="same")(x))
        x = (Activation("relu")(x))
        x = (BatchNormalization(axis=output)(x))
        x = (Conv2D(64, (3, 3), padding="same")(x))
        x = (Activation("relu")(x))
        x = (BatchNormalization(axis=output)(x))
        x = (AveragePooling2D(pool_size=(2, 2))(x))

        # (CONV => RELU) * 2 => POOL
        x = (Conv2D(128, (3, 3), padding="same")(x))
        x = (Activation("relu")(x))
        x = (BatchNormalization(axis=output)(x))
        x = (Conv2D(128, (3, 3))(x))
        x = (Activation("relu")(x))
        x = (BatchNormalization(axis=output)(x))
        x = (MaxPooling2D(pool_size=(2, 2))(x))

        # first (and only) set of FC => RELU layers
        x = (Flatten()(x))
        x = (Dense(128)(x))
        x = (Activation("relu")(x))
        x = (BatchNormalization()(x))
        x = (Dropout(0.5)(x))

        # softmax classifier
        x = (Dense(classes)(x))
        x = (Activation(finalAct)(x))

        x.summary()

        # return the constructed network architecture
[enter image description here][2]

为什么这会在我运行代码时出现，为什么说层激活是用不是符号张量的输入来调用的。请帮助我解决此问题

ValueError：使用不是符号张量的输入来调用layer activation_1。收到的类型：。完整输入：[]。该层的所有输入都应为张量。