Layer conv2d_3 was called with an input that isn't a symbolic tensor

Question

hi I am building a image classifier for one-class classification in which i\'ve used autoencoder while running this model I am getting this error (ValueError: Layer conv2d_3

Answer 1

Here:

x = Conv2D(16, (3, 3), activation='relu', padding='same')(input_shape)

A shape is not a tensor.

Do this:

from keras.layers import *
inputTensor = Input(input_shape)
x = Conv2D(16, (3, 3), activation='relu', padding='same')(inputTensor)

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Hint about autoencoders

You should separate the encoder and decoder as individual models. Later you will probably want to work with only one of them.

Encoder:

inputTensor = Input(input_shape)
x = ....
encodedData = MaxPooling2D((2, 2), padding='same')(x)

encoderModel = Model(inputTensor,encodedData)

Decoder:

encodedInput = Input((4,4,8))
x = ....
decodedData = Conv2D(1, (3, 3), activation='sigmoid', padding='same')(x)

decoderModel = Model(encodedInput,decodedData)

Autoencoder:

autoencoderInput = Input(input_shape)
encoded = encoderModel(autoencoderInput)
decoded = decoderModel(encoded)

autoencoderModel = Model(autoencoderInput,decoded)