ValueError：检查输入时出错：预期 input_1 具有形状 (None, 65563)

Question

我有一个用 Keras 编写的自动编码器，如下所示。我收到以下错误，不知道如何解决，有什么想法吗？

ValueError：检查输入时出错：预期 input_1 具有形状 (None, 65563) 但得到的数组具有形状 (374, 65536)

from keras.layers import Input, Dense, Flatten

from keras.models import Model

from keras.preprocessing.image import img_to_array

import cv2

import numpy

import os

training_directory = '/training'

validation_directory ='/validation'

results_directory = '/results'

training_images = []

validation_images = []

# the size of the encoded represenatation

encoding_dimension = 784

# input placeholder

input_image = Input(shape=(65563,))

# the encoded representation of the input

encoded = Dense(encoding_dimension,activation='relu')(input_image)

# reconstruction of the input (lossy)

decoded = Dense(65563,activation='sigmoid')(encoded)

# map the input image to its reconstruction

autoencoder = Model(input_image,decoded)

# encoder model

# map an input image to its encoded representation

encoder = Model(input_image,encoded)

# decoder model

# place holder fpr an encoded input

encoded_input = Input(shape=(encoding_dimension,))

# retrieve the last layer of the autoencoder model

decoder_layer = autoencoder.layers[-1]

# create the decoder model

decoder = Model(encoded_input,decoder_layer(encoded_input))

for root, dirs, files in os.walk(training_directory):

    for file in files:

        image = cv2.imread(root + '/' + file)

        image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

        image = img_to_array(image)

        training_images.append(image)

training_images = numpy.array(training_images)

for root, dirs, files in os.walk(validation_directory):

    for file in files:

        image = cv2.imread(root + '/' + file)

        image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

        image = img_to_array(image)

        validation_images.append(image)

validation_images = numpy.array(validation_images)

谢谢。

Answer 1

写作65563而不是65536可能是导致问题的错字。