ValueError: 层序列 2 的输入 0 与层不兼容

时间:2021-04-08 12:17:13

标签: python numpy tensorflow keras deep-learning

我有以下代码:

import tensorflow as tf
import keras
from keras.datasets import cifar10

(x_train, y_train), (x_test, y_test) = cifar10.load_data()

import numpy as np

x_train = np.reshape(x_train, (x_train.shape[0], x_train.shape[1], x_train.shape[2], 3))
print(x_train.shape)
x_test = np.reshape(x_test, (x_test.shape[0], x_test.shape[1], x_test.shape[2], 3))
print(x_test.shape)

x_train = x_train.astype('float32')/255.0
x_test  = x_test.astype('float32')/255.0

from keras.utils import to_categorical
y_train = to_categorical(y_train, num_classes = 10)
y_test = to_categorical(y_test, num_classes = 10)

from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Flatten

model = Sequential()
#Defining layers of the model
model.add(Dense(2056, activation='relu', input_shape = (3072,)))
model.add(Dense(10, activation='softmax')) 

model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])
model.summary()

history = model.fit(x_train, y_train, batch_size=1000, epochs=50)

我面临以下错误:

ValueError: 层序列 2 的输入 0 与层不兼容:输入形状的预期轴 -1 具有值 3072 但接收到形状为 (1000, 32, 32, 3) 的输入

我只想将 input_shape 保留为 3072。我怎样才能重塑我的 y_test 来解决这个问题?

1 个答案:

答案 0 :(得分:2)

在将输入数据传递到 Flatten 层之前,您应该Dense

model = Sequential()
#Defining layers of the model
model.add(Flatten(input_shape=(32,32,3)) # 32*32*3 = 3072
model.add(Dense(2056, activation='relu'))
model.add(Dense(10, activation='softmax')) 

这应该可以解决问题。