找到 60000 个输入样本和 10000 个目标 samples.How 来解决这个错误？

Question

这是我从 tensorflow 网站上的 tensorflow 教程中获得的代码。中途我收到了这个错误。 ii 成功训练模型。但是当测试图像通过时我得到错误。

from tensorflow import keras
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
fashion_mnist= keras.datasets.fashion_mnist
(train_images, train_labels), (test_images, test_labels) = fashion_mnist.load_data()
class_names = ['T-shirt/top', 'Trouser', 'Pullover', 'Dress', 'Coat',
               'Sandal', 'Shirt', 'Sneaker', 'Bag', 'Ankle boot']
train_images=train_images/255.0
test_images=train_images/255.0
model=keras.Sequential([
    keras.layers.Flatten(input_shape=(28,28)),
    keras.layers.Dense(128,activation='relu'),
    keras.layers.Dense(10)])
model.compile(optimizer='adam',
              loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True),
              metrics=['accuracy'])
model.fit(train_images,train_labels,epochs=5)
test_loss, test_acc = model.evaluate(test_images,  test_labels, verbose=2)
print('\nTest accuracy:', test_acc)```

this code gives the following error:

ValueError: Input arrays should have the same number of samples as target arrays. Found 60000 input samples and 10000 target samples.

Answer 1

因为你在规范化时打错了：

test_images=train_images/255.0

而不是：

test_images = test_images / 255.0

Answer 2

test_images=train_images/255.0

应该改为：

test_images=test_images/255.0

否则你将 train_images 除以 255，然后再将其除以 255

找到 60000 个输入样本和 10000 个目标 samples.How 来解决这个错误？

Found 60000 input samples and 10000 target samples.How to solve this error?

python

machine-learning

keras

tensorflow

tensorflow2.0