Python 3.5 Tensorflow模型值e

2024-04-26 17:58:06 发布

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import tensorflow as tf
import numpy as np
from keras.preprocessing import image
import cv2
import matplotlib.pyplot as plt

mnist = tf.keras.datasets.fashion_mnist
(training_images, training_labels), (test_images, test_labels) = mnist.load_data()

training_images = training_images.reshape(60000, 28, 28, 1)
training_images = training_images / 255.0
test_images = test_images.reshape(10000, 28, 28, 1)
test_images = test_images / 255.0

model = tf.keras.Sequential([
    tf.keras.layers.Flatten(),
    tf.keras.layers.Dense(128, activation="relu"),
    tf.keras.layers.Dense(10, activation="softmax")
])

model.compile(optimizer="adam", loss="sparse_categorical_crossentropy", metrics=["accuracy"])
model.fit(training_images, training_labels, epochs=20)

我在YouTube上看人工智能教程。从那里我得到了这个密码。在教程中,他们使用Google CoLab,一切正常。因此,当我运行代码时,最后一行抛出错误:ValueError: Attempt to convert a value (9) with an unsupported type (<class 'numpy.uint8'>) to a Tensor.有人知道我遗漏了什么或者我如何修复错误吗?你知道吗


Tags: testimportnumpylabelsmodellayerstfas