首页 > 解决方案 > AttributeError:模块 'keras.utils' 没有属性 'Sequence'

问题描述

回溯(最后一次调用):文件“C:\Users\gutolinPC\Desktop\tensorflow.py”,第 3 行,从 keras.datasets 导入 mnist 文件“C:\Program Files\Python37\lib\site-packages\ keras__init__.py”,第 3 行,来自 . 导入 utils 文件“C:\Program Files\Python37\lib\site-packages\keras\utils__init__.py”第 6 行,从 导入 conv_utils 文件“C:\Program Files\Python37\lib\site-packages\keras\utils\conv_utils.py”,第 9 行,从 .. 导入后端作为 K 文件“C:\Program Files\Python37\lib\ site-packages\keras\backend__init__.py",第 89 行,从 .tensorflow_backend 导入 * 文件 "C:\Program Files\Python37\lib\site-packages\keras\backend\tensorflow_backend.py",第 5 行,导入张量流作为 tf 文件“C:

赢得 10

蟒蛇 3.7.0

Keras 2.2.4

Keras-应用程序 1.0.7

Keras-预处理 1.0.9

张量板 1.13.1

张量流 1.13.1

张量流估计器 1.13.0

完整代码

import numpy

from keras.datasets import mnist
from keras.models import Sequential
from keras.layers import Dense
from keras.utils import np_utils


numpy.random.seed(42)


(X_train, y_train), (X_test, y_test) = mnist.load_data()

X_train = X_train.reshape(60000, 784)
X_test = X_test.reshape(10000, 784)

X_train = X_train.astype('float32')
X_test = X_test.astype('float32')
X_train /= 255
X_test /= 255


Y_train = np_utils.to_categorical(y_train, 10)
Y_test = np_utils.to_categorical(y_test, 10)


model = Sequential()


model.add(Dense(800, input_dim=784, activation="relu",         
kernel_initializer="normal"))
model.add(Dense(10, activation="softmax", kernel_initializer="normal"))


model.compile(loss="categorical_crossentropy", optimizer="SGD", metrics=["accuracy"])

print(model.summary())


model.fit(X_train, Y_train, batch_size=200, epochs=25, validation_split=0.2, verbose=2)


scores = model.evaluate(X_test, Y_test, verbose=0)
print("Точность работы на тестовых данных: %.2f%%" % (scores[1]*100))

标签: pythonpython-3.xtensorflowkeras

解决方案


对于 Keras 版本 - 2.5.0 和 TF 版本 - 2.5.0

from tensorflow.keras.utils import to_categorical

并与

keras.utils.to_categorical()

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