基本 CNN 分类模型有 UnimplementedError: Graph execution error:

原文标题Basic CNN classification model has UnimplementedError: Graph execution error:

我尝试了书中关于 MNIST 数据分类的 CNN 应用程序的示例代码:

from keras import layers
from keras import models

model = models.Sequential()
model.add(layers.Conv2D(32, (3,3), activation = 'relu', input_shape = (28, 28, 1)))
model.add(layers.MaxPooling2D((2,2)))
model.add(layers.Conv2D(64, (3,3), activation = 'relu'))
model.add(layers.MaxPooling2D((2,2)))
model.add(layers.Conv2D(64, (3,3), activation = 'relu'))
model.add(layers.Flatten())
model.add(layers.Dense(64, activation = 'relu'))
model.add(layers.Dense(10, activation = 'softmax'))
model.summary()

#Test this model on mnist
from keras.datasets import mnist
from tensorflow.keras.utils import to_categorical

(train_images, train_labels), (test_images, test_labels) = mnist.load_data()
train_images = train_images.reshape((60000,28,28,1))
train_images = train_images.astype('float32')/255
test_images = test_images.reshape((10000,28,28,1))
test_images = test_images.astype('float32')/255
train_labels = to_categorical(train_labels)
test_labels = to_categorical(test_labels)
model.compile(optimizer = 'rmsprop', loss = 'categorical_crossentropy', metrics = ['accuracy'])
model.fit(train_images, train_labels, epochs=5, batch_size=64)

代码应该是正确的,但是运行代码时出现错误:

UnimplementedError:图形执行错误:

我认为这个问题可能是由不同版本的 tensorflow 引起的(我的 tensorflow 是 2.8,而示例代码是在 tensorflow 2.0 中运行的)。谁能告诉我如何解决这个问题?

原文链接:https://stackoverflow.com//questions/71984908/basic-cnn-classification-model-has-unimplementederror-graph-execution-error

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