2

我在加载自我预训练的 keras 模型时遇到问题。当我在训练模型后直接进行预测时，一切正常。

我的代码：

    import tensorflow as tf
from keras.models import Sequential
from keras.layers import Dense, Conv2D, Dropout, Flatten, MaxPooling2D
import matplotlib.pyplot as plt
import numpy as np
import os
from keras.models import load_model
"""
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Conv2D, Dropout, Flatten, MaxPooling2D
from tensorflow.keras.models import load_model
"""
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
import matplotlib.pyplot as plt
(x_train, y_train), (x_test, y_test) = tf.keras.datasets.mnist.load_data()


# Reshaping the array to 4-dims so that it can work with the Keras API
x_train = x_train.reshape(x_train.shape[0], 28, 28, 1)
x_test = x_test.reshape(x_test.shape[0], 28, 28, 1)
input_shape = (28, 28, 1)
# Making sure that the values are float so that we can get decimal points after division
x_train = x_train.astype('float32')
x_test = x_test.astype('float32')
# Normalizing the RGB codes by dividing it to the max RGB value.
x_train /= 255
x_test /= 255
print('x_train shape:', x_train.shape)
print('Number of images in x_train', x_train.shape[0])
print('Number of images in x_test', x_test.shape[0])
# Importing the required Keras modules containing model and layers


def train():
    # Creating a Sequential Model and adding the layers
    model = Sequential()
    model.add(Conv2D(28, kernel_size=(3,3), input_shape=input_shape))
    model.add(MaxPooling2D(pool_size=(2, 2)))
    model.add(Flatten()) # Flattening the 2D arrays for fully connected layers
    model.add(Dense(128, activation=tf.nn.relu))
    model.add(Dropout(0.2))
    model.add(Dense(10, activation=tf.nn.softmax))

    model.compile(optimizer='adam',
                  loss='sparse_categorical_crossentropy',
                  metrics=['accuracy'])
    model.fit(x=x_train,y=y_train, epochs=10)
    print(model.summary())
    model.save('x.h5')


def eval():
    model = load_model('x.h5')
    scores = model.evaluate(x_test, y_test, verbose=0)
    print("Accuracy: %.2f%%" % (scores[1]*100))


train()
eval()

我得到了一个错误：

ValueError: Unknown activation function:softmax_v2

我尝试使用不同的 tensorflow 版本（1.15、2.0、1.5），但这并没有改变。有什么想法有什么问题吗？编辑：仅当我尝试加载模型时才会出现此问题。

4

0 回答 0