解决 FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is d

本文解决了一个在导入TensorFlow时遇到的错误,该错误源于h5py包版本过低。通过升级h5py包,成功解决了问题。

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问题:在执行import tensorflow的时候报出如下错误:

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D:\Anaconda\lib\site-packages\h5py\__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype fromfloattonp.floatingis deprecated. In future, it will be treated asnp.float64 == np.dtype(float).type. from ._conv import register_converters as _register_converters

从错误中可以看错是h5py包问题,初步判断是h5py包版本太低问题,于是考虑升级h5py包:
pip install --upgrade h5py
升级之后问题解决:

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``` !mkdir -p ~/.keras/datasets !cp work/mnist.npz ~/.keras/datasets/ import warnings warnings.filterwarnings("ignore") from keras.datasets import mnist #train_images 和 train_labels 组成了训练集(training set),模型将从这些数据中进行学习。 #然后在测试集(test set,即 test_images 和 test_labels)上对模型进行测试。 (train_images, train_labels), (test_images, test_labels) = mnist.load_data() train_images.shape#看下数据的维度 len(train_labels) train_labels test_images.shape len(test_labels) test_labels from keras import models from keras import layers # 构建神经网络模型 network = models.Sequential() network.add(layers.Dense(512, activation='relu', input_shape=(28 * 28,))) network.add(layers.Dense(10, activation='softmax')) network.compile(optimizer='rmsprop', loss='categorical_crossentropy', metrics=['accuracy']) train_images = train_images.reshape((60000, 28 * 28)) train_images = train_images.astype('float32') / 255 test_images = test_images.reshape((10000, 28 * 28)) test_images = test_images.astype('float32') / 255 from keras.utils import to_categorical train_labels = to_categorical(train_labels) test_labels = to_categorical(test_labels) network.fit(train_images, train_labels, epochs=5, batch_size=128) test_loss, test_acc = network.evaluate(test_images, test_labels) print('test_acc:', test_acc)```/opt/conda/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`. from ._conv import register_converters as _register_converters
最新发布
04-08
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