python-3.x - TensorFlow 和 pycharm 自动完成问题

Question

我在 pycharm 和张量流中遇到自动完成问题，我有一个运行完美的示例代码，但是我的 IDE 中的问题无法显示自动完成代码选项。

import tensorflow as tf
import tensorflow_datasets as tfds

Mnist_dataSet, Mnist_Info = tfds.load(name='mnist', with_info=True, as_supervised=True)
Mnist_Train, Mnist_Test = Mnist_dataSet['train'], Mnist_dataSet['test']

num_validation_sample = 0.1 * Mnist_Info.splits['train'].num_examples #No code complete option
num_validation_sample = tf.cast(num_validation_sample, tf.int64)

num_Test_sample =0.1*Mnist_Info.splits['test'].num_examples  #No code complete option
num_Test_sample = tf.cast(num_Test_sample, tf.int64)
.....
......

我知道python是动态编程语言，在声明变量时它声明如下

Mnist_dataSet: Any = tfds.load(name='mnist', with_info=True, as_supervised=True)

我尝试声明这样的变量及其工作

import numpy as np
import tensorflow as tf
import tensorflow_datasets as tfds

Mnist_Info: tfds.core.DatasetInfo
Mnist_dataSet, Mnist_Info = tfds.load(name='mnist', with_info=True, as_supervised=True)
Mnist_Train, Mnist_Test = Mnist_dataSet['train'], Mnist_dataSet['test']

num_validation_sample = 0.1 * Mnist_Info.splits['train'].num_examples
num_validation_sample = tf.cast(num_validation_sample, tf.int64)

num_Test_sample =0.1*Mnist_Info.splits['test'].num_examples
num_Test_sample = tf.cast(num_Test_sample, tf.int64)

是否有任何选项可以让python根据主类自动声明变量？

标签： python-3.xtensorflowdeep-learning