在 Tensorflow 中，类型以 _ref 结尾的张量和不以 _ref 结尾的张量有什么区别? [英] In Tensorflow, what is the difference between a tensor that has a type ending in _ref and a tensor that does not?

问题描述

文档说:

另外，定义了这些带有_ref后缀的类型的变体用于引用类型的张量.

In addition, variants of these types with the _ref suffix are defined for reference-typed tensors.

这到底是什么意思?什么是引用类型张量，它们与标准张量有何不同?

What exactly does this mean? What are reference-typed tensors and how do they differ from standard ones?

推荐答案

引用类型的张量是可变的.创建引用类型张量的最常见方法是定义一个 tf.Variable:定义一个初始值为 dtype tf.float32 的 tf.Variable 将创建一个引用类型dtype tf.float32_ref 的张量.您可以通过将引用类型张量作为第一个参数传递给 tf.assign() 来改变它.

A reference-typed tensor is mutable. The most common way to create a reference-typed tensor is to define a tf.Variable: defining a tf.Variable whose initial value has dtype tf.float32 will create a reference-typed tensor with dtype tf.float32_ref. You can mutate a reference-typed tensor by passing it as the first argument to tf.assign().

(请注意，引用类型张量是当前 TensorFlow 版本中的一个实现细节.我们鼓励您使用更高级别的包装器，例如 tf.Variable，它可能会迁移到未来可变状态的替代表示.)

(Note that reference-typed tensors are something of an implementation detail in the present version of TensorFlow. We'd encourage you to use higher-level wrappers like tf.Variable, which may migrate to alternative representations for mutable state in the future.)

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