Menu
The docs say:
In addition, variants of these types with the _ref suffix are defined for reference-typed tensors.
What exactly does this mean? What are reference-typed tensors and how do they differ from standard ones?
293
Tensors v.s. Variables A variable in Tensorflow is also a wrapper around a tensor, but has a different meaning. A variable contains a tensor that is persistent and changeable across different Session.
EagreTensor represents a tensor who's value has been calculated in eager mode whereas Tensor represents a tensor node in a graph that may not yet have been calculated.
Each operation you will do with TensorFlow involves the manipulation of a tensor. There are four main tensor type you can create: tf.
A tensor is a generalization of vectors and matrices to potentially higher dimensions. Internally, TensorFlow represents tensors as n-dimensional arrays of base datatypes. Each element in the Tensor has the same data type, and the data type is always known.
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().
(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.)
124
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With
