tf.compat.v1.get_variable_scope

Returns the current variable scope.

tf.compat.v1.get_variable_scope()

Migrate to TF2

Caution: This API was designed for TensorFlow v1. Continue reading for details on how to migrate from this API to a native TensorFlow v2 equivalent. See the TensorFlow v1 to TensorFlow v2 migration guide for instructions on how to migrate the rest of your code.

Although it is a legacy compat.v1 api, tf.compat.v1.get_variable is compatible with eager execution and tf.function

However, to maintain variable-scope based variable reuse you will need to combine it with tf.compat.v1.keras.utils.track_tf1_style_variables. (Though it will behave as if reuse is always set to tf.compat.v1.AUTO_REUSE.)

See the migration guide for more info.

The TF2 equivalent, if you are just trying to track variable name prefixes and not control get_variable-based variable reuse, would be to use tf.name_scope and capture the output of opening the scope (which represents the current name prefix).

For example:

x = tf.name_scope('foo') as current_scope:
  ...

Description