Configuration

Sionna’s configuration API. It can be used to set global variables which can be used by all modules and functions.

class sionna.Config

The Sionna configuration class.

This class is used to define global configuration variables that can be accessed from all modules and functions. It is instantiated in sionna.__init__() and its properties can be accessed as sionna.config.desired_property.

property xla_compat

Ensure that functions execute in an XLA compatible way.

Not all TensorFlow ops support the three execution modes for all dtypes: Eager, Graph, and Graph with XLA. For this reason, some functions are implemented differently depending on the execution mode. As it is currently impossible to programmatically determine if a function is executed in Graph or Graph with XLA mode, the xla_compat property can be used to indicate which execution mode is desired. Note that most functions will work in all execution modes independently of the value of this property.

This property can be used like this:

import sionna
sionna.config.xla_compat=True
@tf.function(jit_compile=True)
def func()
    # Implementation

func()

Type

bool