Run config#

Settings for how to run zfit.

`zfit.run.set_graph_mode`()	Set the policy for graph building and the usage of automatic vs numerical gradients.
`zfit.run.set_autograd_mode`()	Use automatic or numerical gradients.
`zfit.run.clear_graph_cache`()	Clear all generated graphs and effectively reset.
`zfit.run.executing_eagerly`()	Whether eager execution is enabled.
`zfit.run.assert_executing_eagerly`()	Assert that the execution is eager and Python side effects are taken into account.
`zfit.run.set_n_cpu`([strict])	Set the number of cpus to be used by zfit.
`zfit.run.set_cpus_explicit`(inter)	Set the number of threads (cpus) used for inter-op and intra-op parallelism.

Settings#

General settings for zfit

zfit.settings.set_seed(seed=None, numpy=None, backend=None)[source]#

Set random seed for zfit, numpy and the backend. The seed isn’t directly set but used to generate a seed for each of the three.

Parameters:

seed (int, optional) – Seed to set for the random number generator of the seeds for within zfit. If None (default), the seed is set to a random value.
numpy (int, bool, optional) – Seed to set for numpy. If True (default), a random seed depending on the seed as used for zfit is used. If False, the seed is not set.
backend (int, bool, optional) – Seed to set for the backend. If True (default), a random seed depending on the seed as used for zfit is used. If False, the seed is not set.