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.