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KernelSpec
ImpactModel
aimz.ImpactModel
aimz.ImpactModel.inference
aimz.ImpactModel.kernel
aimz.ImpactModel.kernel_spec
aimz.ImpactModel.param_input
aimz.ImpactModel.param_output
aimz.ImpactModel.posterior
aimz.ImpactModel.rng_key
aimz.ImpactModel.temp_dir
aimz.ImpactModel.vi_result
aimz.ImpactModel.train_on_batch
aimz.ImpactModel.fit_on_batch
aimz.ImpactModel.fit
aimz.ImpactModel.set_posterior_sample
aimz.ImpactModel.is_fitted
aimz.ImpactModel.predict_on_batch
aimz.ImpactModel.predict
aimz.ImpactModel.log_likelihood
aimz.ImpactModel.sample_prior_predictive_on_batch
aimz.ImpactModel.sample_prior_predictive
aimz.ImpactModel.sample
aimz.ImpactModel.sample_posterior_predictive_on_batch
aimz.ImpactModel.sample_posterior_predictive
aimz.ImpactModel.estimate_effect
aimz.ImpactModel.cleanup
aimz.ImpactModel.cleanup_models
ArrayDataset
aimz.utils.data.ArrayDataset
ArrayLoader
aimz.utils.data.ArrayLoader
aimz.utils.data.ArrayLoader.pad_array
MLflow Integration
aimz.mlflow.autolog
aimz.mlflow.get_default_conda_env
aimz.mlflow.get_default_pip_requirements
aimz.mlflow.load_model
aimz.mlflow.log_model
aimz.mlflow.save_model
API Reference
ImpactModel
aimz.ImpactModel.rng_key
aimz.ImpactModel.rng_key
#
property
ImpactModel.
rng_key
:
Array
#
Pseudo-random number generator key.
On this page
ImpactModel.rng_key
Edit on GitHub