tutorials.examples.train_hypergrid_local_search
===============================================

.. py:module:: tutorials.examples.train_hypergrid_local_search

.. autoapi-nested-parse::

   A version of GFlowNet training that implements local search sampling strategies on the
   HyperGrid environment. This demonstrates how to use more sophisticated sampling
   approaches like local search and Metropolis-Hastings.

   Example usage:
   python train_hypergrid_local_search.py --ndim 2 --height 8 --n_local_search_loops 2 \
       --back_ratio 0.5 --use_metropolis_hastings

   Key features:
   - Implements local search sampling
   - Configurable number of local search loops
   - Adjustable backward step ratio
   - Optional Metropolis-Hastings acceptance criterion
   - Based on TB loss like the train_hypergrid_simple.py example



Attributes
----------

.. autoapisummary::

   tutorials.examples.train_hypergrid_local_search.parser


Functions
---------

.. autoapisummary::

   tutorials.examples.train_hypergrid_local_search.main


Module Contents
---------------

.. py:function:: main(args)

.. py:data:: parser