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:py:mod:`tlm_adjoint.checkpoint_schedules.mixed`
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.. py:module:: tlm_adjoint.checkpoint_schedules.mixed


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

.. py:class:: MixedCheckpointSchedule(max_n, snapshots, *, storage='disk')




   
   A checkpointing schedule which mixes storage of forward restart data and
   non-linear dependency data in checkpointing units. Assumes that the data
   required to restart the forward has the same size as the data required to
   advance the adjoint over a step.

   Described in

       - James R. Maddison, 'Step-based checkpointing with high-level
         algorithmic differentiation', Journal of Computational Science 82,
         102405, 2024, doi: 10.1016/j.jocs.2024.102405

   Offline, one adjoint calculation permitted.

   :arg max_n: The number of forward steps in the initial forward calculation.
   :arg snapshots: The number of available checkpointing units.
   :arg storage: Checkpointing unit storage location. Either `'RAM'` or
       `'disk'`.















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   .. py:property:: is_exhausted

      
      Whether the schedule has concluded. Note that some schedules permit
      multiple adjoint calculation, and may never conclude.
















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   .. py:property:: uses_disk_storage

      
      Whether the schedule may use disk storage. If `False` then no disk
      storage is required.
















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   .. py:method:: iter()

      
      A generator which should be overridden in derived classes in order
      to define a checkpointing schedule.
















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