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Copy file name to clipboardexpand all lines: doc/sphinx/docs/python/tutorials/coding_udi.rst
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@@ -47,7 +47,7 @@ That was easy! Lets now understand what we actually did. The object ``isl`` now
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But there is a catch. We are in python! So it is not possible, in general, to have the same interpreter execute instructions in parallel as,
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in most of the popular python language implementations, memory management is not thread-safe. So, while the code above is perfectly fine and will
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work with pygmo, a set of ``my_isl`` running evolutions will not run in parallel as each :class:`~pygmo.island`, when executing its :func:`~pygmo.island.evolve()`
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acquires the GIL (Global Interpreter Lock) and holds it during the :func:`~pygmo.island.evolve()` execution.
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method, acquires the GIL (Global Interpreter Lock) and holds it during the :func:`~pygmo.island.evolve()` execution.
Copy file name to clipboardexpand all lines: doc/sphinx/docs/python/tutorials/using_archipelago.rst
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@@ -91,7 +91,7 @@ assemble an archipelago, the user can instantiate an empty archipelago and use t
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.. note::
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The island type selected by the :class:`~pygmo.archipelago` constructor is, in this case, the
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``Multiprocessing island``, (:class:`pygmo.py_islands.mp_island`) as we run this example on py36 and
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``multiprocessing island``, (:class:`pygmo.mp_island`) as we run this example on py36 and
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a linux machine. In general, the exact island chosen is platform, population and algorithm
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dependent and such choice is described in the docs of the :class:`~pygmo.island` class constructor.
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7 Multiprocessing island Self-adaptive constraints handling A toy problem 50 busy
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...
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Note how the evolution is happening in parallel on 32 separate threads (each one spawning a process, in this case, as a Multiprocessing island is used).
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Note how the evolution is happening in parallel on 32 separate threads (each one spawning a process, in this case, as a multiprocessing island is used).
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The evolution happens asynchronously and thus does not interfere directly with our main process. We then have to call the :func:`pygmo.archipelago.wait()`
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method to have the main process explicitly wait for all islands to be finished.
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@@ -158,7 +158,7 @@ constructed using random seeds.
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Managing exceptions
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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What happens if, during the optimization task sent to an :class:`~pygmo.island`, an exception happens? This question is already explored
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in the :ref:`py_tutorial_using_island` and since an :class:`~pygmo.archipelago` is, basically, a container for multiple :class:`~pygmo.island`
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in the :ref:`island tutorial<py_tutorial_using_island>` and since an :class:`~pygmo.archipelago` is, basically, a container for multiple :class:`~pygmo.island`
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here we will overlap with part of that tutorial, exploring exceptions thrown in the :class:`~pygmo.archipelago` context.
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To show how pygmo handles these situations we use the fake problem below throwing as soon as 300 fitness evaluations are made.
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