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Change-Id: I52e4fc9ebf2f59da57d8cf8f3e37cc79598c2f5f Signed-off-by: Andreas Sandberg <andreas.sandberg@arm.com> Reviewed-by: Andreas Hansson <andreas.hansson@arm.com> Reviewed-by: Curtis Dunham <curtis.dunham@arm.com> Reviewed-on: https://gem5-review.googlesource.com/2229 Reviewed-by: Tony Gutierrez <anthony.gutierrez@amd.com> Reviewed-by: Jason Lowe-Power <jason@lowepower.com> Reviewed-by: Pierre-Yves Péneau <pierre-yves.peneau@lirmm.fr>
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42 lines
1.5 KiB
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Type conversions
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Apart from enabling cross-language function calls, a fundamental problem
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that a binding tool like pybind11 must address is to provide access to
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native Python types in C++ and vice versa. There are three fundamentally
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different ways to do this—which approach is preferable for a particular type
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depends on the situation at hand.
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1. Use a native C++ type everywhere. In this case, the type must be wrapped
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using pybind11-generated bindings so that Python can interact with it.
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2. Use a native Python type everywhere. It will need to be wrapped so that
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C++ functions can interact with it.
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3. Use a native C++ type on the C++ side and a native Python type on the
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Python side. pybind11 refers to this as a *type conversion*.
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Type conversions are the most "natural" option in the sense that native
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(non-wrapped) types are used everywhere. The main downside is that a copy
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of the data must be made on every Python ↔ C++ transition: this is
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needed since the C++ and Python versions of the same type generally won't
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have the same memory layout.
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pybind11 can perform many kinds of conversions automatically. An overview
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is provided in the table ":ref:`conversion_table`".
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The following subsections discuss the differences between these options in more
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detail. The main focus in this section is on type conversions, which represent
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the last case of the above list.
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.. toctree::
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:maxdepth: 1
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overview
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stl
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functional
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chrono
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eigen
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custom
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