ext: Updated Pybind11 to version 2.4.1.

This updates Pybind11 from version 2.2.1 to version 2.4.1. This fixes
warning/error received when "<experiment/optional>" is used when
compiling using c++14 with clang. It should be noted that
"ext/pybind11/include/pybind11/std.h" has been changed to include a fix
added by commit ba42457254cc362eddc099f22b60d469cc6369e0. This is
necessary to avoid build errors.

Built: Linux (gcc, c++11) and MacOS (clang, c++14).
Tested: Ran quick tests for X86, ARM, and RISC-V.
Deprecates: https://gem5-review.googlesource.com/c/public/gem5/+/21019
Change-Id: Ie9783511cb6be50136076a55330e645f4f36d075
Reviewed-on: https://gem5-review.googlesource.com/c/public/gem5/+/21119
Reviewed-by: Jason Lowe-Power <jason@lowepower.com>
Reviewed-by: Andreas Sandberg <andreas.sandberg@arm.com>
Maintainer: Jason Lowe-Power <jason@lowepower.com>
Maintainer: Andreas Sandberg <andreas.sandberg@arm.com>
Tested-by: kokoro <noreply+kokoro@google.com>

5 files changed, 16 insertions, 15 deletions

diff --git a/ext/pybind11/docs/advanced/cast/chrono.rst b/ext/pybind11/docs/advanced/cast/chrono.rst
index 8c6b3d7e5..fbd46057a 100644
--- a/ext/pybind11/docs/advanced/cast/chrono.rst
+++ b/ext/pybind11/docs/advanced/cast/chrono.rst
@@ -59,7 +59,7 @@ Provided conversions
 
 .. rubric:: Python to C++
 
-- ``datetime.datetime`` → ``std::chrono::system_clock::time_point``
+- ``datetime.datetime`` or ``datetime.date`` or ``datetime.time`` → ``std::chrono::system_clock::time_point``
     Date/time objects are converted into system clock timepoints. Any
     timezone information is ignored and the type is treated as a naive
     object.
diff --git a/ext/pybind11/docs/advanced/cast/eigen.rst b/ext/pybind11/docs/advanced/cast/eigen.rst
index acdb51de6..59ba08c3c 100644
--- a/ext/pybind11/docs/advanced/cast/eigen.rst
+++ b/ext/pybind11/docs/advanced/cast/eigen.rst
@@ -37,11 +37,11 @@ that maps into the source ``numpy.ndarray`` data: this requires both that the
 data types are the same (e.g. ``dtype='float64'`` and ``MatrixType::Scalar`` is
 ``double``); and that the storage is layout compatible.  The latter limitation
 is discussed in detail in the section below, and requires careful
-consideration: by default, numpy matrices and eigen matrices are *not* storage
+consideration: by default, numpy matrices and Eigen matrices are *not* storage
 compatible.
 
 If the numpy matrix cannot be used as is (either because its types differ, e.g.
-passing an array of integers to an Eigen paramater requiring doubles, or
+passing an array of integers to an Eigen parameter requiring doubles, or
 because the storage is incompatible), pybind11 makes a temporary copy and
 passes the copy instead.
 
@@ -89,7 +89,7 @@ as dictated by the binding function's return value policy (see the
 documentation on :ref:`return_value_policies` for full details).  That means,
 without an explicit return value policy, lvalue references will be copied and
 pointers will be managed by pybind11.  In order to avoid copying, you should
-explictly specify an appropriate return value policy, as in the following
+explicitly specify an appropriate return value policy, as in the following
 example:
 
 .. code-block:: cpp
@@ -226,7 +226,7 @@ order.
 Failing rather than copying
 ===========================
 
-The default behaviour when binding ``Eigen::Ref<const MatrixType>`` eigen
+The default behaviour when binding ``Eigen::Ref<const MatrixType>`` Eigen
 references is to copy matrix values when passed a numpy array that does not
 conform to the element type of ``MatrixType`` or does not have a compatible
 stride layout.  If you want to explicitly avoid copying in such a case, you
@@ -275,7 +275,7 @@ Vectors versus column/row matrices
 Eigen and numpy have fundamentally different notions of a vector.  In Eigen, a
 vector is simply a matrix with the number of columns or rows set to 1 at
 compile time (for a column vector or row vector, respectively).  Numpy, in
-contast, has comparable 2-dimensional 1xN and Nx1 arrays, but *also* has
+contrast, has comparable 2-dimensional 1xN and Nx1 arrays, but *also* has
 1-dimensional arrays of size N.
 
 When passing a 2-dimensional 1xN or Nx1 array to Eigen, the Eigen type must
@@ -287,15 +287,15 @@ On the other hand, pybind11 allows you to pass 1-dimensional arrays of length N
 as Eigen parameters.  If the Eigen type can hold a column vector of length N it
 will be passed as such a column vector.  If not, but the Eigen type constraints
 will accept a row vector, it will be passed as a row vector.  (The column
-vector takes precendence when both are supported, for example, when passing a
+vector takes precedence when both are supported, for example, when passing a
 1D numpy array to a MatrixXd argument).  Note that the type need not be
-expicitly a vector: it is permitted to pass a 1D numpy array of size 5 to an
+explicitly a vector: it is permitted to pass a 1D numpy array of size 5 to an
 Eigen ``Matrix<double, Dynamic, 5>``: you would end up with a 1x5 Eigen matrix.
 Passing the same to an ``Eigen::MatrixXd`` would result in a 5x1 Eigen matrix.
 
-When returning an eigen vector to numpy, the conversion is ambiguous: a row
+When returning an Eigen vector to numpy, the conversion is ambiguous: a row
 vector of length 4 could be returned as either a 1D array of length 4, or as a
-2D array of size 1x4.  When encoutering such a situation, pybind11 compromises
+2D array of size 1x4.  When encountering such a situation, pybind11 compromises
 by considering the returned Eigen type: if it is a compile-time vector--that
 is, the type has either the number of rows or columns set to 1 at compile
 time--pybind11 converts to a 1D numpy array when returning the value.  For
diff --git a/ext/pybind11/docs/advanced/cast/overview.rst b/ext/pybind11/docs/advanced/cast/overview.rst
index 2ac7d3009..b0e32a52f 100644
--- a/ext/pybind11/docs/advanced/cast/overview.rst
+++ b/ext/pybind11/docs/advanced/cast/overview.rst
@@ -131,6 +131,8 @@ as arguments and return values, refer to the section on binding :ref:`classes`.
 +------------------------------------+---------------------------+-------------------------------+
 | ``std::vector<T>``                 | STL dynamic array         | :file:`pybind11/stl.h`        |
 +------------------------------------+---------------------------+-------------------------------+
+| ``std::deque<T>``                  | STL double-ended queue    | :file:`pybind11/stl.h`        |
++------------------------------------+---------------------------+-------------------------------+
 | ``std::valarray<T>``               | STL value array           | :file:`pybind11/stl.h`        |
 +------------------------------------+---------------------------+-------------------------------+
 | ``std::list<T>``                   | STL linked list           | :file:`pybind11/stl.h`        |
diff --git a/ext/pybind11/docs/advanced/cast/stl.rst b/ext/pybind11/docs/advanced/cast/stl.rst
index 3f30c0290..e48409f02 100644
--- a/ext/pybind11/docs/advanced/cast/stl.rst
+++ b/ext/pybind11/docs/advanced/cast/stl.rst
@@ -5,7 +5,7 @@ Automatic conversion
 ====================
 
 When including the additional header file :file:`pybind11/stl.h`, conversions
-between ``std::vector<>``/``std::list<>``/``std::array<>``,
+between ``std::vector<>``/``std::deque<>``/``std::list<>``/``std::array<>``,
 ``std::set<>``/``std::unordered_set<>``, and
 ``std::map<>``/``std::unordered_map<>`` and the Python ``list``, ``set`` and
 ``dict`` data structures are automatically enabled. The types ``std::pair<>``
@@ -175,9 +175,6 @@ in Python, and to define a set of available operations, e.g.:
         }, py::keep_alive<0, 1>()) /* Keep vector alive while iterator is used */
         // ....
 
-Please take a look at the :ref:`macro_notes` before using the
-``PYBIND11_MAKE_OPAQUE`` macro.
-
 .. seealso::
 
     The file :file:`tests/test_opaque_types.cpp` contains a complete
diff --git a/ext/pybind11/docs/advanced/cast/strings.rst b/ext/pybind11/docs/advanced/cast/strings.rst
index 2cdbade3a..e25701eca 100644
--- a/ext/pybind11/docs/advanced/cast/strings.rst
+++ b/ext/pybind11/docs/advanced/cast/strings.rst
@@ -58,7 +58,9 @@ Passing bytes to C++
 --------------------
 
 A Python ``bytes`` object will be passed to C++ functions that accept
-``std::string`` or ``char*`` *without* conversion.
+``std::string`` or ``char*`` *without* conversion.  On Python 3, in order to
+make a function *only* accept ``bytes`` (and not ``str``), declare it as taking
+a ``py::bytes`` argument.
 
 
 Returning C++ strings to Python