ext: Upgrade PyBind11 to version 2.1.1

Change-Id: I16870dec402d661295f9d013dc23e362b2b2c169
Signed-off-by: Andreas Sandberg <andreas.sandberg@arm.com>
Reviewed-by: Curtis Dunham <curtis.dunham@arm.com>
Reviewed-on: https://gem5-review.googlesource.com/3225
Reviewed-by: Jason Lowe-Power <jason@lowepower.com>

1 files changed, 89 insertions, 4 deletions

diff --git a/ext/pybind11/tests/test_numpy_vectorize.py b/ext/pybind11/tests/test_numpy_vectorize.py
index 718646efa..7ae777227 100644
--- a/ext/pybind11/tests/test_numpy_vectorize.py
+++ b/ext/pybind11/tests/test_numpy_vectorize.py
@@ -1,10 +1,11 @@
 import pytest
 
+pytestmark = pytest.requires_numpy
+
 with pytest.suppress(ImportError):
     import numpy as np
 
 
-@pytest.requires_numpy
 def test_vectorize(capture):
     from pybind11_tests import vectorized_func, vectorized_func2, vectorized_func3
 
@@ -24,6 +25,20 @@ def test_vectorize(capture):
             my_func(x:int=3, y:float=4, z:float=3)
         """
         with capture:
+            a = np.array([[1, 2], [3, 4]], order='F')
+            b = np.array([[10, 20], [30, 40]], order='F')
+            c = 3
+            result = f(a, b, c)
+            assert np.allclose(result, a * b * c)
+            assert result.flags.f_contiguous
+        # All inputs are F order and full or singletons, so we the result is in col-major order:
+        assert capture == """
+            my_func(x:int=1, y:float=10, z:float=3)
+            my_func(x:int=3, y:float=30, z:float=3)
+            my_func(x:int=2, y:float=20, z:float=3)
+            my_func(x:int=4, y:float=40, z:float=3)
+        """
+        with capture:
             a, b, c = np.array([[1, 3, 5], [7, 9, 11]]), np.array([[2, 4, 6], [8, 10, 12]]), 3
             assert np.allclose(f(a, b, c), a * b * c)
         assert capture == """
@@ -56,9 +71,37 @@ def test_vectorize(capture):
             my_func(x:int=5, y:float=3, z:float=2)
             my_func(x:int=6, y:float=3, z:float=2)
         """
+        with capture:
+            a, b, c = np.array([[1, 2, 3], [4, 5, 6]], order='F'), np.array([[2], [3]]), 2
+            assert np.allclose(f(a, b, c), a * b * c)
+        assert capture == """
+            my_func(x:int=1, y:float=2, z:float=2)
+            my_func(x:int=2, y:float=2, z:float=2)
+            my_func(x:int=3, y:float=2, z:float=2)
+            my_func(x:int=4, y:float=3, z:float=2)
+            my_func(x:int=5, y:float=3, z:float=2)
+            my_func(x:int=6, y:float=3, z:float=2)
+        """
+        with capture:
+            a, b, c = np.array([[1, 2, 3], [4, 5, 6]])[::, ::2], np.array([[2], [3]]), 2
+            assert np.allclose(f(a, b, c), a * b * c)
+        assert capture == """
+            my_func(x:int=1, y:float=2, z:float=2)
+            my_func(x:int=3, y:float=2, z:float=2)
+            my_func(x:int=4, y:float=3, z:float=2)
+            my_func(x:int=6, y:float=3, z:float=2)
+        """
+        with capture:
+            a, b, c = np.array([[1, 2, 3], [4, 5, 6]], order='F')[::, ::2], np.array([[2], [3]]), 2
+            assert np.allclose(f(a, b, c), a * b * c)
+        assert capture == """
+            my_func(x:int=1, y:float=2, z:float=2)
+            my_func(x:int=3, y:float=2, z:float=2)
+            my_func(x:int=4, y:float=3, z:float=2)
+            my_func(x:int=6, y:float=3, z:float=2)
+        """
 
 
-@pytest.requires_numpy
 def test_type_selection():
     from pybind11_tests import selective_func
 
@@ -67,10 +110,52 @@ def test_type_selection():
     assert selective_func(np.array([1.0j], dtype=np.complex64)) == "Complex float branch taken."
 
 
-@pytest.requires_numpy
 def test_docs(doc):
     from pybind11_tests import vectorized_func
 
     assert doc(vectorized_func) == """
-        vectorized_func(arg0: numpy.ndarray[int], arg1: numpy.ndarray[float], arg2: numpy.ndarray[float]) -> object
+        vectorized_func(arg0: numpy.ndarray[int32], arg1: numpy.ndarray[float32], arg2: numpy.ndarray[float64]) -> object
     """  # noqa: E501 line too long
+
+
+def test_trivial_broadcasting():
+    from pybind11_tests import vectorized_is_trivial, trivial, vectorized_func
+
+    assert vectorized_is_trivial(1, 2, 3) == trivial.c_trivial
+    assert vectorized_is_trivial(np.array(1), np.array(2), 3) == trivial.c_trivial
+    assert vectorized_is_trivial(np.array([1, 3]), np.array([2, 4]), 3) == trivial.c_trivial
+    assert trivial.c_trivial == vectorized_is_trivial(
+        np.array([[1, 3, 5], [7, 9, 11]]), np.array([[2, 4, 6], [8, 10, 12]]), 3)
+    assert vectorized_is_trivial(
+        np.array([[1, 2, 3], [4, 5, 6]]), np.array([2, 3, 4]), 2) == trivial.non_trivial
+    assert vectorized_is_trivial(
+        np.array([[1, 2, 3], [4, 5, 6]]), np.array([[2], [3]]), 2) == trivial.non_trivial
+    z1 = np.array([[1, 2, 3, 4], [5, 6, 7, 8]], dtype='int32')
+    z2 = np.array(z1, dtype='float32')
+    z3 = np.array(z1, dtype='float64')
+    assert vectorized_is_trivial(z1, z2, z3) == trivial.c_trivial
+    assert vectorized_is_trivial(1, z2, z3) == trivial.c_trivial
+    assert vectorized_is_trivial(z1, 1, z3) == trivial.c_trivial
+    assert vectorized_is_trivial(z1, z2, 1) == trivial.c_trivial
+    assert vectorized_is_trivial(z1[::2, ::2], 1, 1) == trivial.non_trivial
+    assert vectorized_is_trivial(1, 1, z1[::2, ::2]) == trivial.c_trivial
+    assert vectorized_is_trivial(1, 1, z3[::2, ::2]) == trivial.non_trivial
+    assert vectorized_is_trivial(z1, 1, z3[1::4, 1::4]) == trivial.c_trivial
+
+    y1 = np.array(z1, order='F')
+    y2 = np.array(y1)
+    y3 = np.array(y1)
+    assert vectorized_is_trivial(y1, y2, y3) == trivial.f_trivial
+    assert vectorized_is_trivial(y1, 1, 1) == trivial.f_trivial
+    assert vectorized_is_trivial(1, y2, 1) == trivial.f_trivial
+    assert vectorized_is_trivial(1, 1, y3) == trivial.f_trivial
+    assert vectorized_is_trivial(y1, z2, 1) == trivial.non_trivial
+    assert vectorized_is_trivial(z1[1::4, 1::4], y2, 1) == trivial.f_trivial
+    assert vectorized_is_trivial(y1[1::4, 1::4], z2, 1) == trivial.c_trivial
+
+    assert vectorized_func(z1, z2, z3).flags.c_contiguous
+    assert vectorized_func(y1, y2, y3).flags.f_contiguous
+    assert vectorized_func(z1, 1, 1).flags.c_contiguous
+    assert vectorized_func(1, y2, 1).flags.f_contiguous
+    assert vectorized_func(z1[1::4, 1::4], y2, 1).flags.f_contiguous
+    assert vectorized_func(y1[1::4, 1::4], z2, 1).flags.c_contiguous