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274 lines (240 loc) · 8.36 KB
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/***************************************************************************
* Copyright (c) Wolf Vollprecht, Johan Mabille and Sylvain Corlay *
* Copyright (c) QuantStack *
* *
* Distributed under the terms of the BSD 3-Clause License. *
* *
* The full license is in the file LICENSE, distributed with this software. *
****************************************************************************/
#include "gtest/gtest.h"
#include "xtensor-python/pytensor.hpp"
#include "xtensor/containers/xtensor.hpp"
#include "xtensor/views/xview.hpp"
#include "test_common.hpp"
namespace xt
{
using container_type = std::array<npy_intp, 3>;
TEST(pytensor, initializer_constructor)
{
pytensor<int, 3> t
{{{ 0, 1, 2},
{ 3, 4, 5},
{ 6, 7, 8}},
{{ 9, 10, 11},
{12, 13, 14},
{15, 16, 17}}};
EXPECT_EQ(t.dimension(), 3);
EXPECT_EQ(t(0, 0, 1), 1);
EXPECT_EQ(t.shape()[0], 2);
}
TEST(pytensor, shaped_constructor)
{
{
SCOPED_TRACE("row_major constructor");
row_major_result<container_type> rm;
pytensor<int, 3> ra(rm.m_shape);
compare_shape(ra, rm);
EXPECT_EQ(layout_type::row_major, ra.layout());
}
{
SCOPED_TRACE("column_major constructor");
column_major_result<container_type> cm;
pytensor<int, 3> ca(cm.m_shape, layout_type::column_major);
compare_shape(ca, cm);
EXPECT_EQ(layout_type::column_major, ca.layout());
}
}
TEST(pytensor, from_shape)
{
auto arr = pytensor<double, 3>::from_shape({5, 2, 6});
auto exp_shape = std::vector<std::size_t>{5, 2, 6};
EXPECT_TRUE(std::equal(arr.shape().begin(), arr.shape().end(), exp_shape.begin()));
EXPECT_EQ(arr.shape().size(), 3);
EXPECT_EQ(arr.size(), 5 * 2 * 6);
using pyt3 = pytensor<double, 3>;
std::vector<std::size_t> shp = std::vector<std::size_t>{5, 2};
EXPECT_THROW(pyt3::from_shape(shp), std::runtime_error);
}
TEST(pytensor, scalar_from_shape)
{
std::array<size_t, 0> shape;
auto a = pytensor<double, 0>::from_shape(shape);
pytensor<double, 0> b(1.2);
EXPECT_TRUE(a.size() == b.size());
EXPECT_TRUE(xt::has_shape(a, b.shape()));
}
TEST(pytensor, strided_constructor)
{
central_major_result<container_type> cmr;
pytensor<int, 3> cma(cmr.m_shape, cmr.m_strides);
compare_shape(cma, cmr);
}
TEST(pytensor, valued_constructor)
{
{
SCOPED_TRACE("row_major valued constructor");
row_major_result<container_type> rm;
int value = 2;
pytensor<int, 3> ra(rm.m_shape, value);
compare_shape(ra, rm);
std::vector<int> vec(ra.size(), value);
EXPECT_TRUE(std::equal(vec.cbegin(), vec.cend(), ra.storage().cbegin()));
}
{
SCOPED_TRACE("column_major valued constructor");
column_major_result<container_type> cm;
int value = 2;
pytensor<int, 3> ca(cm.m_shape, value, layout_type::column_major);
compare_shape(ca, cm);
std::vector<int> vec(ca.size(), value);
EXPECT_TRUE(std::equal(vec.cbegin(), vec.cend(), ca.storage().cbegin()));
}
}
TEST(pytensor, strided_valued_constructor)
{
central_major_result<container_type> cmr;
int value = 2;
pytensor<int, 3> cma(cmr.m_shape, cmr.m_strides, value);
compare_shape(cma, cmr);
std::vector<int> vec(cma.size(), value);
EXPECT_TRUE(std::equal(vec.cbegin(), vec.cend(), cma.storage().cbegin()));
}
TEST(pytensor, copy_semantic)
{
central_major_result<container_type> res;
int value = 2;
pytensor<int, 3> a(res.m_shape, res.m_strides, value);
{
SCOPED_TRACE("copy constructor");
pytensor<int, 3> b(a);
compare_shape(a, b);
EXPECT_EQ(a.storage(), b.storage());
a.data()[0] += 1;
EXPECT_NE(a.storage()[0], b.storage()[0]);
}
{
SCOPED_TRACE("assignment operator");
row_major_result<container_type> r;
pytensor<int, 3> c(r.m_shape, 0);
EXPECT_NE(a.data(), c.data());
c = a;
compare_shape(a, c);
EXPECT_EQ(a.storage(), c.storage());
a.data()[0] += 1;
EXPECT_NE(a.storage()[0], c.storage()[0]);
}
}
TEST(pytensor, move_semantic)
{
central_major_result<container_type> res;
int value = 2;
pytensor<int, 3> a(res.m_shape, res.m_strides, value);
{
SCOPED_TRACE("move constructor");
pytensor<int, 3> tmp(a);
pytensor<int, 3> b(std::move(tmp));
compare_shape(a, b);
EXPECT_EQ(a.storage(), b.storage());
}
{
SCOPED_TRACE("move assignment");
row_major_result<container_type> r;
pytensor<int, 3> c(r.m_shape, 0);
EXPECT_NE(a.storage(), c.storage());
pytensor<int, 3> tmp(a);
c = std::move(tmp);
compare_shape(a, c);
EXPECT_EQ(a.storage(), c.storage());
}
}
TEST(pytensor, extended_constructor)
{
xt::xtensor<int, 2> a1 = { {1, 2}, {3, 4} };
xt::xtensor<int, 2> a2 = { {1, 2}, {3, 4} };
pytensor<int, 2> c = a1 + a2;
EXPECT_EQ(c(0, 0), a1(0, 0) + a2(0, 0));
EXPECT_EQ(c(0, 1), a1(0, 1) + a2(0, 1));
EXPECT_EQ(c(1, 0), a1(1, 0) + a2(1, 0));
EXPECT_EQ(c(1, 1), a1(1, 1) + a2(1, 1));
}
TEST(pytensor, resize)
{
pytensor<int, 3> a;
test_resize<pytensor<int, 3>, container_type>(a);
pytensor<int, 3> b = { { { 1, 2 },{ 3, 4 } } };
a.resize(b.shape());
EXPECT_EQ(a.shape(), b.shape());
}
TEST(pytensor, transpose)
{
pytensor<int, 3> a;
test_transpose<pytensor<int, 3>, container_type>(a);
}
TEST(pytensor, access)
{
pytensor<int, 3> a;
test_access<pytensor<int, 3>, container_type>(a);
}
TEST(pytensor, indexed_access)
{
pytensor<int, 3> a;
test_indexed_access<pytensor<int, 3>, container_type>(a);
}
TEST(pytensor, broadcast_shape)
{
pytensor<int, 4> a;
test_broadcast(a);
}
TEST(pytensor, iterator)
{
pytensor<int, 3> a;
pytensor<int, 3> b;
test_iterator<pytensor<int, 3>, pytensor<int, 3>, container_type>(a, b);
pytensor<int, 3, layout_type::row_major> c;
bool truthy = std::is_same<decltype(c.begin()), int*>::value;
EXPECT_TRUE(truthy);
}
TEST(pytensor, zerod)
{
pytensor<int, 3> a;
EXPECT_EQ(0, a());
}
TEST(pytensor, reshape)
{
pytensor<int, 2> a = {{1,2,3}, {4,5,6}};
auto ptr = a.data();
a.reshape(a.shape()); // compilation check
a.reshape({1, 6});
EXPECT_EQ(ptr, a.data());
EXPECT_THROW(a.reshape(std::vector<std::size_t>{6}), std::runtime_error);
// note this throws because std array has only 1 element initialized
// and the second element is `0`.
EXPECT_THROW(a.reshape({6, 5}), std::runtime_error);
}
TEST(pytensor, view)
{
xt::pytensor<int, 1> arr = xt::zeros<int>({ 10 });
auto v = xt::view(arr, xt::all());
EXPECT_EQ(v(0), 0.);
}
TEST(pytensor, unary)
{
pytensor<int, 1> a = { 1, 2, 3 };
pytensor<int, 1> res = -a;
pytensor<int, 1> ref = { -1, -2, -3 };
EXPECT_EQ(ref(0), res(0));
EXPECT_EQ(ref(1), res(1));
EXPECT_EQ(ref(1), res(1));
}
TEST(pytensor, inplace_pybind11_overload)
{
// pybind11 overrrides a number of operators in pybind11::object.
// This is testing that the right overload is picked up.
pytensor<double, 1> a = { 1.0, 2.0, 3.0 };
a /= 2;
pytensor<double, 1> ref = { 0.5, 1.0, 1.5 };
EXPECT_EQ(ref(0), a(0));
EXPECT_EQ(ref(1), a(1));
EXPECT_EQ(ref(1), a(1));
}
}