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Merged
ryanmrichard merged 2 commits into from
Apr 22, 2025
Merged

Buffer API update #141

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6f2967b
update to new buffer API
jwaldrop107 Apr 22, 2025
fd1b1c8
Committing clang-format changes
github-actions[bot] Apr 22, 2025
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8 changes: 5 additions & 3 deletions src/integrals/ao_integrals/coulomb_metric.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -30,7 +30,7 @@ struct Kernel {
// Unwrap buffer info
tensorwrapper::allocator::Eigen<FloatType> allocator(rv);
const auto& eigen_I = allocator.rebind(I);
const auto* pI = eigen_I.data();
const auto* pI = eigen_I.get_immutable_data();
const auto& shape_I = eigen_I.layout().shape().as_smooth();
auto rows = shape_I.extent(0);
auto cols = shape_I.extent(1);
Expand All @@ -49,8 +49,10 @@ struct Kernel {
tensorwrapper::shape::Smooth matrix_shape{rows, cols};
tensorwrapper::layout::Physical matrix_layout(matrix_shape);
auto pM_buffer = allocator.allocate(matrix_layout);
for(auto i = 0; i < rows; ++i) {
for(auto j = 0; j < cols; ++j) { pM_buffer->at(i, j) = Linv(i, j); }
for(decltype(rows) i = 0; i < rows; ++i) {
for(decltype(cols) j = 0; j < cols; ++j) {
pM_buffer->set_elem({i, j}, Linv(i, j));
}
}
return simde::type::tensor(matrix_shape, std::move(pM_buffer));
}
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6 changes: 3 additions & 3 deletions src/integrals/ao_integrals/uq_driver.cpp
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Expand Up @@ -34,9 +34,9 @@ struct Kernel {

auto rv_buffer = alloc.allocate(t_eigen.layout());
for(std::size_t i = 0; i < t_eigen.size(); ++i) {
const auto elem = (t_eigen.data() + i)->mean();
const auto elem_error = (error_eigen.data() + i)->mean();
*(rv_buffer->data() + i) = FloatType(elem, elem_error);
const auto elem = t_eigen.get_data(i).mean();
const auto elem_error = error_eigen.get_data(i).mean();
rv_buffer->set_data(i, FloatType(elem, elem_error));
}

const auto& shape = t_eigen.layout().shape();
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3 changes: 2 additions & 1 deletion src/integrals/libint/libint.cpp
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Expand Up @@ -75,7 +75,8 @@ auto fill_tensor(const std::vector<libint2::BasisSet>& basis_sets,
auto ord = detail_::shells2ord(basis_sets, shells);
auto n_ord = ord.size();
for(decltype(n_ord) i_ord = 0; i_ord < n_ord; ++i_ord) {
pbuffer->data()[ord[i_ord]] += vals[i_ord];
auto update = pbuffer->get_data(ord[i_ord]) + vals[i_ord];
pbuffer->set_data(ord[i_ord], update);
}
}

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18 changes: 9 additions & 9 deletions tests/cxx/unit/integrals/ao_integrals/ao_integrals_driver.cpp
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Expand Up @@ -26,15 +26,15 @@ void compare_matrices(const tensor& A, const tensor& A_corr) {
const auto& A_corr_buffer = alloc_type::rebind(A_corr.buffer());

const auto tol = 1E-6;
auto A00 = A_buffer.at(0, 0);
auto A01 = A_buffer.at(0, 1);
auto A10 = A_buffer.at(1, 0);
auto A11 = A_buffer.at(1, 1);

REQUIRE(A00 == Catch::Approx(A_corr_buffer.at(0, 0)).margin(tol));
REQUIRE(A01 == Catch::Approx(A_corr_buffer.at(0, 1)).margin(tol));
REQUIRE(A10 == Catch::Approx(A_corr_buffer.at(1, 0)).margin(tol));
REQUIRE(A11 == Catch::Approx(A_corr_buffer.at(1, 1)).margin(tol));
auto A00 = A_buffer.get_elem({0, 0});
auto A01 = A_buffer.get_elem({0, 1});
auto A10 = A_buffer.get_elem({1, 0});
auto A11 = A_buffer.get_elem({1, 1});

REQUIRE(A00 == Catch::Approx(A_corr_buffer.get_elem({0, 0})).margin(tol));
REQUIRE(A01 == Catch::Approx(A_corr_buffer.get_elem({0, 1})).margin(tol));
REQUIRE(A10 == Catch::Approx(A_corr_buffer.get_elem({1, 0})).margin(tol));
REQUIRE(A11 == Catch::Approx(A_corr_buffer.get_elem({1, 1})).margin(tol));
}

} // namespace
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36 changes: 18 additions & 18 deletions tests/cxx/unit/integrals/ao_integrals/test_uq_driver.cpp
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Expand Up @@ -22,24 +22,24 @@ auto corr_answer(const simde::type::tensor& T) {
return T;
} else {
simde::type::tensor T_corr(T);
using alloc_type = tensorwrapper::allocator::Eigen<FloatType>;
auto& corr_buffer = alloc_type::rebind(T_corr.buffer());
corr_buffer.at(0, 0, 0, 0) = FloatType{0.774606, 0};
corr_buffer.at(0, 0, 0, 1) = FloatType{0.265558, 2.49687e-06};
corr_buffer.at(0, 0, 1, 0) = FloatType{0.265558, 2.49687e-06};
corr_buffer.at(0, 0, 1, 1) = FloatType{0.446701, 0};
corr_buffer.at(0, 1, 0, 0) = FloatType{0.265558, 2.49687e-06};
corr_buffer.at(0, 1, 0, 1) = FloatType{0.120666, 1.10748e-05};
corr_buffer.at(0, 1, 1, 0) = FloatType{0.120666, 1.10748e-05};
corr_buffer.at(0, 1, 1, 1) = FloatType{0.265558, 2.49687e-06};
corr_buffer.at(1, 0, 0, 0) = FloatType{0.265558, 2.49687e-06};
corr_buffer.at(1, 0, 0, 1) = FloatType{0.120666, 1.10748e-05};
corr_buffer.at(1, 0, 1, 0) = FloatType{0.120666, 1.10748e-05};
corr_buffer.at(1, 0, 1, 1) = FloatType{0.265558, 2.49687e-06};
corr_buffer.at(1, 1, 0, 0) = FloatType{0.446701, 0};
corr_buffer.at(1, 1, 0, 1) = FloatType{0.265558, 2.49687e-06};
corr_buffer.at(1, 1, 1, 0) = FloatType{0.265558, 2.49687e-06};
corr_buffer.at(1, 1, 1, 1) = FloatType{0.774606, 0};
using alloc_type = tensorwrapper::allocator::Eigen<FloatType>;
auto& corr_buffer = alloc_type::rebind(T_corr.buffer());
corr_buffer.set_elem({0, 0, 0, 0}, FloatType{0.774606, 0});
corr_buffer.set_elem({0, 0, 0, 1}, FloatType{0.265558, 2.49687e-06});
corr_buffer.set_elem({0, 0, 1, 0}, FloatType{0.265558, 2.49687e-06});
corr_buffer.set_elem({0, 0, 1, 1}, FloatType{0.446701, 0});
corr_buffer.set_elem({0, 1, 0, 0}, FloatType{0.265558, 2.49687e-06});
corr_buffer.set_elem({0, 1, 0, 1}, FloatType{0.120666, 1.10748e-05});
corr_buffer.set_elem({0, 1, 1, 0}, FloatType{0.120666, 1.10748e-05});
corr_buffer.set_elem({0, 1, 1, 1}, FloatType{0.265558, 2.49687e-06});
corr_buffer.set_elem({1, 0, 0, 0}, FloatType{0.265558, 2.49687e-06});
corr_buffer.set_elem({1, 0, 0, 1}, FloatType{0.120666, 1.10748e-05});
corr_buffer.set_elem({1, 0, 1, 0}, FloatType{0.120666, 1.10748e-05});
corr_buffer.set_elem({1, 0, 1, 1}, FloatType{0.265558, 2.49687e-06});
corr_buffer.set_elem({1, 1, 0, 0}, FloatType{0.446701, 0});
corr_buffer.set_elem({1, 1, 0, 1}, FloatType{0.265558, 2.49687e-06});
corr_buffer.set_elem({1, 1, 1, 0}, FloatType{0.265558, 2.49687e-06});
corr_buffer.set_elem({1, 1, 1, 1}, FloatType{0.774606, 0});
return T_corr;
}
}
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2 changes: 1 addition & 1 deletion tests/cxx/unit/integrals/testing.hpp
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Expand Up @@ -33,7 +33,7 @@ auto eigen_tensor_(const tensorwrapper::buffer::BufferBase& buffer,
std::array<int, N> extents, std::index_sequence<Is...>) {
const auto& b = tensorwrapper::allocator::Eigen<FloatType>::rebind(buffer);
using eigen_type = Eigen::Tensor<const FloatType, N, Eigen::RowMajor>;
return Eigen::TensorMap<eigen_type>(b.data(), extents[Is]...);
return Eigen::TensorMap<eigen_type>(b.get_immutable_data(), extents[Is]...);
}

// Checking eigen outputs
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