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tensor.h
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tensor.h
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/*
pybind11/eigen/tensor.h: Transparent conversion for Eigen tensors
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#pragma once
#include "../numpy.h"
#if defined(__GNUC__) && !defined(__clang__) && !defined(__INTEL_COMPILER)
static_assert(__GNUC__ > 5, "Eigen Tensor support in pybind11 requires GCC > 5.0");
#endif
// Disable warnings for Eigen
PYBIND11_WARNING_PUSH
PYBIND11_WARNING_DISABLE_MSVC(4554)
PYBIND11_WARNING_DISABLE_MSVC(4127)
PYBIND11_WARNING_DISABLE_GCC("-Wmaybe-uninitialized")
#include <unsupported/Eigen/CXX11/Tensor>
PYBIND11_WARNING_POP
static_assert(EIGEN_VERSION_AT_LEAST(3, 3, 0),
"Eigen Tensor support in pybind11 requires Eigen >= 3.3.0");
PYBIND11_NAMESPACE_BEGIN(PYBIND11_NAMESPACE)
PYBIND11_WARNING_DISABLE_MSVC(4127)
PYBIND11_NAMESPACE_BEGIN(detail)
inline bool is_tensor_aligned(const void *data) {
return (reinterpret_cast<std::size_t>(data) % EIGEN_DEFAULT_ALIGN_BYTES) == 0;
}
template <typename T>
constexpr int compute_array_flag_from_tensor() {
static_assert((static_cast<int>(T::Layout) == static_cast<int>(Eigen::RowMajor))
|| (static_cast<int>(T::Layout) == static_cast<int>(Eigen::ColMajor)),
"Layout must be row or column major");
return (static_cast<int>(T::Layout) == static_cast<int>(Eigen::RowMajor)) ? array::c_style
: array::f_style;
}
template <typename T>
struct eigen_tensor_helper {};
template <typename Scalar_, int NumIndices_, int Options_, typename IndexType>
struct eigen_tensor_helper<Eigen::Tensor<Scalar_, NumIndices_, Options_, IndexType>> {
using Type = Eigen::Tensor<Scalar_, NumIndices_, Options_, IndexType>;
using ValidType = void;
static Eigen::DSizes<typename Type::Index, Type::NumIndices> get_shape(const Type &f) {
return f.dimensions();
}
static constexpr bool
is_correct_shape(const Eigen::DSizes<typename Type::Index, Type::NumIndices> & /*shape*/) {
return true;
}
template <typename T>
struct helper {};
template <size_t... Is>
struct helper<index_sequence<Is...>> {
static constexpr auto value = concat(const_name(((void) Is, "?"))...);
};
static constexpr auto dimensions_descriptor
= helper<decltype(make_index_sequence<Type::NumIndices>())>::value;
template <typename... Args>
static Type *alloc(Args &&...args) {
return new Type(std::forward<Args>(args)...);
}
static void free(Type *tensor) { delete tensor; }
};
template <typename Scalar_, typename std::ptrdiff_t... Indices, int Options_, typename IndexType>
struct eigen_tensor_helper<
Eigen::TensorFixedSize<Scalar_, Eigen::Sizes<Indices...>, Options_, IndexType>> {
using Type = Eigen::TensorFixedSize<Scalar_, Eigen::Sizes<Indices...>, Options_, IndexType>;
using ValidType = void;
static constexpr Eigen::DSizes<typename Type::Index, Type::NumIndices>
get_shape(const Type & /*f*/) {
return get_shape();
}
static constexpr Eigen::DSizes<typename Type::Index, Type::NumIndices> get_shape() {
return Eigen::DSizes<typename Type::Index, Type::NumIndices>(Indices...);
}
static bool
is_correct_shape(const Eigen::DSizes<typename Type::Index, Type::NumIndices> &shape) {
return get_shape() == shape;
}
static constexpr auto dimensions_descriptor = concat(const_name<Indices>()...);
template <typename... Args>
static Type *alloc(Args &&...args) {
Eigen::aligned_allocator<Type> allocator;
return ::new (allocator.allocate(1)) Type(std::forward<Args>(args)...);
}
static void free(Type *tensor) {
Eigen::aligned_allocator<Type> allocator;
tensor->~Type();
allocator.deallocate(tensor, 1);
}
};
template <typename Type, bool ShowDetails, bool NeedsWriteable = false>
struct get_tensor_descriptor {
static constexpr auto details
= const_name<NeedsWriteable>(", flags.writeable", "")
+ const_name<static_cast<int>(Type::Layout) == static_cast<int>(Eigen::RowMajor)>(
", flags.c_contiguous", ", flags.f_contiguous");
static constexpr auto value
= const_name("numpy.ndarray[") + npy_format_descriptor<typename Type::Scalar>::name
+ const_name("[") + eigen_tensor_helper<remove_cv_t<Type>>::dimensions_descriptor
+ const_name("]") + const_name<ShowDetails>(details, const_name("")) + const_name("]");
};
// When EIGEN_AVOID_STL_ARRAY is defined, Eigen::DSizes<T, 0> does not have the begin() member
// function. Falling back to a simple loop works around this issue.
//
// We need to disable the type-limits warning for the inner loop when size = 0.
PYBIND11_WARNING_PUSH
PYBIND11_WARNING_DISABLE_GCC("-Wtype-limits")
template <typename T, int size>
std::vector<T> convert_dsizes_to_vector(const Eigen::DSizes<T, size> &arr) {
std::vector<T> result(size);
for (size_t i = 0; i < size; i++) {
result[i] = arr[i];
}
return result;
}
template <typename T, int size>
Eigen::DSizes<T, size> get_shape_for_array(const array &arr) {
Eigen::DSizes<T, size> result;
const T *shape = arr.shape();
for (size_t i = 0; i < size; i++) {
result[i] = shape[i];
}
return result;
}
PYBIND11_WARNING_POP
template <typename Type>
struct type_caster<Type, typename eigen_tensor_helper<Type>::ValidType> {
using Helper = eigen_tensor_helper<Type>;
static constexpr auto temp_name = get_tensor_descriptor<Type, false>::value;
PYBIND11_TYPE_CASTER(Type, temp_name);
bool load(handle src, bool convert) {
if (!convert) {
if (!isinstance<array>(src)) {
return false;
}
array temp = array::ensure(src);
if (!temp) {
return false;
}
if (!temp.dtype().is(dtype::of<typename Type::Scalar>())) {
return false;
}
}
array_t<typename Type::Scalar, compute_array_flag_from_tensor<Type>()> arr(
reinterpret_borrow<object>(src));
if (arr.ndim() != Type::NumIndices) {
return false;
}
auto shape = get_shape_for_array<typename Type::Index, Type::NumIndices>(arr);
if (!Helper::is_correct_shape(shape)) {
return false;
}
#if EIGEN_VERSION_AT_LEAST(3, 4, 0)
auto data_pointer = arr.data();
#else
// Handle Eigen bug
auto data_pointer = const_cast<typename Type::Scalar *>(arr.data());
#endif
if (is_tensor_aligned(arr.data())) {
value = Eigen::TensorMap<const Type, Eigen::Aligned>(data_pointer, shape);
} else {
value = Eigen::TensorMap<const Type>(data_pointer, shape);
}
return true;
}
static handle cast(Type &&src, return_value_policy policy, handle parent) {
if (policy == return_value_policy::reference
|| policy == return_value_policy::reference_internal) {
pybind11_fail("Cannot use a reference return value policy for an rvalue");
}
return cast_impl(&src, return_value_policy::move, parent);
}
static handle cast(const Type &&src, return_value_policy policy, handle parent) {
if (policy == return_value_policy::reference
|| policy == return_value_policy::reference_internal) {
pybind11_fail("Cannot use a reference return value policy for an rvalue");
}
return cast_impl(&src, return_value_policy::move, parent);
}
static handle cast(Type &src, return_value_policy policy, handle parent) {
if (policy == return_value_policy::automatic
|| policy == return_value_policy::automatic_reference) {
policy = return_value_policy::copy;
}
return cast_impl(&src, policy, parent);
}
static handle cast(const Type &src, return_value_policy policy, handle parent) {
if (policy == return_value_policy::automatic
|| policy == return_value_policy::automatic_reference) {
policy = return_value_policy::copy;
}
return cast(&src, policy, parent);
}
static handle cast(Type *src, return_value_policy policy, handle parent) {
if (policy == return_value_policy::automatic) {
policy = return_value_policy::take_ownership;
} else if (policy == return_value_policy::automatic_reference) {
policy = return_value_policy::reference;
}
return cast_impl(src, policy, parent);
}
static handle cast(const Type *src, return_value_policy policy, handle parent) {
if (policy == return_value_policy::automatic) {
policy = return_value_policy::take_ownership;
} else if (policy == return_value_policy::automatic_reference) {
policy = return_value_policy::reference;
}
return cast_impl(src, policy, parent);
}
template <typename C>
static handle cast_impl(C *src, return_value_policy policy, handle parent) {
object parent_object;
bool writeable = false;
switch (policy) {
case return_value_policy::move:
if (std::is_const<C>::value) {
pybind11_fail("Cannot move from a constant reference");
}
src = Helper::alloc(std::move(*src));
parent_object
= capsule(src, [](void *ptr) { Helper::free(reinterpret_cast<Type *>(ptr)); });
writeable = true;
break;
case return_value_policy::take_ownership:
if (std::is_const<C>::value) {
// This cast is ugly, and might be UB in some cases, but we don't have an
// alternative here as we must free that memory
Helper::free(const_cast<Type *>(src));
pybind11_fail("Cannot take ownership of a const reference");
}
parent_object
= capsule(src, [](void *ptr) { Helper::free(reinterpret_cast<Type *>(ptr)); });
writeable = true;
break;
case return_value_policy::copy:
writeable = true;
break;
case return_value_policy::reference:
parent_object = none();
writeable = !std::is_const<C>::value;
break;
case return_value_policy::reference_internal:
// Default should do the right thing
if (!parent) {
pybind11_fail("Cannot use reference internal when there is no parent");
}
parent_object = reinterpret_borrow<object>(parent);
writeable = !std::is_const<C>::value;
break;
default:
pybind11_fail("pybind11 bug in eigen.h, please file a bug report");
}
auto result = array_t<typename Type::Scalar, compute_array_flag_from_tensor<Type>()>(
convert_dsizes_to_vector(Helper::get_shape(*src)), src->data(), parent_object);
if (!writeable) {
array_proxy(result.ptr())->flags &= ~detail::npy_api::NPY_ARRAY_WRITEABLE_;
}
return result.release();
}
};
template <typename StoragePointerType,
bool needs_writeable,
enable_if_t<!needs_writeable, bool> = true>
StoragePointerType get_array_data_for_type(array &arr) {
#if EIGEN_VERSION_AT_LEAST(3, 4, 0)
return reinterpret_cast<StoragePointerType>(arr.data());
#else
// Handle Eigen bug
return reinterpret_cast<StoragePointerType>(const_cast<void *>(arr.data()));
#endif
}
template <typename StoragePointerType,
bool needs_writeable,
enable_if_t<needs_writeable, bool> = true>
StoragePointerType get_array_data_for_type(array &arr) {
return reinterpret_cast<StoragePointerType>(arr.mutable_data());
}
template <typename T, typename = void>
struct get_storage_pointer_type;
template <typename MapType>
struct get_storage_pointer_type<MapType, void_t<typename MapType::StoragePointerType>> {
using SPT = typename MapType::StoragePointerType;
};
template <typename MapType>
struct get_storage_pointer_type<MapType, void_t<typename MapType::PointerArgType>> {
using SPT = typename MapType::PointerArgType;
};
template <typename Type, int Options>
struct type_caster<Eigen::TensorMap<Type, Options>,
typename eigen_tensor_helper<remove_cv_t<Type>>::ValidType> {
using MapType = Eigen::TensorMap<Type, Options>;
using Helper = eigen_tensor_helper<remove_cv_t<Type>>;
bool load(handle src, bool /*convert*/) {
// Note that we have a lot more checks here as we want to make sure to avoid copies
if (!isinstance<array>(src)) {
return false;
}
auto arr = reinterpret_borrow<array>(src);
if ((arr.flags() & compute_array_flag_from_tensor<Type>()) == 0) {
return false;
}
if (!arr.dtype().is(dtype::of<typename Type::Scalar>())) {
return false;
}
if (arr.ndim() != Type::NumIndices) {
return false;
}
constexpr bool is_aligned = (Options & Eigen::Aligned) != 0;
if (is_aligned && !is_tensor_aligned(arr.data())) {
return false;
}
auto shape = get_shape_for_array<typename Type::Index, Type::NumIndices>(arr);
if (!Helper::is_correct_shape(shape)) {
return false;
}
if (needs_writeable && !arr.writeable()) {
return false;
}
auto result = get_array_data_for_type<typename get_storage_pointer_type<MapType>::SPT,
needs_writeable>(arr);
value.reset(new MapType(std::move(result), std::move(shape)));
return true;
}
static handle cast(MapType &&src, return_value_policy policy, handle parent) {
return cast_impl(&src, policy, parent);
}
static handle cast(const MapType &&src, return_value_policy policy, handle parent) {
return cast_impl(&src, policy, parent);
}
static handle cast(MapType &src, return_value_policy policy, handle parent) {
if (policy == return_value_policy::automatic
|| policy == return_value_policy::automatic_reference) {
policy = return_value_policy::copy;
}
return cast_impl(&src, policy, parent);
}
static handle cast(const MapType &src, return_value_policy policy, handle parent) {
if (policy == return_value_policy::automatic
|| policy == return_value_policy::automatic_reference) {
policy = return_value_policy::copy;
}
return cast(&src, policy, parent);
}
static handle cast(MapType *src, return_value_policy policy, handle parent) {
if (policy == return_value_policy::automatic) {
policy = return_value_policy::take_ownership;
} else if (policy == return_value_policy::automatic_reference) {
policy = return_value_policy::reference;
}
return cast_impl(src, policy, parent);
}
static handle cast(const MapType *src, return_value_policy policy, handle parent) {
if (policy == return_value_policy::automatic) {
policy = return_value_policy::take_ownership;
} else if (policy == return_value_policy::automatic_reference) {
policy = return_value_policy::reference;
}
return cast_impl(src, policy, parent);
}
template <typename C>
static handle cast_impl(C *src, return_value_policy policy, handle parent) {
object parent_object;
constexpr bool writeable = !std::is_const<C>::value;
switch (policy) {
case return_value_policy::reference:
parent_object = none();
break;
case return_value_policy::reference_internal:
// Default should do the right thing
if (!parent) {
pybind11_fail("Cannot use reference internal when there is no parent");
}
parent_object = reinterpret_borrow<object>(parent);
break;
case return_value_policy::take_ownership:
delete src;
// fallthrough
default:
// move, take_ownership don't make any sense for a ref/map:
pybind11_fail("Invalid return_value_policy for Eigen Map type, must be either "
"reference or reference_internal");
}
auto result = array_t<typename Type::Scalar, compute_array_flag_from_tensor<Type>()>(
convert_dsizes_to_vector(Helper::get_shape(*src)),
src->data(),
std::move(parent_object));
if (!writeable) {
array_proxy(result.ptr())->flags &= ~detail::npy_api::NPY_ARRAY_WRITEABLE_;
}
return result.release();
}
#if EIGEN_VERSION_AT_LEAST(3, 4, 0)
static constexpr bool needs_writeable = !std::is_const<typename std::remove_pointer<
typename get_storage_pointer_type<MapType>::SPT>::type>::value;
#else
// Handle Eigen bug
static constexpr bool needs_writeable = !std::is_const<Type>::value;
#endif
protected:
// TODO: Move to std::optional once std::optional has more support
std::unique_ptr<MapType> value;
public:
static constexpr auto name = get_tensor_descriptor<Type, true, needs_writeable>::value;
explicit operator MapType *() { return value.get(); }
explicit operator MapType &() { return *value; }
explicit operator MapType &&() && { return std::move(*value); }
template <typename T_>
using cast_op_type = ::pybind11::detail::movable_cast_op_type<T_>;
};
PYBIND11_NAMESPACE_END(detail)
PYBIND11_NAMESPACE_END(PYBIND11_NAMESPACE)