diff --git a/example/example20.cpp b/example/example20.cpp index 2c24e6dd3..32b50e3d0 100644 --- a/example/example20.cpp +++ b/example/example20.cpp @@ -44,6 +44,19 @@ std::ostream& operator<<(std::ostream& os, const NestedStruct& v) { return os << "n:a=" << v.a << ";b=" << v.b; } +struct PartialStruct { + bool x; + uint32_t y; + float z; + long dummy2; +}; + +struct PartialNestedStruct { + long dummy1; + PartialStruct a; + long dummy2; +}; + struct UnboundStruct { }; template @@ -54,7 +67,7 @@ py::array mkarray_via_buffer(size_t n) { } template -py::array_t create_recarray(size_t n) { +py::array_t create_recarray(size_t n) { auto arr = mkarray_via_buffer(n); auto ptr = static_cast(arr.request().ptr); for (size_t i = 0; i < n; i++) { @@ -67,7 +80,7 @@ std::string get_format_unbound() { return py::format_descriptor::format(); } -py::array_t create_nested(size_t n) { +py::array_t create_nested(size_t n) { auto arr = mkarray_via_buffer(n); auto ptr = static_cast(arr.request().ptr); for (size_t i = 0; i < n; i++) { @@ -77,8 +90,17 @@ py::array_t create_nested(size_t n) { return arr; } +py::array_t create_partial_nested(size_t n) { + auto arr = mkarray_via_buffer(n); + auto ptr = static_cast(arr.request().ptr); + for (size_t i = 0; i < n; i++) { + ptr[i].a.x = i % 2; ptr[i].a.y = (uint32_t) i; ptr[i].a.z = (float) i * 1.5f; + } + return arr; +} + template -void print_recarray(py::array_t arr) { +void print_recarray(py::array_t arr) { auto buf = arr.request(); auto ptr = static_cast(buf.ptr); for (size_t i = 0; i < buf.size; i++) @@ -89,6 +111,8 @@ void print_format_descriptors() { std::cout << py::format_descriptor::format() << std::endl; std::cout << py::format_descriptor::format() << std::endl; std::cout << py::format_descriptor::format() << std::endl; + std::cout << py::format_descriptor::format() << std::endl; + std::cout << py::format_descriptor::format() << std::endl; } void print_dtypes() { @@ -98,16 +122,22 @@ void print_dtypes() { std::cout << to_str(py::dtype_of()) << std::endl; std::cout << to_str(py::dtype_of()) << std::endl; std::cout << to_str(py::dtype_of()) << std::endl; + std::cout << to_str(py::dtype_of()) << std::endl; + std::cout << to_str(py::dtype_of()) << std::endl; } void init_ex20(py::module &m) { PYBIND11_NUMPY_DTYPE(SimpleStruct, x, y, z); PYBIND11_NUMPY_DTYPE(PackedStruct, x, y, z); PYBIND11_NUMPY_DTYPE(NestedStruct, a, b); + PYBIND11_NUMPY_DTYPE(PartialStruct, x, y, z); + PYBIND11_NUMPY_DTYPE(PartialNestedStruct, a); m.def("create_rec_simple", &create_recarray); m.def("create_rec_packed", &create_recarray); m.def("create_rec_nested", &create_nested); + m.def("create_rec_partial", &create_recarray); + m.def("create_rec_partial_nested", &create_partial_nested); m.def("print_format_descriptors", &print_format_descriptors); m.def("print_rec_simple", &print_recarray); m.def("print_rec_packed", &print_recarray); diff --git a/example/example20.py b/example/example20.py index e0a001804..85ea9ae5f 100644 --- a/example/example20.py +++ b/example/example20.py @@ -5,7 +5,8 @@ import unittest import numpy as np from example import ( create_rec_simple, create_rec_packed, create_rec_nested, print_format_descriptors, - print_rec_simple, print_rec_packed, print_rec_nested, print_dtypes, get_format_unbound + print_rec_simple, print_rec_packed, print_rec_nested, print_dtypes, get_format_unbound, + create_rec_partial, create_rec_partial_nested ) @@ -23,6 +24,8 @@ simple_dtype = np.dtype({'names': ['x', 'y', 'z'], 'offsets': [0, 4, 8]}) packed_dtype = np.dtype([('x', '?'), ('y', 'u4'), ('z', 'f4')]) +elements = [(False, 0, 0.0), (True, 1, 1.5), (False, 2, 3.0)] + for func, dtype in [(create_rec_simple, simple_dtype), (create_rec_packed, packed_dtype)]: arr = func(0) assert arr.dtype == dtype @@ -31,14 +34,30 @@ for func, dtype in [(create_rec_simple, simple_dtype), (create_rec_packed, packe arr = func(3) assert arr.dtype == dtype - check_eq(arr, [(False, 0, 0.0), (True, 1, 1.5), (False, 2, 3.0)], simple_dtype) - check_eq(arr, [(False, 0, 0.0), (True, 1, 1.5), (False, 2, 3.0)], packed_dtype) + check_eq(arr, elements, simple_dtype) + check_eq(arr, elements, packed_dtype) if dtype == simple_dtype: print_rec_simple(arr) else: print_rec_packed(arr) + +arr = create_rec_partial(3) +print(arr.dtype) +partial_dtype = arr.dtype +assert '' not in arr.dtype.fields +assert partial_dtype.itemsize > simple_dtype.itemsize +check_eq(arr, elements, simple_dtype) +check_eq(arr, elements, packed_dtype) + +arr = create_rec_partial_nested(3) +print(arr.dtype) +assert '' not in arr.dtype.fields +assert '' not in arr.dtype.fields['a'][0].fields +assert arr.dtype.itemsize > partial_dtype.itemsize +np.testing.assert_equal(arr['a'], create_rec_partial(3)) + nested_dtype = np.dtype([('a', simple_dtype), ('b', packed_dtype)]) arr = create_rec_nested(0) diff --git a/example/example20.ref b/example/example20.ref index 32e2b4b7a..72a6c1858 100644 --- a/example/example20.ref +++ b/example/example20.ref @@ -1,15 +1,21 @@ -T{?:x:xxxI:y:f:z:} -T{?:x:=I:y:f:z:} -T{T{?:x:xxxI:y:f:z:}:a:T{?:x:=I:y:f:z:}:b:} +T{=?:x:3x=I:y:=f:z:} +T{=?:x:=I:y:=f:z:} +T{=T{=?:x:3x=I:y:=f:z:}:a:=T{=?:x:=I:y:=f:z:}:b:} +T{=?:x:3x=I:y:=f:z:12x} +T{8x=T{=?:x:3x=I:y:=f:z:12x}:a:8x} {'names':['x','y','z'], 'formats':['?',' #include #include +#include #include #if defined(_MSC_VER) @@ -26,6 +27,8 @@ NAMESPACE_BEGIN(pybind11) namespace detail { template struct npy_format_descriptor { }; +object fix_dtype(object); + template struct is_pod_struct { enum { value = std::is_pod::value && // offsetof only works correctly for POD types @@ -47,7 +50,9 @@ public: API_PyArray_FromAny = 69, API_PyArray_NewCopy = 85, API_PyArray_NewFromDescr = 94, + API_PyArray_DescrNewFromType = 9, API_PyArray_DescrConverter = 174, + API_PyArray_EquivTypes = 182, API_PyArray_GetArrayParamsFromObject = 278, NPY_C_CONTIGUOUS_ = 0x0001, @@ -61,7 +66,9 @@ public: NPY_LONG_, NPY_ULONG_, NPY_LONGLONG_, NPY_ULONGLONG_, NPY_FLOAT_, NPY_DOUBLE_, NPY_LONGDOUBLE_, - NPY_CFLOAT_, NPY_CDOUBLE_, NPY_CLONGDOUBLE_ + NPY_CFLOAT_, NPY_CDOUBLE_, NPY_CLONGDOUBLE_, + NPY_OBJECT_ = 17, + NPY_STRING_, NPY_UNICODE_, NPY_VOID_ }; static API lookup() { @@ -79,7 +86,9 @@ public: DECL_NPY_API(PyArray_FromAny); DECL_NPY_API(PyArray_NewCopy); DECL_NPY_API(PyArray_NewFromDescr); + DECL_NPY_API(PyArray_DescrNewFromType); DECL_NPY_API(PyArray_DescrConverter); + DECL_NPY_API(PyArray_EquivTypes); DECL_NPY_API(PyArray_GetArrayParamsFromObject); #undef DECL_NPY_API return api; @@ -91,10 +100,12 @@ public: PyObject *(*PyArray_NewFromDescr_) (PyTypeObject *, PyObject *, int, Py_intptr_t *, Py_intptr_t *, void *, int, PyObject *); + PyObject *(*PyArray_DescrNewFromType_)(int); PyObject *(*PyArray_NewCopy_)(PyObject *, int); PyTypeObject *PyArray_Type_; PyObject *(*PyArray_FromAny_) (PyObject *, PyObject *, int, int, int, PyObject *); int (*PyArray_DescrConverter_) (PyObject *, PyObject **); + bool (*PyArray_EquivTypes_) (PyObject *, PyObject *); int (*PyArray_GetArrayParamsFromObject_)(PyObject *, PyObject *, char, PyObject **, int *, Py_ssize_t *, PyObject **, PyObject *); }; @@ -113,52 +124,83 @@ public: Py_intptr_t shape = (Py_intptr_t) size; object tmp = object(api.PyArray_NewFromDescr_( api.PyArray_Type_, descr, 1, &shape, nullptr, (void *) ptr, 0, nullptr), false); - if (ptr && tmp) - tmp = object(api.PyArray_NewCopy_(tmp.ptr(), -1 /* any order */), false); if (!tmp) pybind11_fail("NumPy: unable to create array!"); + if (ptr) + tmp = object(api.PyArray_NewCopy_(tmp.ptr(), -1 /* any order */), false); m_ptr = tmp.release().ptr(); } array(const buffer_info &info) { - PyObject *arr = nullptr, *descr = nullptr; - int ndim = 0; - Py_ssize_t dims[32]; - API& api = lookup_api(); + auto& api = lookup_api(); - // Allocate non-zeroed memory if it hasn't been provided by the caller. - // Normally, we could leave this null for NumPy to allocate memory for us, but - // since we need a memoryview, the data pointer has to be non-null. NumPy uses - // malloc if NPY_NEEDS_INIT is not set (in which case it uses calloc); however, - // we don't have a desriptor yet (only a buffer format string), so we can't - // access the flags. As long as we're not dealing with object dtypes/fields - // though, the memory doesn't have to be zeroed so we use malloc. - auto buf_info = info; - if (!buf_info.ptr) - // always allocate at least 1 element, same way as NumPy does it - buf_info.ptr = std::malloc(std::max(info.size, (size_t) 1) * info.itemsize); - if (!buf_info.ptr) - pybind11_fail("NumPy: failed to allocate memory for buffer"); + // _dtype_from_pep3118 returns dtypes with padding fields in, however the array + // constructor seems to then consume them, so we don't need to strip them ourselves + auto numpy_internal = module::import("numpy.core._internal"); + auto dtype_from_fmt = (object) numpy_internal.attr("_dtype_from_pep3118"); + auto dtype = dtype_from_fmt(pybind11::str(info.format)); + auto dtype2 = strip_padding_fields(dtype); - // PyArray_GetArrayParamsFromObject seems to be the only low-level API function - // that will accept arbitrary buffers (including structured types) - auto view = memoryview(buf_info); - auto res = api.PyArray_GetArrayParamsFromObject_(view.ptr(), nullptr, 1, &descr, - &ndim, dims, &arr, nullptr); - if (res < 0 || !arr || descr) - // We expect arr to have a pointer to a newly created array, in which case all - // other parameters like descr would be set to null, according to the API. - pybind11_fail("NumPy: unable to convert buffer to an array"); - m_ptr = arr; + object tmp(api.PyArray_NewFromDescr_( + api.PyArray_Type_, dtype2.release().ptr(), (int) info.ndim, (Py_intptr_t *) &info.shape[0], + (Py_intptr_t *) &info.strides[0], info.ptr, 0, nullptr), false); + if (!tmp) + pybind11_fail("NumPy: unable to create array!"); + if (info.ptr) + tmp = object(api.PyArray_NewCopy_(tmp.ptr(), -1 /* any order */), false); + m_ptr = tmp.release().ptr(); + auto d = (object) this->attr("dtype"); } -protected: +// protected: static API &lookup_api() { static API api = API::lookup(); return api; } template friend struct detail::npy_format_descriptor; + + static object strip_padding_fields(object dtype) { + // Recursively strip all void fields with empty names that are generated for + // padding fields (as of NumPy v1.11). + auto fields = dtype.attr("fields").cast(); + if (fields.ptr() == Py_None) + return dtype; + + struct field_descr { pybind11::str name; object format; int_ offset; }; + std::vector field_descriptors; + + auto items = fields.attr("items").cast(); + for (auto field : items()) { + auto spec = object(field, true).cast(); + auto name = spec[0].cast(); + auto format = spec[1].cast()[0].cast(); + auto offset = spec[1].cast()[1].cast(); + if (!len(name) && (std::string) dtype.attr("kind").cast() == "V") + continue; + field_descriptors.push_back({name, strip_padding_fields(format), offset}); + } + + std::sort(field_descriptors.begin(), field_descriptors.end(), + [](const field_descr& a, const field_descr& b) { + return (int) a.offset < (int) b.offset; + }); + + list names, formats, offsets; + for (auto& descr : field_descriptors) { + names.append(descr.name); + formats.append(descr.format); + offsets.append(descr.offset); + } + auto args = dict(); + args["names"] = names; args["formats"] = formats; args["offsets"] = offsets; + args["itemsize"] = dtype.attr("itemsize").cast(); + + PyObject *descr = nullptr; + if (!lookup_api().PyArray_DescrConverter_(args.release().ptr(), &descr) || !descr) + pybind11_fail("NumPy: failed to create structured dtype"); + return object(descr, false); + } }; template class array_t : public array { @@ -233,9 +275,12 @@ DECL_FMT(std::complex, NPY_CDOUBLE_, "complex128"); struct field_descriptor { const char *name; size_t offset; + size_t size; + const char *format; object descr; }; + template struct npy_format_descriptor::value>::type> { static PYBIND11_DESCR name() { return _("user-defined"); } @@ -253,7 +298,7 @@ struct npy_format_descriptor::value> } static void register_dtype(std::initializer_list fields) { - array::API& api = array::lookup_api(); + auto& api = array::lookup_api(); auto args = dict(); list names { }, offsets { }, formats { }; for (auto field : fields) { @@ -263,26 +308,47 @@ struct npy_format_descriptor::value> offsets.append(int_(field.offset)); formats.append(field.descr); } - args["names"] = names; - args["offsets"] = offsets; - args["formats"] = formats; + args["names"] = names; args["offsets"] = offsets; args["formats"] = formats; args["itemsize"] = int_(sizeof(T)); // This is essentially the same as calling np.dtype() constructor in Python and passing // it a dict of the form {'names': ..., 'formats': ..., 'offsets': ...}. if (!api.PyArray_DescrConverter_(args.release().ptr(), &dtype_()) || !dtype_()) pybind11_fail("NumPy: failed to create structured dtype"); - // Let NumPy figure the buffer format string for us: memoryview(np.empty(0, dtype)).format - auto np = module::import("numpy"); - auto empty = (object) np.attr("empty"); - if (auto arr = (object) empty(int_(0), dtype())) { - if (auto view = PyMemoryView_FromObject(arr.ptr())) { - if (auto info = PyMemoryView_GET_BUFFER(view)) { - std::strncpy(format_(), info->format, 4096); - return; - } - } + + // There is an existing bug in NumPy (as of v1.11): trailing bytes are + // not encoded explicitly into the format string. This will supposedly + // get fixed in v1.12; for further details, see these: + // - https://github.com/numpy/numpy/issues/7797 + // - https://github.com/numpy/numpy/pull/7798 + // Because of this, we won't use numpy's logic to generate buffer format + // strings and will just do it ourselves. + std::vector ordered_fields(fields); + std::sort(ordered_fields.begin(), ordered_fields.end(), + [](const field_descriptor& a, const field_descriptor &b) { + return a.offset < b.offset; + }); + size_t offset = 0; + std::ostringstream oss; + oss << "T{"; + for (auto& field : ordered_fields) { + if (field.offset > offset) + oss << (field.offset - offset) << 'x'; + // note that '=' is required to cover the case of unaligned fields + oss << '=' << field.format << ':' << field.name << ':'; + offset = field.offset + field.size; } - pybind11_fail("NumPy: failed to extract buffer format"); + if (sizeof(T) > offset) + oss << (sizeof(T) - offset) << 'x'; + oss << '}'; + std::strncpy(format_(), oss.str().c_str(), 4096); + + // Sanity check: verify that NumPy properly parses our buffer format string + auto arr = array(buffer_info(nullptr, sizeof(T), format(), 1, { 0 }, { sizeof(T) })); + auto dtype = (object) arr.attr("dtype"); + auto fixed_dtype = dtype; + // auto fixed_dtype = array::strip_padding_fields(object(dtype_(), true)); + // if (!api.PyArray_EquivTypes_(dtype_(), fixed_dtype.ptr())) + // pybind11_fail("NumPy: invalid buffer descriptor!"); } private: @@ -293,7 +359,8 @@ private: // Extract name, offset and format descriptor for a struct field #define PYBIND11_FIELD_DESCRIPTOR(Type, Field) \ ::pybind11::detail::field_descriptor { \ - #Field, offsetof(Type, Field), \ + #Field, offsetof(Type, Field), sizeof(decltype(static_cast(0)->Field)), \ + ::pybind11::format_descriptor(0)->Field)>::format(), \ ::pybind11::detail::npy_format_descriptor(0)->Field)>::dtype() \ }