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Use malloc insterad of calloc for numpy arrays

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Ivan Smirnov 2016-07-02 16:43:21 +01:00
parent 5412a05cf0
commit 511401599c
1 changed files with 5 additions and 4 deletions
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9
include/pybind11/numpy.h
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@ -126,16 +126,17 @@ public:
Py_ssize_t dims[32]; Py_ssize_t dims[32];
API& api = lookup_api(); API& api = lookup_api();
// Allocate zeroed memory if it hasn't been provided by the caller. // 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 // 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 // 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, // malloc if NPY_NEEDS_INIT is not set (in which case it uses calloc); however,
// we don't have a descriptor yet (only a buffer format string), so we can't // we don't have a desriptor yet (only a buffer format string), so we can't
// access the flags. The safest thing to do is thus to use calloc. // 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; auto buf_info = info;
if (!buf_info.ptr) if (!buf_info.ptr)
// always allocate at least 1 element, same way as NumPy does it // always allocate at least 1 element, same way as NumPy does it
buf_info.ptr = std::calloc(std::max(info.size, (size_t) 1), info.itemsize); buf_info.ptr = std::malloc(std::max(info.size, (size_t) 1) * info.itemsize);
if (!buf_info.ptr) if (!buf_info.ptr)
pybind11_fail("NumPy: failed to allocate memory for buffer"); pybind11_fail("NumPy: failed to allocate memory for buffer");