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Use malloc insterad of calloc for numpy arrays
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@ -126,16 +126,17 @@ public:
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Py_ssize_t dims[32];
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API& api = lookup_api();
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// Allocate zeroed memory if it hasn't been provided by the caller.
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// Allocate non-zeroed memory if it hasn't been provided by the caller.
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// Normally, we could leave this null for NumPy to allocate memory for us, but
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// since we need a memoryview, the data pointer has to be non-null. NumPy uses
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// malloc if NPY_NEEDS_INIT is not set (in which case it uses calloc); however,
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// we don't have a descriptor yet (only a buffer format string), so we can't
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// access the flags. The safest thing to do is thus to use calloc.
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// we don't have a desriptor yet (only a buffer format string), so we can't
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// access the flags. As long as we're not dealing with object dtypes/fields
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// though, the memory doesn't have to be zeroed so we use malloc.
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auto buf_info = info;
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if (!buf_info.ptr)
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// always allocate at least 1 element, same way as NumPy does it
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buf_info.ptr = std::calloc(std::max(info.size, (size_t) 1), info.itemsize);
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buf_info.ptr = std::malloc(std::max(info.size, (size_t) 1) * info.itemsize);
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if (!buf_info.ptr)
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pybind11_fail("NumPy: failed to allocate memory for buffer");
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