I recently had need of tracing numpy data allocation/deallocation. I
was unable to find a simple way to do so, and so ended up putting the
code below into ndarraytypes.h to allow me to trace allocations. A
key part is that this jumps back into python, so I can inspect the
stack and find out where in the upper level code large allocations are
occurring.
I wondered, however, if there were a better way to accomplish the same
goal, preferably in pure python.
Ray Jones
static void *numpy_memtrace_malloc(size_t size) {
void *result = malloc(size);
PyObject *npy = PyImport_ImportModule("numpy");
if (npy != NULL) {
if (PyObject_HasAttrString(npy, "tracemalloc")) {
PyObject *ret;
ret = PyObject_CallMethod(npy, "tracemalloc", "Nl",
PyLong_FromVoidPtr(result), (long) size);
Py_XDECREF(ret);
Py_DECREF(npy);
PyErr_Clear();
}
}
return result;
}
static void numpy_memtrace_free(void *ptr) {
free(ptr);
PyObject *npy = PyImport_ImportModule("numpy");
if (npy != NULL) {
if (PyObject_HasAttrString(npy, "tracefree")) {
PyObject *ret;
ret = PyObject_CallMethod(npy, "tracefree", "N", PyLong_FromVoidPtr(ptr));
Py_XDECREF(ret);
Py_DECREF(npy);
PyErr_Clear();
}
}
}
static void *numpy_memtrace_realloc(void *ptr, size_t size) {
void *result = realloc(ptr, size);
PyObject *npy = PyImport_ImportModule("numpy");
if (npy != NULL) {
if (PyObject_HasAttrString(npy, "npyealloc")) {
PyObject *ret;
ret = PyObject_CallMethod(npy, "npyealloc", "NNl",
PyLong_FromVoidPtr(ptr), PyLong_FromVoidPtr(result), size);
Py_XDECREF(ret);
Py_DECREF(npy);
PyErr_Clear();
}
}
return result;
}
/* Data buffer */
#define PyDataMem_NEW(size) ((char *)numpy_memtrace_malloc(size))
#define PyDataMem_FREE(ptr) numpy_memtrace_free(ptr)
#define PyDataMem_RENEW(ptr,size) ((char *)numpy_memtrace_realloc(ptr,size))
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