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edgify / torch   python

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Version: 2.0.1+cpu 

/ include / torch / csrc / copy_utils.h

#pragma once

#include <torch/csrc/Types.h>
#include <functional>
#include <vector>

typedef std::function<void(PyObject*, PyObject*, bool)> THPCopyFunction;
// NOLINTNEXTLINE(cppcoreguidelines-pro-type-member-init)
struct THPCopyInfo {
  PyTypeObject* srcType; // Python type of src tensor/storage
  THPCopyFunction copy; // copy function
  bool non_blocking; // true if copy implements an 'non_blocking' copy
  bool broadcast; // true if the copy implements a broadcast copy
};
typedef std::vector<THPCopyInfo> THPCopyList;

inline bool tryTHPCopy(
    const THPCopyList& v,
    PyObject* dst,
    PyObject* src,
    bool non_blocking,
    bool broadcast) {
  for (auto& i : v) {
    if (i.non_blocking == non_blocking &&
        PyType_IsSubtype(Py_TYPE(src), i.srcType)) {
      (i.copy)(dst, src, broadcast);
      return true;
    }
  }
  return false;
}

inline bool THPCopy(
    const THPCopyList& v,
    PyObject* dst,
    PyObject* src,
    bool non_blocking,
    bool broadcast) {
  // NOLINTNEXTLINE(bugprone-branch-clone)
  if (tryTHPCopy(v, dst, src, non_blocking, broadcast)) {
    return true;
  } else if (non_blocking && tryTHPCopy(v, dst, src, false, broadcast)) {
    return true;
  }
  THPUtils_setError(
      "copy from %s to %s isn't implemented",
      THPUtils_typename(src),
      THPUtils_typename(dst));
  return false;
}