Function PyTensorObject_var

oneflow/api/python/framework/tensor_functions.cpp:520–549

}

static PyObject* PyTensorObject_var(PyObject* self, PyObject* args, PyObject* kwargs) {
  HANDLE_ERRORS
  PyObject* dim_obj = Py_None;
  PyObject* unbiased_obj = Py_True;
  PyObject* keepdim_obj = Py_False;
  static const char* keywords[4] = {"dim", "unbiased", "keepdim", NULL};
  if (!PyArg_ParseTupleAndKeywords(args, kwargs, "|OO!O!:var", const_cast<char**>(keywords),
                                   &dim_obj, &PyBool_Type, &unbiased_obj, &PyBool_Type,
                                   &keepdim_obj)) {
    return NULL;
  }
  bool unbiased = unbiased_obj == Py_True;
  bool keepdim = keepdim_obj == Py_True;
  CHECK_OR_THROW(dim_obj == Py_None || PyLong_Check(dim_obj)
                 || functional::PyLongSequenceCheck(dim_obj))
      << Error::TypeError() << "var(): argument 'dim' must be int32 list, not "
      << functional::PyStringAsString(PyObject_Str((PyObject*)Py_TYPE(dim_obj)));
  auto tensor = PyTensor_Unpack(self);
  if (dim_obj == Py_None) {
    return PyTensor_New(ASSERT_PTR(functional::Variance(tensor, NullOpt, unbiased, keepdim)));
  }
  std::vector<int32_t> dim;
  if (PyLong_Check(dim_obj)) {
    dim.emplace_back(static_cast<int32_t>(PyLong_AsLong(dim_obj)));
    return PyTensor_New(ASSERT_PTR(functional::Variance(tensor, dim, unbiased, keepdim)));
  }
  dim = functional::PyUnpackLongSequence<int32_t>(dim_obj);
  return PyTensor_New(ASSERT_PTR(functional::Variance(tensor, dim, unbiased, keepdim)));
  END_HANDLE_ERRORS
}

static PyObject* PyTensorObject_std(PyObject* self, PyObject* args, PyObject* kwargs) {
  HANDLE_ERRORS