Lightstar/venv/Lib/site-packages/torch/include/ATen/native/TensorDimApply.h

#pragma once
#include <ATen/core/Tensor.h>
#include <c10/util/irange.h>

namespace at::native {
//input tensors are non-zero dim and non-empty
template<typename T1, typename T2, typename Function>

void tensor_dim_apply3(const Tensor& self, Tensor& values, Tensor& indices, int64_t dim, Function func) {
  int ndims = self.dim();
  int tensor_dim_apply_has_finished = 0;
  std::vector<int64_t> counter(ndims, 0);
  const T1* self_data = self.const_data_ptr<T1>();
  T1* values_data = values.data_ptr<T1>();
  T2* indices_data = indices.data_ptr<T2>();
  int64_t self_stride = self.stride(dim);
  int64_t values_stride = values.stride(dim);
  int64_t indices_stride = indices.stride(dim);
  int self_dim_size = self.size(dim);

  while (!tensor_dim_apply_has_finished) {
    func(self_data, values_data, indices_data, self_dim_size, self_stride, values_stride, indices_stride);
    if (ndims == 1) {
       break;
    }
    for (const auto dim_i : c10::irange(ndims)) {
      if (dim_i == dim) {
        if (dim_i == (ndims - 1)) {
          tensor_dim_apply_has_finished = 1;
          break;
        }
        continue;
      }
      counter[dim_i]++;
      self_data += self.stride(dim_i);
      values_data += values.stride(dim_i);
      indices_data += indices.stride(dim_i);

      if (counter[dim_i] == self.size(dim_i)) {
        if (dim_i == ndims-1) {
          tensor_dim_apply_has_finished = 1;
          break;
        } else {
          self_data -= counter[dim_i]*self.stride(dim_i);
          values_data -= counter[dim_i]*values.stride(dim_i);
          indices_data -= counter[dim_i]*indices.stride(dim_i);
          counter[dim_i] = 0;
        }
      } else {
        break;
     }
    }
  }
}
} // namespace at::native