-   Once the PR is in the Google codebase, we make sure it integrates well with
    its dependencies and the rest of the system.
-   Rarely, If the tests fail at this stage, we cannot merge the code.
-   If needed, we may come to you to make some changes. At times, it may not be
    you, it may be us who may have hit a snag. Please be patient while we work
    to fix this.

  if (TF_GetCode(status) != TF_OK) return;
  if (childrens.size() > 1 || (childrens.size() == 1 && !childrens[0].empty()))
    return TF_SetStatus(status, TF_FAILED_PRECONDITION,
                        "Cannot delete a non-empty directory.");
  if (childrens.size() == 1 && childrens[0].empty()) {
    // This is the directory marker object. Delete it.
    std::string dir = path;
    MaybeAppendSlash(&dir);

      return;
    }
  } else if (S_ISDIR(st.st_mode)) {
    TF_SetStatus(status, TF_FAILED_PRECONDITION, "target path is a directory");
    return;
  }

  // We cannot rename directories yet, so prevent this.
  if (stat(src, &st) != 0) {
    TF_SetStatusFromIOError(status, errno, src);
    return;
  } else if (S_ISDIR(st.st_mode)) {

// Operations the tape needs to perform on tensors to do backpropagation. Named
// "vspace" because a subset of these are related to a vector space, such as
// adding gradients, getting zeroes, etc. Currently cannot be implemented
// without using tensorflow python code, hence left unspecified here.
//
// Gradient is the type returned by gradient functions. In Python TF it's either

  TF_ShapeAndType& shape = shape_list->items[index];
  DCHECK(shape.dims == nullptr) << "Shape at " << index << " is already set!";
  DCHECK(num_dims >= 0) << "Number of dimensions cannot be negative!";
  shape.num_dims = num_dims;
  shape.dims = new int64_t[num_dims];
  memcpy(shape.dims, dims, sizeof(int64_t) * num_dims);
}

void TF_ShapeAndTypeListSetUnknownShape(TF_ShapeAndTypeList* shape_list,

-       | ((const unsigned char *) (const char *) (src))[idx + 2]) << 8	      \
-      | ((const unsigned char *) (const char *) (src))[idx + 3])
-# endif
 #else
 /* These are a few types we need for the optimizations if we cannot
    use unaligned memory accesses.  */
@@ -94,148 +72,11 @@ __STRING2_COPY_TYPE (8);
 
 /* Set N bytes of S to C.  */
 #if !defined _HAVE_STRING_ARCH_memset
-# if !__GNUC_PREREQ (3, 0)

                          const TF_Function* grad, TF_Status* status) {
  if (func == nullptr) {
    status->status = InvalidArgument(
        "'func' argument to TF_GraphCopyFunction cannot be null");
    return;
  }

  tensorflow::mutex_lock l(g->mu);
  status->status = g->graph.AddFunctionDef(func->record->fdef(),
                                           func->record->stack_traces());