}

  close(fd);
}

static void CreateDir(const TF_Filesystem* filesystem, const char* path,
                      TF_Status* status) {
  if (strlen(path) == 0)
    TF_SetStatus(status, TF_ALREADY_EXISTS, "already exists");
  else if (mkdir(path, /*mode=*/0755) != 0)
    TF_SetStatusFromIOError(status, errno, path);
  else
    TF_SetStatus(status, TF_OK, "");
}

  status->status = c.construction_status();
  if (!status->status.ok()) return;

  if (op_reg_data->shape_inference_fn == nullptr) {
    status->status =
        InvalidArgument("No shape inference function exists for op '",
                        node_def.op(), "', did you forget to define it?");
    return;
  }

  status->status = c.Run(op_reg_data->shape_inference_fn);
  if (!status->status.ok()) return;

your changes by running the command:

```bash
tensorflow/tools/ci_build/ci_build.sh CPU tensorflow/tools/ci_build/ci_sanity.sh
```

This will catch most license, Python coding style and BUILD file issues that
may exist in your changes.

#### Running unit tests

There are two ways to run TensorFlow unit tests.

1.  Using tools and libraries installed directly on your system.

    Refer to the

namespace {

template <typename BackwardFunction, typename TapeTensor>
struct BackpropInitialState {
  OpTape<BackwardFunction, TapeTensor> op_tape;

  // Map from tensor ID to how many references still exist for this tensor in
  // the tape.
  std::unordered_map<int64_t, int64_t> tensor_usage_counts;

  // Maps from op ID to how many output tensors of this op still need to have
  // their gradients computed.