// to allow their size to be computed and they need to be passable to a backward
// function and deleted (as the backprop code creates lots of gradients the user
// is not interested in).
//
// BackwardFunction needs to be a closure which stores intermediate activations
// from the forward computation and calls a vector-jacobian product function
// (also known as adjoint function) to compute, given downstream gradients,
// upstream gradients.
//

  } else {
    DCHECK_EQ(nullptr, session);
    return nullptr;
  }
}

void TF_CloseDeprecatedSession(TF_DeprecatedSession* s, TF_Status* status) {
  status->status = s->session->Close();
}

void TF_DeleteDeprecatedSession(TF_DeprecatedSession* s, TF_Status* status) {
  status->status = absl::OkStatus();
  if (s == nullptr) return;
  delete s->session;
  delete s;
}

*   `import tensorflow` now goes much faster.
*   Adds a file cache to the GCS filesystem with configurable max staleness for
    file contents. This permits caching of file contents across close/open
    boundaries.
*   Added an axis parameter to `tf.gather`.
*   Added a `constant_values` keyword argument to `tf.pad`.
*   Adds `Dataset.interleave` transformation.

  ops->writable_file_ops->tell = tf_writable_file::Tell;
  ops->writable_file_ops->flush = tf_writable_file::Flush;
  ops->writable_file_ops->sync = tf_writable_file::Sync;
  ops->writable_file_ops->close = tf_writable_file::Close;

  ops->read_only_memory_region_ops = static_cast<TF_ReadOnlyMemoryRegionOps*>(
      plugin_memory_allocate(TF_READ_ONLY_MEMORY_REGION_OPS_SIZE));
  ops->read_only_memory_region_ops->cleanup =

      'w') as f:
    f.write('export PYTHON_BIN_PATH="{}"'.format(python_bin_path))


def reset_tf_configure_bazelrc():
  """Reset file that contains customized config settings."""
  open(_TF_BAZELRC, 'w').close()


def cleanup_makefile():
  """Delete any leftover BUILD files from the Makefile build.

  These files could interfere with Bazel parsing.
  """