baacb20d15066935e4a23c09b1c1a6843331172f,research/object_detection/meta_architectures/center_net_meta_arch.py,,regressed_keypoints_at_object_centers,#Any#Any#Any#,453

Before Change

    to absolute coordinates in the output coordinate frame.
  
  batch_size, _, width, _ = _get_shape(regressed_keypoint_predictions, 4)
  flattened_indices = flattened_indices_from_row_col_indices(
      y_indices, x_indices, width)
  _, num_instances = _get_shape(flattened_indices, 2)

  regressed_keypoints_flat = _flatten_spatial_dimensions(
      regressed_keypoint_predictions)

After Change

  // TF Lite does not support tf.gather with batch_dims > 0, so we need to use
  // tf_gather_nd instead and here we prepare the indices for that.
  combined_indices = tf.stack([
      _multi_range(batch_size, value_repetitions=num_instances),
      tf.reshape(y_indices, [-1]),
      tf.reshape(x_indices, [-1])
  ], axis=1)

  relative_regressed_keypoints = tf.gather_nd(regressed_keypoint_predictions,
                                              combined_indices)
  relative_regressed_keypoints = tf.reshape(

Instances