message: Update metrics_op.py
  Using core method over private
diff: @@ -34,6 +34,7 @@ from tensorflow.python.ops import metrics_impl
  from tensorflow.python.ops import nn
  from tensorflow.python.ops import state_ops
  from tensorflow.python.ops import variable_scope
  +from tensorflow.python.ops import weights_broadcast_ops
  from tensorflow.python.util.deprecation import deprecated
  @@ -651,7 +652,7 @@ def _streaming_confusion_matrix_at_thresholds(
  label_is_neg = math_ops.logical_not(label_is_pos)
  if weights is not None:
  - broadcast_weights = _broadcast_weights(
  + broadcast_weights = weights_broadcast_ops.broadcast_weights(
  math_ops.to_float(weights), predictions)
  weights_tiled = array_ops.tile(array_ops.reshape(
  broadcast_weights, [1, -1]), [num_thresholds, 1])
  @@ -1924,7 +1925,7 @@ def streaming_covariance(predictions,
  weighted_predictions = predictions
  weighted_labels = labels
  else:
  - weights = _broadcast_weights(weights, labels)
  + weights = weights_broadcast_ops.broadcast_weights(weights, labels)
  batch_count = math_ops.reduce_sum(weights) # n_B in eqn
  weighted_predictions = math_ops.multiply(predictions, weights)
  weighted_labels = math_ops.multiply(labels, weights)
  @@ -2051,7 +2052,7 @@ def streaming_pearson_correlation(predictions,
  # Broadcast weights here to avoid duplicate broadcasting in each call to
  # `streaming_covariance`.
  if weights is not None:
  - weights = _broadcast_weights(weights, labels)
  + weights = weights_broadcast_ops.broadcast_weights(weights, labels)
  cov, update_cov = streaming_covariance(
  predictions, labels, weights=weights, name='covariance')
  var_predictions, update_var_predictions = streaming_covariance(
  