tensorflow/models · error · NotImplementedError

Applying sparse gradients is not implemented.

Error message

Applying sparse gradients is not implemented.

What it means

Error "Applying sparse gradients is not implemented." thrown in tensorflow/models.

Source

Thrown at official/modeling/optimization/lars.py:151

      trust_ratio = 1.0
      if self._do_layer_adaptation(param_name):
        w_norm = tf.norm(param, ord=2)
        v_norm = tf.norm(update, ord=2)
        trust_ratio = tf.where(
            tf.greater(w_norm, 0),
            tf.where(tf.greater(v_norm, 0), (self.eeta * w_norm / v_norm), 1.0),
            1.0)
      scaled_lr = trust_ratio * learning_rate
      next_param = param - scaled_lr * update

    return tf.group(*[
        param.assign(next_param, use_locking=False),
        v.assign(next_v, use_locking=False)
    ])

  def _resource_apply_sparse(self, grad, handle, indices, apply_state):
    raise NotImplementedError("Applying sparse gradients is not implemented.")

  def _use_weight_decay(self, param_name):
    """Whether to use L2 weight decay for `param_name`."""
    if not self.weight_decay_rate:
      return False
    if self.exclude_from_weight_decay:
      for r in self.exclude_from_weight_decay:
        if re.search(r, param_name) is not None:
          return False
    return True

  def _do_layer_adaptation(self, param_name):
    """Whether to do layer-wise learning rate adaptation for `param_name`."""
    if self.exclude_from_layer_adaptation:
      for r in self.exclude_from_layer_adaptation:
        if re.search(r, param_name) is not None:
          return False
    return True

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/modeling/optimization/lars.py:151 when the library encounters an invalid state.

Common situations: See trigger scenarios.

AI-assisted analysis of tensorflow/models@e006f5f0d5 (2026-08-24). Data as JSON: /api/errors/9f91f9a25348f79d. Report an issue: GitHub.