tensorflow/models · error · ValueError

Unsupported optimizer type:

Error message

Unsupported optimizer type: 

What it means

Error "Unsupported optimizer type: " thrown in tensorflow/models.

Source

Thrown at official/nlp/optimization.py:111

    optimizer = AdamWeightDecay(
        learning_rate=lr_schedule,
        weight_decay_rate=0.01,
        beta_1=beta_1,
        beta_2=0.999,
        epsilon=1e-6,
        exclude_from_weight_decay=['LayerNorm', 'layer_norm', 'bias'])
  elif optimizer_type == 'lamb':
    logging.info('using Lamb optimizer')
    optimizer = LAMB(
        learning_rate=lr_schedule,
        weight_decay_rate=0.01,
        beta_1=beta_1,
        beta_2=0.999,
        epsilon=1e-6,
        exclude_from_weight_decay=['LayerNorm', 'layer_norm', 'bias'],
    )
  else:
    raise ValueError('Unsupported optimizer type: ', optimizer_type)

  return optimizer

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/nlp/optimization.py:111 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/e8e5ec608454b5f3. Report an issue: GitHub.