tensorflow/models · error · ValueError

At most one of `hub_module_url` and `init_checkpoint` can be

Error message

At most one of `hub_module_url` and `init_checkpoint` can be specified.

What it means

Error "At most one of `hub_module_url` and `init_checkpoint` can be specified." thrown in tensorflow/models.

Source

Thrown at official/nlp/tasks/dual_encoder.py:77

  # be specified.
  init_checkpoint: str = ''
  hub_module_url: str = ''
  # Defines the concrete model config at instantiation time.
  model: ModelConfig = dataclasses.field(default_factory=ModelConfig)
  train_data: cfg.DataConfig = dataclasses.field(default_factory=cfg.DataConfig)
  validation_data: cfg.DataConfig = dataclasses.field(
      default_factory=cfg.DataConfig
  )


@task_factory.register_task_cls(DualEncoderConfig)
class DualEncoderTask(base_task.Task):
  """Task object for dual encoder."""

  def build_model(self):
    """Interface to build model. Refer to base_task.Task.build_model."""
    if self.task_config.hub_module_url and self.task_config.init_checkpoint:
      raise ValueError('At most one of `hub_module_url` and '
                       '`init_checkpoint` can be specified.')
    if self.task_config.hub_module_url:
      encoder_network = utils.get_encoder_from_hub(
          self.task_config.hub_module_url)
    else:
      encoder_network = encoders.build_encoder(self.task_config.model.encoder)

    # Currently, we only supports bert-style dual encoder.
    return models.DualEncoder(
        network=encoder_network,
        max_seq_length=self.task_config.model.max_sequence_length,
        normalize=self.task_config.model.normalize,
        logit_scale=self.task_config.model.logit_scale,
        logit_margin=self.task_config.model.logit_margin,
        output='logits')

  def build_losses(self, labels, model_outputs, aux_losses=None) -> tf.Tensor:
    """Interface to compute losses. Refer to base_task.Task.build_losses."""

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/nlp/tasks/dual_encoder.py:77 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/33996f90f7bef06e. Report an issue: GitHub.