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/projects/lra/lra_dual_encoder_task.py:85
@task_factory.register_task_cls(DualEncoderConfig)
class DualEncoderTask(base_task.Task):
"""Task object for DualEncoderTask."""
def __init__(self, params: cfg.TaskConfig, logging_dir=None, name=None):
super().__init__(params, logging_dir, name=name)
if params.metric_type not in METRIC_TYPES:
raise ValueError('Invalid metric_type: {}'.format(params.metric_type))
self.metric_type = params.metric_type
if hasattr(params.train_data, 'label_field'):
self.label_field = params.train_data.label_field
else:
self.label_field = 'label_ids'
def build_model(self):
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)
encoder_cfg = self.task_config.model.encoder.get()
return lra_dual_encoder.LRADualEncoder(
network=encoder_network,
max_seq_length=self.task_config.model.max_seq_length,
num_classes=self.task_config.model.num_classes,
initializer=tf_keras.initializers.TruncatedNormal(
stddev=encoder_cfg.initializer_range
),View on GitHub (pinned to e006f5f0d5)
When it happens
Trigger: Thrown at official/projects/lra/lra_dual_encoder_task.py:85 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/b3e2e4fe6cefa2c9.
Report an issue: GitHub.