tensorflow/models · error · ValueError
Unrecognized file_type: {}
Error message
Unrecognized file_type: {} What it means
Error "Unrecognized file_type: {}" thrown in tensorflow/models.
Source
Thrown at official/projects/pointpillars/tasks/pointpillars.py:40
from official.core import base_task
from official.core import task_factory
from official.projects.pointpillars.configs import pointpillars as cfg
from official.projects.pointpillars.dataloaders import decoders
from official.projects.pointpillars.dataloaders import parsers
from official.projects.pointpillars.modeling import factory
from official.projects.pointpillars.utils import utils
from official.vision.dataloaders import input_reader_factory
from official.vision.losses import focal_loss
from official.vision.losses import loss_utils
def pick_dataset_fn(file_type: str) -> Any:
if file_type == 'tfrecord':
return tf.data.TFRecordDataset
if file_type == 'tfrecord_compressed':
return functools.partial(tf.data.TFRecordDataset, compression_type='GZIP')
raise ValueError('Unrecognized file_type: {}'.format(file_type))
def get_batch_size_per_replica(global_batch_size: int) -> int:
"""Get batch size per accelerator replica."""
num_replicas = tf.distribute.get_strategy().num_replicas_in_sync
if global_batch_size < num_replicas:
logging.warning('Global batch size is smaller than num replicas. '
'Set batch size per replica to 1.')
return 1
if global_batch_size % num_replicas != 0:
raise ValueError(
'global_batch_size {} is not a multiple of num_replicas {}'
.format(global_batch_size, num_replicas))
batch_size = int(global_batch_size / num_replicas)
return batch_size
@task_factory.register_task_cls(cfg.PointPillarsTask)View on GitHub (pinned to e006f5f0d5)
When it happens
Trigger: Thrown at official/projects/pointpillars/tasks/pointpillars.py:40 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/b9353803cdd28642.
Report an issue: GitHub.