tensorflow/models · error · ValueError
Export module not implemented for {} task.
Error message
Export module not implemented for {} task. What it means
Error "Export module not implemented for {} task." thrown in tensorflow/models.
Source
Thrown at official/vision/serving/export_saved_model_lib.py:145
batch_size=batch_size,
input_image_size=input_image_size,
input_type=input_type,
num_channels=num_channels,
input_name=input_name,
)
elif isinstance(
params.task, configs.video_classification.VideoClassificationTask
):
export_module = video_classification.VideoClassificationModule(
params=params,
batch_size=batch_size,
input_image_size=input_image_size,
input_type=input_type,
num_channels=num_channels,
input_name=input_name,
)
else:
raise ValueError(
'Export module not implemented for {} task.'.format(type(params.task))
)
if add_tpu_function_alias:
if input_type == 'image_tensor':
inference_func = export_module.inference_from_image_tensors
elif input_type == 'image_bytes':
inference_func = export_module.inference_from_image_bytes
elif input_type == 'tf_example':
inference_func = export_module.inference_from_tf_example
else:
raise ValueError(
'add_tpu_function_alias is only allowed for input_type of:'
' image_tensor, image_bytes, tf_example.'
)
save_options = tf.saved_model.SaveOptions(
function_aliases={
'tpu_candidate': inference_func,View on GitHub (pinned to e006f5f0d5)
Solutions
- Use a supported task for SavedModel export (e.g. 'classification', 'detection', 'segmentation').
- Register an export module for your custom task.
When it happens
Trigger: Thrown at official/vision/serving/export_saved_model_lib.py:145 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/23f55145292001f4.
Report an issue: GitHub.