# InvalidArgumentError: The SavedModel's tag set is empty or does not match the requested tags

- **ID:** `tensorflow/savedmodel-tagset-mismatch`
- **Domain:** tensorflow
- **Category:** config_error
- **Verification:** ai_generated
- **Fix Rate:** 92%

## Root Cause

When loading a SavedModel with tf.saved_model.load(), the 'tags' argument does not match any MetaGraphDef present in the SavedModel, or the SavedModel was saved without tags.

## Version Compatibility

| Version | Status | Introduced | Deprecated |
|---------|--------|------------|------------|
| tensorflow 2.8 | active | — | — |
| tensorflow 2.9 | active | — | — |
| tensorflow 2.10 | active | — | — |

## Workarounds

1. **Use saved_model_cli show --dir /path/to/saved_model --all to list available tag sets, then pass the correct tags to tf.saved_model.load(). For example: model = tf.saved_model.load('/path/to/saved_model', tags=['serve'])** (95% success)
   ```
   Use saved_model_cli show --dir /path/to/saved_model --all to list available tag sets, then pass the correct tags to tf.saved_model.load(). For example: model = tf.saved_model.load('/path/to/saved_model', tags=['serve'])
   ```
2. **If no tags were saved, reload using tf.saved_model.load(path, tags=[]) or save the model again with explicit tags using tf.saved_model.save(model, path, signatures=..., tags=['serve']).** (90% success)
   ```
   If no tags were saved, reload using tf.saved_model.load(path, tags=[]) or save the model again with explicit tags using tf.saved_model.save(model, path, signatures=..., tags=['serve']).
   ```

## Dead Ends

- **** — The error is tag-specific, not path-related; another SavedModel may have the same tag mismatch. (80% fail)
- **** — Debug info is unrelated to MetaGraphDef tags; the tag set remains unchanged. (95% fail)