Vertica 25.4.1 ERROR 9450: Unsupported tensorflow type: 0 when importing Universal Sentence Encoder (Multilingual)

Hi everyone,

I am struggling to import the Google Universal Sentence Encoder (Multilingual) model into Vertica 25.4.1 using the TensorFlow integration.

My Environment:

• OS: Rocky Linux 9

• Vertica Version: 25.4.1-x

• TensorFlow: 2.15.0

• TensorFlow Text: 2.15.0 (required for the multilingual USE ops)

• Python: 3.10 (for model freezing)

The Issue: I have successfully loaded the USE model in Python, registered the SentencepieceOp via tensorflow_text, and exported it as a frozen .pb file with a corresponding tf_model_desc.json.

However, when I run the following SQL command in Vertica:

SELECT IMPORT_MODELS('/home/dbadmin/frozen_dir/' USING PARAMETERS category='TENSORFLOW');

I consistently get this error: ERROR 9450: Failed to import model(s): Failed to import single model: Error in importModelFiles: Error calling setup() in User Function import_model_files at [src/Common/TFCommon.cpp:51], error code: 0, message: Unsupported tensorflow type: 0

My tf_model_desc.json:

{
    "frozen_graph": "use_model.pb",
    "input_desc": [{
        "name": "input_text",
        "dims": [-1],
        "data_type": "string"
    }],
    "output_desc": [{
        "name": "Identity",
        "dims": [-1, 512],
        "data_type": "float"
    }]
}

What I've tried:

1. Verified that the tensor name input_text exists in the frozen graph.

2. Attempted changing data_type in the JSON to "STRING", "string", and tried changing dims from [-1] to [1].

3. Confirmed that tensorflow_text ops are required for this model.

The error type: 0 seems to map to DT_INVALID in the TensorFlow source. Does Vertica's TensorFlow integration support DT_STRING tensors for the Multilingual USE model? Or is there a specific way to define string inputs in the descriptor file for this version of Vertica?

Any guidance or workarounds would be greatly appreciated!