Exporting a SavedModel

OpenNMT-tf can export SavedModel packages for inference in other environments, for example with TensorFlow Serving. A model export contains all information required for inference: the graph definition, the weights, and external assets such as vocabulary files. It typically looks like this on disk:

├── assets
│   ├── src-vocab.txt
│   └── tgt-vocab.txt
├── saved_model.pb
└── variables
    └── variables.index

Models can be manually exported using the export run type:

onmt-main --config my_config.yml --auto_config export --export_dir ~/my-models/ende

Automatic evaluation during the training can also export models, see Training to learn more.

Running a SavedModel

When using an exported model, you need to know the input and output nodes of your model. You can use the saved_model_cli script provided by TensorFlow for inspection, e.g.:

saved_model_cli show --dir ~/my-models/ende \
    --tag_set serve --signature_def serving_default

Some examples using exported models are available in the examples/serving directory.

Input preprocessing and tokenization

TensorFlow Serving only runs TensorFlow operations. Preprocessing functions such as the tokenization is sometimes not implemented in terms of TensorFlow ops (see Tokenization for more details). In this case, these functions should be run outside of the TensorFlow engine, either by the client or a proxy server.

  • The OpenNMT-tf serving example uses the client approach to implement a simple interactive translation loop

  • The project nmt-wizard-docker uses the proxy server approach to wrap a TensorFlow Serving instance with a custom processing layer and REST API. Exported OpenNMT-tf models can integrated with this tool by following these instructions.


CTranslate2 is an optimized inference engine for OpenNMT models that is typically faster and more customizable than the TensorFlow runtime.

Selected models can be exported to the CTranslate2 format directly from OpenNMT-tf. An additional export_format option should be configured to select this export type:

onmt-main [...] export --export_dir ~/my-models/ende --export_format ctranslate2

The same option is available in the eval block of the YAML configuration when exporting models during the training.