# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================

# LINT.IfChange(savedmodel_to_stablehlo)
def savedmodel_to_stablehlo(
    input_path: str,
    exported_model_signatures: list[str] = ["serving_default"],
    tag_names: list[str] = ["serve"],
    input_arg_shapes_str: str = "",
) -> bytes: ...
# LINT.ThenChange()

}  // namespace

PYBIND11_MODULE(pywrap_tensorflow_to_stablehlo, m) {
  m.doc() = "TensorFlow to StableHLO APIs.";

  // LINT.IfChange(savedmodel_to_stablehlo)
  m.def(
      "savedmodel_to_stablehlo",
      [](absl::string_view input_path,
         const std::vector<std::string>& exported_model_signatures =
             {"serving_default"},

* TensorFlow
* MLIR
* Abseil (absl)

## Python APIs


### `savedmodel_to_stablehlo`

Converts a TensorFlow SavedModel into StableHLO bytecode.

```Python
from tensorflow.compiler.mlir.tensorflow_to_stablehlo.python import pywrap_tensorflow_to_stablehlo as tf2shlo

stablehlo_bytes = tf2shlo.savedmodel_to_stablehlo(
        input_path="/path/to/your/savedmodel",

  def test_saved_model_to_stablehlo(self):
    with tempfile.TemporaryDirectory() as tempdir:
      path = build_savedmodel(tempdir)
      module_bytecode = tensorflow_to_stablehlo.savedmodel_to_stablehlo(
          input_path=path, input_arg_shapes_str='4'
      )
      with ir.Context() as ctx:
        stablehlo.register_dialect(ctx)
        module = ir.Module.parse(module_bytecode)