add api v1 compatibility

src/bentoml/_internal/frameworks/onnx.py

@@ -7,7 +7,6 @@
 from typing import TYPE_CHECKING
 
 import attr
-import numpy as np
 
 import bentoml
 from bentoml import Tag
@@ -17,25 +16,20 @@
 from bentoml.exceptions import BentoMLException
 from bentoml.exceptions import MissingDependencyException
 
-from ..types import LazyType
 from ..utils.pkg import get_pkg_version
 from ..utils.pkg import PackageNotFoundError
 from ..utils.onnx import gen_input_casting_func
-from ..runner.utils import Params
 
 if TYPE_CHECKING:
-    import torch  # noqa
 
     from bentoml.types import ModelSignature
     from bentoml.types import ModelSignatureDict
 
-    from .. import external_typing as ext
-    from ..external_typing import tensorflow as tf_ext  # noqa
-
-    ProvidersType = list[str | tuple[str, dict[str, t.Any]]]
     from ..utils.onnx import ONNXArgType
     from ..utils.onnx import ONNXArgCastedType
 
+    ProvidersType = list[str | tuple[str, dict[str, t.Any]]]
+
 
 try:
     import onnx
@@ -112,6 +106,16 @@ def get(tag_like: str | Tag) -> bentoml.Model:
     return model
 
 
+def _load_raw_model(bento_model: str | Tag | bentoml.Model) -> onnx.ModelProto:
+
+    if not isinstance(bento_model, bentoml.Model):
+        bento_model = get(bento_model)
+
+    model_path = bento_model.path_of(MODEL_FILENAME)
+    raw_model = onnx.load(model_path)
+    return raw_model
+
+
 def load_model(
     bento_model: str | Tag | bentoml.Model,
     *,
@@ -327,6 +331,25 @@ def get_runnable(bento_model: bentoml.Model) -> t.Type[bentoml.Runnable]:
     Private API: use :obj:`~bentoml.Model.to_runnable` instead.
     """
 
+    # backward compatibility for v1, load raw model to infer
+    # input_specs/output_specs for onnx model
+    if bento_model.info.api_version == "v1":
+
+        raw_model: onnx.ModelProto | None = None
+        options = t.cast(ONNXOptions, bento_model.info.options)
+
+        if not options.input_specs:
+            raw_model = _load_raw_model(bento_model)
+            run_input_specs = [MessageToDict(inp) for inp in raw_model.graph.input]
+            input_specs = {"run": run_input_specs}
+            bento_model = bento_model.with_options(input_specs=input_specs)
+
+        if not options.output_specs:
+            raw_model = raw_model or _load_raw_model(bento_model)
+            run_output_specs = [MessageToDict(out) for out in raw_model.graph.output]
+            output_specs = {"run": run_output_specs}
+            bento_model = bento_model.with_options(output_specs=output_specs)
+
     class ONNXRunnable(bentoml.Runnable):
         SUPPORTED_RESOURCES = ("nvidia.com/gpu", "cpu")
         SUPPORTS_CPU_MULTI_THREADING = True