[ONNX] Remove ExportTypes (#137789)

Remove deprecated ExportTypes and the `_exporter_states` module. Only protobuf (default) is supported going forward.

Differential Revision: [D64412947](https://our.internmc.facebook.com/intern/diff/D64412947)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/137789
Approved by: https://github.com/titaiwangms, https://github.com/xadupre

torch/onnx/__init__.py

@@ -24,7 +24,6 @@ __all__ = [
     "symbolic_opset19",
     "symbolic_opset20",
     # Enums
-    "ExportTypes",
     "OperatorExportTypes",
     "TrainingMode",
     "TensorProtoDataType",
@@ -57,7 +56,6 @@ from torch import _C
 from torch._C import _onnx as _C_onnx
 from torch._C._onnx import OperatorExportTypes, TensorProtoDataType, TrainingMode
 
-from ._exporter_states import ExportTypes
 from ._internal.exporter._onnx_program import ONNXProgram
 from ._internal.onnxruntime import (
     is_onnxrt_backend_supported,
@@ -115,7 +113,6 @@ if TYPE_CHECKING:
 # Set namespace for exposed private names
 DiagnosticOptions.__module__ = "torch.onnx"
 ExportOptions.__module__ = "torch.onnx"
-ExportTypes.__module__ = "torch.onnx"
 JitScalarType.__module__ = "torch.onnx"
 ONNXProgram.__module__ = "torch.onnx"
 ONNXRuntimeOptions.__module__ = "torch.onnx"

torch/onnx/_internal/onnx_proto_utils.py

@@ -4,19 +4,21 @@
 from __future__ import annotations
 
 import glob
-import io
 import os
 import shutil
-import zipfile
-from typing import Any, Mapping
+from typing import Any, Mapping, TYPE_CHECKING
 
 import torch
 import torch.jit._trace
 import torch.serialization
-from torch.onnx import _constants, _exporter_states, errors
+from torch.onnx import errors
 from torch.onnx._internal import jit_utils, registration
 
 
+if TYPE_CHECKING:
+    import io
+
+
 def export_as_test_case(
     model_bytes: bytes, inputs_data, outputs_data, name: str, dir: str
 ) -> str:
@@ -54,7 +56,6 @@ def export_as_test_case(
     _export_file(
         model_bytes,
         os.path.join(test_case_dir, "model.onnx"),
-        _exporter_states.ExportTypes.PROTOBUF_FILE,
         {},
     )
     data_set_dir = os.path.join(test_case_dir, "test_data_set_0")
@@ -163,47 +164,12 @@ def export_data(data, value_info_proto, f: str) -> None:
 def _export_file(
     model_bytes: bytes,
     f: io.BytesIO | str,
-    export_type: str,
     export_map: Mapping[str, bytes],
 ) -> None:
     """export/write model bytes into directory/protobuf/zip"""
-    if export_type == _exporter_states.ExportTypes.PROTOBUF_FILE:
-        assert len(export_map) == 0
-        with torch.serialization._open_file_like(f, "wb") as opened_file:
-            opened_file.write(model_bytes)
-    elif export_type in {
-        _exporter_states.ExportTypes.ZIP_ARCHIVE,
-        _exporter_states.ExportTypes.COMPRESSED_ZIP_ARCHIVE,
-    }:
-        compression = (
-            zipfile.ZIP_DEFLATED
-            if export_type == _exporter_states.ExportTypes.COMPRESSED_ZIP_ARCHIVE
-            else zipfile.ZIP_STORED
-        )
-        with zipfile.ZipFile(f, "w", compression=compression) as z:
-            z.writestr(_constants.ONNX_ARCHIVE_MODEL_PROTO_NAME, model_bytes)
-            for k, v in export_map.items():
-                z.writestr(k, v)
-    elif export_type == _exporter_states.ExportTypes.DIRECTORY:
-        if isinstance(f, io.BytesIO) or not os.path.isdir(f):  # type: ignore[arg-type]
-            raise ValueError(
-                f"f should be directory when export_type is set to DIRECTORY, instead get type(f): {type(f)}"
-            )
-        if not os.path.exists(f):  # type: ignore[arg-type]
-            os.makedirs(f)  # type: ignore[arg-type]
-
-        model_proto_file = os.path.join(f, _constants.ONNX_ARCHIVE_MODEL_PROTO_NAME)  # type: ignore[arg-type]
-        with torch.serialization._open_file_like(model_proto_file, "wb") as opened_file:
-            opened_file.write(model_bytes)
-
-        for k, v in export_map.items():
-            weight_proto_file = os.path.join(f, k)  # type: ignore[arg-type]
-            with torch.serialization._open_file_like(
-                weight_proto_file, "wb"
-            ) as opened_file:
-                opened_file.write(v)
-    else:
-        raise ValueError("Unknown export type")
+    assert len(export_map) == 0
+    with torch.serialization._open_file_like(f, "wb") as opened_file:
+        opened_file.write(model_bytes)
 
 
 def _add_onnxscript_fn(

torch/onnx/utils.py

@@ -20,13 +20,7 @@ import torch._C._onnx as _C_onnx
 import torch.jit._trace
 import torch.serialization
 from torch import _C
-from torch.onnx import (  # noqa: F401
-    _constants,
-    _deprecation,
-    _exporter_states,
-    errors,
-    symbolic_helper,
-)
+from torch.onnx import _constants, _deprecation, errors, symbolic_helper  # noqa: F401
 from torch.onnx._globals import GLOBALS
 from torch.onnx._internal import diagnostics, jit_utils, onnx_proto_utils, registration
 
@@ -1423,9 +1417,6 @@ def _export(
 ):
     assert GLOBALS.in_onnx_export is False
 
-    if export_type is None:
-        export_type = _exporter_states.ExportTypes.PROTOBUF_FILE
-
     if isinstance(model, torch.nn.DataParallel):
         raise ValueError(
             "torch.nn.DataParallel is not supported by ONNX "
@@ -1516,10 +1507,6 @@ def _export(
                 dynamic_axes=dynamic_axes,
             )
 
-            # TODO: Don't allocate a in-memory string for the protobuf
-            defer_weight_export = (
-                export_type is not _exporter_states.ExportTypes.PROTOBUF_FILE
-            )
             if custom_opsets is None:
                 custom_opsets = {}
 
@@ -1540,6 +1527,7 @@ def _export(
                     getattr(model, "training", False),  # type: ignore[arg-type]
                 )
             _C._jit_pass_onnx_assign_scoped_names_for_node_and_value(graph)
+            defer_weight_export = False
             if export_params:
                 (
                     proto,
@@ -1569,7 +1557,7 @@ def _export(
                     {},
                     opset_version,
                     dynamic_axes,
-                    False,
+                    defer_weight_export,
                     operator_export_type,
                     not verbose,
                     val_keep_init_as_ip,
@@ -1585,7 +1573,7 @@ def _export(
             )
             if verbose:
                 _C._jit_onnx_log("Exported graph: ", graph)
-            onnx_proto_utils._export_file(proto, f, export_type, export_map)
+            onnx_proto_utils._export_file(proto, f, export_map)
     finally:
         assert GLOBALS.in_onnx_export
         GLOBALS.in_onnx_export = False

torch/onnx/verification.py

@@ -26,7 +26,7 @@ import numpy.typing as npt
 import torch
 import torch._C._onnx as _C_onnx
 from torch import _C
-from torch.onnx import _constants, _experimental, _exporter_states, utils
+from torch.onnx import _constants, _experimental, utils
 from torch.onnx._globals import GLOBALS
 from torch.onnx._internal import onnx_proto_utils
 from torch.types import Number
@@ -893,8 +893,7 @@ def verify_aten_graph(
         graph, export_options, onnx_params_dict
     )
     model_f: str | io.BytesIO = io.BytesIO()
-    export_type = _exporter_states.ExportTypes.PROTOBUF_FILE
-    onnx_proto_utils._export_file(proto, model_f, export_type, export_map)
+    onnx_proto_utils._export_file(proto, model_f, export_map)
 
     # NOTE: Verification is unstable. Try catch to emit information for debugging.
     try: