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from __future__ import annotations
import enum
from typing import Dict
from torch import _C
class ExportTypes:
r"""Specifies how the ONNX model is stored."""
PROTOBUF_FILE = "Saves model in the specified protobuf file."
ZIP_ARCHIVE = "Saves model in the specified ZIP file (uncompressed)."
COMPRESSED_ZIP_ARCHIVE = "Saves model in the specified ZIP file (compressed)."
DIRECTORY = "Saves model in the specified folder."
class SymbolicContext:
"""Extra context for symbolic functions.
Args:
params_dict (Dict[str, _C.IValue]): Mapping from graph initializer name to IValue.
env (Dict[_C.Value, _C.Value]): Mapping from Torch domain graph Value to ONNX domain graph Value.
cur_node (_C.Node): Current node being converted to ONNX domain.
onnx_block (_C.Block): Current ONNX block that converted nodes are being appended to.
"""
def __init__(
self,
params_dict: Dict[str, _C.IValue],
env: dict,
cur_node: _C.Node,
onnx_block: _C.Block,
):
self.params_dict: Dict[str, _C.IValue] = params_dict
self.env: Dict[_C.Value, _C.Value] = env
# Current node that is being converted.
self.cur_node: _C.Node = cur_node
# Current onnx block that converted nodes are being appended to.
self.onnx_block: _C.Block = onnx_block
@enum.unique
class RuntimeTypeCheckState(enum.Enum):
"""Runtime type check state."""
# Runtime type checking is disabled.
DISABLED = enum.auto()
# Runtime type checking is enabled but warnings are shown only.
WARNINGS = enum.auto()
# Runtime type checking is enabled.
ERRORS = enum.auto()
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