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()