# mypy: ignore-errors

from inspect import getattr_static
from typing import TYPE_CHECKING

from ..bytecode_transformation import create_call_function
from ..exc import Unsupported
from ..source import AttrSource
from .base import VariableTracker


if TYPE_CHECKING:
    from torch._dynamo.symbolic_convert import InstructionTranslator

PARAM_NAMES = "query key value attn_mask dropout is_causal enable_gqa".split()


class SDPAParamsVariable(VariableTracker):
    """Represents the c++ params struct for scaled dot product attention.
    This is a read-only container."""

    @staticmethod
    def create(tx: "InstructionTranslator", value, source):
        from torch.backends.cuda import SDPAParams

        from .torch import TorchInGraphFunctionVariable

        params = [
            VariableTracker.build(tx, getattr(value, p), AttrSource(source, p))
            for p in PARAM_NAMES
        ]
        return TorchInGraphFunctionVariable(SDPAParams).call_function(tx, params, {})

    def __init__(self, proxy, param_vars, **kwargs) -> None:
        self.proxy = proxy
        self.param_vars = param_vars
        super().__init__(**kwargs)

    def reconstruct(self, codegen):
        assert self.source is None
        assert self.param_vars is not None
        codegen.add_push_null(
            lambda: codegen.load_import_from("torch._C", "_SDPAParams")
        )
        codegen.foreach(self.param_vars)
        codegen.extend_output(create_call_function(len(self.param_vars), False))

    def as_proxy(self):
        return self.proxy

    def var_getattr(self, tx: "InstructionTranslator", name: str) -> VariableTracker:
        import torch._C

        from .builder import wrap_fx_proxy
        from .misc import GetAttrVariable

        try:
            getattr_static(torch._C._SDPAParams, name)
        except AttributeError:
            # Using raise from is too verbose here
            raise Unsupported(
                f"Unsupported torch._C._SDPAParams attribute {name}"
            ) from None

        proxy = GetAttrVariable.create_getattr_proxy(self.as_proxy(), name)
        if self.source is not None:
            return wrap_fx_proxy(
                tx=tx, proxy=proxy, source=AttrSource(self.source, name)
            )
        else:
            return wrap_fx_proxy(tx=tx, proxy=proxy)

    @staticmethod
    def is_sdpa_params(value):
        from torch.backends.cuda import SDPAParams

        return value is SDPAParams