peacock-data-public-datasets-idc-llm_eval
/
env-llmeval
/lib
/python3.10
/site-packages
/torchgen
/api
/native.py
from typing import List, Optional, Sequence, Union | |
from torchgen import local | |
from torchgen.api import cpp | |
from torchgen.api.types import ( | |
ArgName, | |
BaseCType, | |
Binding, | |
boolT, | |
ConstRefCType, | |
CType, | |
deviceT, | |
layoutT, | |
ListCType, | |
MutRefCType, | |
NamedCType, | |
OptionalCType, | |
scalarT, | |
scalarTypeT, | |
tensorT, | |
) | |
from torchgen.model import ( | |
Argument, | |
FunctionSchema, | |
Return, | |
SelfArgument, | |
TensorOptionsArguments, | |
Type, | |
) | |
from torchgen.utils import assert_never | |
# This file describes the translation of JIT schema to the native functions API. | |
# This looks a lot like the C++ API (which makes historical sense, because the | |
# idea was you wrote native functions to implement functions in the C++ API), | |
# but over time we have evolved the C++ API without actually changing our | |
# native:: kernels. The intention is to make native API and dispatcher API | |
# line up as closely as possible, since this results in the least overhead | |
# (no translation is needed from dispatcher API to native API). | |
# | |
# NB: this is symint aware, you will get the non-SymInt variant for some | |
# dispatch entries and SymInt for others. | |
def name(func: FunctionSchema) -> str: | |
name = str(func.name.name) | |
# TODO: delete this! | |
if func.is_out_fn(): | |
name += "_out" | |
if func.name.overload_name: | |
name += f"_{func.name.overload_name}" | |
return name | |
def argumenttype_type( | |
t: Type, *, mutable: bool, binds: ArgName, symint: bool | |
) -> NamedCType: | |
if str(t) == "Tensor?": | |
tensor_type: OptionalCType = OptionalCType(BaseCType(tensorT)) | |
if mutable and not local.use_const_ref_for_mutable_tensors(): | |
return NamedCType(binds, MutRefCType(tensor_type)) | |
else: | |
return NamedCType(binds, ConstRefCType(tensor_type)) | |
elif str(t) == "Tensor?[]": | |
return NamedCType( | |
binds, ConstRefCType(ListCType(OptionalCType(BaseCType(tensorT)))) | |
) | |
elif str(t) == "Scalar": | |
return NamedCType(binds, ConstRefCType(BaseCType(scalarT))) | |
elif str(t) == "Scalar?": | |
return NamedCType(binds, ConstRefCType(OptionalCType(BaseCType(scalarT)))) | |
return cpp.argumenttype_type(t, mutable=mutable, binds=binds, symint=symint) | |
def returns_type(rs: Sequence[Return], *, symint: bool) -> CType: | |
return cpp.returns_type(rs, symint=symint) | |
def argument_type(a: Argument, *, binds: ArgName, symint: bool) -> NamedCType: | |
return argumenttype_type(a.type, mutable=a.is_write, binds=binds, symint=symint) | |
def argument( | |
a: Union[Argument, SelfArgument, TensorOptionsArguments], | |
*, | |
is_out: bool, | |
symint: bool, | |
) -> List[Binding]: | |
# Ideally, we NEVER default native functions. However, there are a number | |
# of functions that call native:: directly and rely on the defaulting | |
# existing. So for BC, we generate defaults for non-out variants (but not | |
# for out variants, where it is impossible to generate an appropriate | |
# default) | |
should_default = not is_out | |
if isinstance(a, Argument): | |
default: Optional[str] = None | |
if should_default and a.default is not None: | |
default = cpp.default_expr(a.default, a.type, symint=symint) | |
return [ | |
Binding( | |
nctype=argument_type(a, binds=a.name, symint=symint), | |
name=a.name, | |
default=default, | |
argument=a, | |
) | |
] | |
elif isinstance(a, SelfArgument): | |
# Erase SelfArgument from the distinction | |
return argument(a.argument, is_out=is_out, symint=symint) | |
elif isinstance(a, TensorOptionsArguments): | |
default = None | |
if should_default: | |
default = "{}" | |
# TODO: Not sure why the arguments assigned here are for | |
# TensorOptionsArguments and not the constituent pieces. It seems | |
# to matter | |
return [ | |
Binding( | |
nctype=NamedCType("dtype", OptionalCType(BaseCType(scalarTypeT))), | |
name="dtype", | |
default=default, | |
argument=a, | |
), | |
Binding( | |
nctype=NamedCType("layout", OptionalCType(BaseCType(layoutT))), | |
name="layout", | |
default=default, | |
argument=a, | |
), | |
Binding( | |
nctype=NamedCType("device", OptionalCType(BaseCType(deviceT))), | |
name="device", | |
default=default, | |
argument=a, | |
), | |
Binding( | |
nctype=NamedCType("pin_memory", OptionalCType(BaseCType(boolT))), | |
name="pin_memory", | |
default=default, | |
argument=a, | |
), | |
] | |
else: | |
assert_never(a) | |
def arguments(func: FunctionSchema, *, symint: bool) -> List[Binding]: | |
args: List[Union[Argument, TensorOptionsArguments, SelfArgument]] = [] | |
args.extend(func.arguments.non_out) | |
args.extend(func.arguments.out) | |
return [ | |
r for arg in args for r in argument(arg, symint=symint, is_out=func.is_out_fn()) | |
] | |