pytorch/tools/codegen/api/native.py
Edward Yang 9b0ffb9fb3 Delete cpp.group_arguments (#49043)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/49043

Previously, this function had nontrivial algorithmic content,
but after #48195, this was just a swiss army knife for pasting
together arguments while maintaining structure.  I added some
more properties for Arguments for convenient access in this way,
and then inlined the implementation of group_arguments into all of its call
sites, simplifying whenever contextual.  This might be controversial, but I
think the resulting code is easier to understand.

You may notice that there is some modest code duplication between
dispatcher.cpparguments_exprs and CppSignature.argument_packs.
This is a known problem and I will be attempting to fix it in
a follow up PR.

Confirmed to be byte-for-byte compatible.

Signed-off-by: Edward Z. Yang <ezyang@fb.com>

Test Plan: Imported from OSS

Reviewed By: H-Huang

Differential Revision: D25455885

Pulled By: ezyang

fbshipit-source-id: 8fbe066e8c3cb7ee8adb5b87296ec5bd7b49e01f
2020-12-10 18:20:46 -08:00

116 lines
4.2 KiB
Python

from tools.codegen.model import *
from tools.codegen.api.types import NativeArgument
import tools.codegen.api.cpp as cpp
from tools.codegen import local
from typing import Union, Sequence, Tuple, List
# 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).
#
# When a function is not use_c10_dispatcher: full, the dispatcher API actually
# coincides with the native:: API (e.g., we do as dumb as pass through as
# possible).
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) -> str:
if str(t) == 'Tensor?':
if mutable:
return 'Tensor &'
else:
return 'const Tensor &'
elif str(t) == 'Tensor?[]':
return 'TensorList'
return cpp.argumenttype_type(t, mutable=mutable)
def returns_type(rs: Sequence[Return]) -> str:
return cpp.returns_type(rs)
def argument_type(a: Argument) -> str:
return argumenttype_type(a.type, mutable=a.is_write)
def argument(a: Union[Argument, SelfArgument, TensorOptionsArguments]) -> Sequence[NativeArgument]:
if isinstance(a, Argument):
return [NativeArgument(
type=argument_type(a),
name=a.name,
default=cpp.default_expr(a.default, a.type) if a.default is not None else None,
argument=a,
)]
elif isinstance(a, SelfArgument):
# Erase SelfArgument from the distinction
return [NativeArgument(
type=argument_type(a.argument),
name=a.argument.name,
default=None,
argument=a.argument,
)]
elif isinstance(a, TensorOptionsArguments):
if local.use_c10_dispatcher() in [UseC10Dispatcher.hacky_wrapper_for_legacy_signatures,
UseC10Dispatcher.with_codegenerated_unboxing_wrapper]:
# TODO: expunge this logic entirely
default = None
if all(x.default == "None" for x in a.all()):
default = '{}'
elif a.dtype.default == "long":
default = 'at::kLong' # TODO: this is wrong
return [NativeArgument(
type='const TensorOptions &',
name='options',
default=default,
argument=a,
)]
else:
assert local.use_c10_dispatcher() == UseC10Dispatcher.full
return [
NativeArgument(
type='c10::optional<ScalarType>',
name='dtype',
default='{}',
argument=a,
),
NativeArgument(
type='c10::optional<Layout>',
name='layout',
default='{}',
argument=a,
),
NativeArgument(
type='c10::optional<Device>',
name='device',
default='{}',
argument=a,
),
NativeArgument(
type='c10::optional<bool>',
name='pin_memory',
default='{}',
argument=a,
)]
else:
assert_never(a)
def arguments(func: FunctionSchema) -> Tuple[NativeArgument, ...]:
args: List[Union[Argument, TensorOptionsArguments, SelfArgument]] = []
if local.use_c10_dispatcher() is UseC10Dispatcher.full:
args.extend(func.arguments.non_out)
args.extend(func.arguments.out)
else:
args.extend(func.arguments.out)
args.extend(func.arguments.non_out)
return tuple(i for arg in args for i in argument(arg))