Initial import: grid-bot — grid trading bot for BTC-USDT on Cifra Markets
This commit is contained in:
Kolp
@@ -0,0 +1,475 @@
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from __future__ import annotations
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from typing import TYPE_CHECKING
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from typing_extensions import assert_never
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from torchgen import local
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from torchgen.api.types import (
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ArgName,
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ArrayCType,
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ArrayRefCType,
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BaseCType,
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BaseTypeToCppMapping,
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Binding,
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boolT,
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ConstRefCType,
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CType,
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dimnameListT,
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intArrayRefT,
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iTensorListRefT,
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ListCType,
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longT,
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MutRefCType,
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NamedCType,
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OptionalCType,
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optionalIntArrayRefT,
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optionalSymIntArrayRefT,
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scalarT,
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SpecialArgName,
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symIntArrayRefT,
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SymIntT,
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tensorListT,
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tensorOptionsT,
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tensorT,
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TupleCType,
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VectorCType,
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voidT,
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)
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from torchgen.model import (
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Argument,
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Arguments,
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BaseTy,
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BaseType,
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FunctionSchema,
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ListType,
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NativeFunction,
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OptionalType,
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Return,
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SelfArgument,
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TensorOptionsArguments,
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Type,
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)
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if TYPE_CHECKING:
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from collections.abc import Sequence
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# This file describes the translation of JIT schema to the public C++
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# API, which is what people use when they call functions like at::add.
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#
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# Prominent characteristics of the C++ API:
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#
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# - dtype, layout, device and pin_memory are collected into
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# a single C++ type TensorOptions (the native functions API
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# also has this, but tensor options is really most relevant
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# for the C++ API; it makes calling kwarg factory functions
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# pleasant)
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#
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# - defaulting lives here (in fact, the dispatcher is completely
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# oblivious of defaults!)
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#
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# BTW: policy on name collisions: we try not to have types with
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# collisions, but functions are fair game to collide
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def name(
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func: FunctionSchema,
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*,
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faithful_name_for_out_overloads: bool = False,
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symint_overload: bool = False,
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) -> str:
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name = str(func.name.name)
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if symint_overload:
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name += "_symint"
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if func.is_out_fn():
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if faithful_name_for_out_overloads:
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name += "_outf"
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else:
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name += "_out"
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return name
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# Translation of "value types" in JIT schema to C++ API type. Value
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# types look the same no matter if they are argument types or return
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# types. Returns None if the type in question is not a value type.
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def valuetype_type(
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t: Type,
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*,
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binds: ArgName,
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mutable: bool = True,
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symint: bool = False,
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) -> NamedCType | None:
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if isinstance(t, BaseType):
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if t.name in (BaseTy.Tensor, BaseTy.Scalar):
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return None
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elif str(t) == "SymInt":
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if symint:
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return NamedCType(binds, BaseCType(SymIntT))
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else:
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return NamedCType(binds, BaseCType(longT))
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# All other BaseType currently map directly to BaseCppTypes.
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return NamedCType(binds, BaseCType(BaseTypeToCppMapping[t.name]))
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elif isinstance(t, OptionalType):
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elem = valuetype_type(t.elem, binds=binds, mutable=mutable, symint=symint)
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if elem is None:
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return None
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return NamedCType(binds, OptionalCType(elem.type))
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elif isinstance(t, ListType):
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if str(t.elem) == "bool":
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if t.size is None:
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raise AssertionError("bool ListType must have a size")
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return NamedCType(binds, ArrayCType(BaseCType(boolT), t.size))
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else:
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return None
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else:
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raise AssertionError(f"unrecognized type {repr(t)}")
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# Translation of types occurring in JIT arguments to a C++ argument type.
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# If remove_non_owning_ref_types is set, we'll guarantee that the output CType is not a non-owning reference type.
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# For example, we'll return std::vector<int> instead of IntArrayRef.
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# See Note [translation from C++ reference to value types]
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def argumenttype_type(
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t: Type,
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*,
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mutable: bool,
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binds: ArgName,
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remove_non_owning_ref_types: bool = False,
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symint: bool = False,
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) -> NamedCType:
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# If it's a value type, do the value type translation
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r = valuetype_type(
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t,
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binds=binds,
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mutable=mutable,
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symint=symint,
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)
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if r is not None:
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return r
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if isinstance(t, BaseType):
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if t.name == BaseTy.Tensor:
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if mutable and not local.use_const_ref_for_mutable_tensors():
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return NamedCType(binds, MutRefCType(BaseCType(tensorT)))
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else:
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return NamedCType(binds, ConstRefCType(BaseCType(tensorT)))
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elif t.name == BaseTy.Scalar:
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return NamedCType(binds, ConstRefCType(BaseCType(scalarT)))
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else:
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raise AssertionError(f"base type should have been value type {t}")
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elif isinstance(t, OptionalType):
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if str(t.elem) == "Tensor":
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if mutable and not local.use_const_ref_for_mutable_tensors():
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return NamedCType(
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binds, MutRefCType(BaseCType(tensorT))
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) # TODO: fix this discrepancy
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else:
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return NamedCType(
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binds, ConstRefCType(OptionalCType(BaseCType(tensorT)))
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)
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elif str(t.elem) == "Scalar":
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return NamedCType(binds, ConstRefCType(OptionalCType(BaseCType(scalarT))))
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elif isinstance(t.elem, ListType) and str(t.elem.elem) == "int":
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return NamedCType(binds, BaseCType(optionalIntArrayRefT))
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elif isinstance(t.elem, ListType) and str(t.elem.elem) == "SymInt":
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if symint:
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return NamedCType(binds, BaseCType(optionalSymIntArrayRefT))
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else:
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return NamedCType(binds, BaseCType(optionalIntArrayRefT))
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elem = argumenttype_type(t.elem, mutable=mutable, binds=binds, symint=symint)
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return NamedCType(binds, OptionalCType(elem.type))
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elif isinstance(t, ListType):
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# TODO: remove these special cases, ArrayRef fallthrough works fine
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if str(t.elem) == "int":
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if remove_non_owning_ref_types:
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return NamedCType(binds, VectorCType(BaseCType(longT)))
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else:
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return NamedCType(binds, BaseCType(intArrayRefT))
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if str(t.elem) == "SymInt":
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if remove_non_owning_ref_types:
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if symint:
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return NamedCType(binds, VectorCType(BaseCType(SymIntT)))
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else:
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return NamedCType(binds, VectorCType(BaseCType(longT)))
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else:
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if symint:
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return NamedCType(binds, BaseCType(symIntArrayRefT))
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else:
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return NamedCType(binds, BaseCType(intArrayRefT))
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if str(t.elem) == "Tensor":
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if local.use_ilistref_for_tensor_lists():
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return NamedCType(binds, ConstRefCType(BaseCType(iTensorListRefT)))
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else:
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return NamedCType(binds, BaseCType(tensorListT))
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elif str(t.elem) == "Scalar":
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return NamedCType(binds, ArrayRefCType(BaseCType(scalarT)))
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elif str(t.elem) == "Dimname":
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return NamedCType(binds, BaseCType(dimnameListT))
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elif str(t.elem) == "Tensor?":
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return NamedCType(
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binds, ConstRefCType(ListCType(OptionalCType(BaseCType(tensorT))))
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)
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elem = argumenttype_type(t.elem, mutable=mutable, binds=binds, symint=symint)
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return NamedCType(binds, ArrayRefCType(elem.type))
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else:
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raise AssertionError(f"unrecognized type {repr(t)}")
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# Translate a JIT argument into its C++ type
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def argument_type(a: Argument, *, binds: ArgName, symint: bool = False) -> NamedCType:
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return argumenttype_type(a.type, mutable=a.is_write, symint=symint, binds=binds)
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# Translation of a (non-multi) return type from JIT to C++
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# N.B: returntype_type returns a CType, not a NamedCType.
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# This is mostly because of the mismatch between return types and return names.
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# e.g. a function with a return type of 'void' has 0 return names,
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# and a function with a return type of 'std::tuple' has >1 return name.
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def returntype_type(t: Type, *, mutable: bool, symint: bool = False) -> CType:
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# placeholder is ignored
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# NB: symint is ALWAYS respected for return types. So symint argument
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# here is IGNORED
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r = valuetype_type(t, binds="__placeholder__", mutable=mutable, symint=True)
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if r is not None:
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return r.type
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if isinstance(t, BaseType):
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if t.name == BaseTy.Tensor:
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if mutable:
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if local.use_const_ref_for_mutable_tensors():
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return ConstRefCType(BaseCType(tensorT))
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else:
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return MutRefCType(BaseCType(tensorT))
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else:
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# Note [Tensor Copy Returns]
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# Currently, we use "Argument.is_write" to determine
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# whether or not Tensor return types should be copies or references.
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# If that ever changes, take a look at other locations of this note!
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return BaseCType(tensorT)
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elif t.name == BaseTy.Scalar:
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return BaseCType(scalarT)
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elif isinstance(t, ListType):
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if mutable:
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raise AssertionError(
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"Native functions should never return a mutable tensor list. "
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"They should return void."
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)
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elem = returntype_type(t.elem, mutable=False)
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if t.size is not None:
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raise AssertionError(f"fixed size list returns not supported: {t}")
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return VectorCType(elem)
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elif isinstance(t, OptionalType):
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elem = returntype_type(t.elem, mutable=mutable)
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if str(t.elem) == "Tensor":
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return OptionalCType(elem)
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raise AssertionError(f"unrecognized return type {t}")
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# Translation of a single return to its C++ type
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def return_type(r: Return, *, symint: bool = False) -> CType:
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return returntype_type(r.type, mutable=r.is_write, symint=symint)
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# Translation of a full (possibly multi) return from JIT to its C++ type
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def returns_type(rs: Sequence[Return], *, symint: bool = False) -> CType:
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if len(rs) == 0:
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return BaseCType(voidT)
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elif len(rs) == 1:
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return return_type(rs[0], symint=symint)
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else:
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return TupleCType([return_type(r, symint=symint) for r in rs])
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def return_names(f: NativeFunction, *, fallback_name: str = "result") -> Sequence[str]:
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returns: list[str] = []
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for i, r in enumerate(f.func.returns):
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# If we have an inplace function, the return argument is
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# implicitly named self.
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# TODO: Consider incorporating this into the data model
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if f.func.name.name.inplace:
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if i != 0:
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raise AssertionError("illegal inplace function with multiple returns")
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name = "self"
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# If we are out function, the name is the name of the
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# corresponding output function (r.name will get recorded
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# in field_name later.)
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elif f.func.is_out_fn():
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name = f.func.arguments.out[i].name
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# If the return argument is explicitly named...
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elif r.name:
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name_conflict = any(
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r.name == a.name for a in f.func.schema_order_arguments()
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)
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if name_conflict and not f.func.is_out_fn():
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name = f"{r.name}_return"
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else:
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name = r.name
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# If there is no explicit name and no fallback name was passed in, we just name the output result,
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# unless it's a multi-return, in which case it's result0,
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# result1, etc (zero-indexed)
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else:
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name = fallback_name if len(f.func.returns) == 1 else f"{fallback_name}{i}"
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returns.append(name)
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return returns
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JIT_TO_CPP_DEFAULT = {
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"False": "false",
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"True": "true",
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"None": "::std::nullopt", # UGH this one is type directed
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"Mean": "at::Reduction::Mean",
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"[]": "{}",
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"contiguous_format": "c10::MemoryFormat::Contiguous",
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"long": "at::kLong",
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||||
}
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||||
|
||||
|
||||
# Convert a JIT default into C++ expression representing the default
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||||
def default_expr(d: str, t: Type, *, symint: bool) -> str:
|
||||
if d == "None" and str(t) == "Tensor?":
|
||||
return "{}"
|
||||
if isinstance(t, BaseType) and t.name is BaseTy.str:
|
||||
# Schema allows single quotes but C++ needs double
|
||||
if len(d) >= 2 and d[0] == "'" and d[-1] == "'":
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s = ""
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i = 1
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||||
while i + 1 < len(d):
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||||
if d[i] != "\\":
|
||||
if d[i] == '"':
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||||
s += '\\"'
|
||||
else:
|
||||
s += d[i]
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||||
i += 1
|
||||
else:
|
||||
if d[i + 1] == "'":
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||||
s += "'"
|
||||
else:
|
||||
s += d[i : i + 2]
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||||
i += 2
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||||
|
||||
return f'"{s}"'
|
||||
|
||||
if isinstance(t, OptionalType):
|
||||
if d == "None":
|
||||
return "::std::nullopt"
|
||||
|
||||
return default_expr(d, t.elem, symint=symint)
|
||||
|
||||
if isinstance(t, ListType):
|
||||
if d.startswith("[") and d.endswith("]"):
|
||||
return "{" + d[1:-1] + "}"
|
||||
elif symint and d.isdigit() and str(t.elem) == "SymInt":
|
||||
return f"c10::SymInt({d})"
|
||||
elif t.size is None:
|
||||
# NOTE: Sized lists can have scalar defaults
|
||||
raise ValueError(f"Expected a list default '[...]' but found: '{d}'")
|
||||
|
||||
return JIT_TO_CPP_DEFAULT.get(d, d)
|
||||
|
||||
|
||||
# Convert an argument into its C++ API form
|
||||
|
||||
|
||||
def argument(
|
||||
a: Argument | TensorOptionsArguments | SelfArgument,
|
||||
*,
|
||||
cpp_no_default_args: set[str],
|
||||
method: bool,
|
||||
faithful: bool,
|
||||
symint: bool = False,
|
||||
has_tensor_options: bool,
|
||||
) -> list[Binding]:
|
||||
def sub_argument(
|
||||
a: Argument | TensorOptionsArguments | SelfArgument,
|
||||
) -> list[Binding]:
|
||||
return argument(
|
||||
a,
|
||||
cpp_no_default_args=cpp_no_default_args,
|
||||
method=method,
|
||||
faithful=faithful,
|
||||
symint=symint,
|
||||
has_tensor_options=has_tensor_options,
|
||||
)
|
||||
|
||||
if isinstance(a, Argument):
|
||||
binds: ArgName
|
||||
if a.name == "memory_format" and has_tensor_options:
|
||||
binds = SpecialArgName.possibly_redundant_memory_format
|
||||
else:
|
||||
binds = a.name
|
||||
default: str | None = None
|
||||
if a.name not in cpp_no_default_args and a.default is not None:
|
||||
default = default_expr(a.default, a.type, symint=symint)
|
||||
return [
|
||||
Binding(
|
||||
nctype=argument_type(a, binds=binds, symint=symint),
|
||||
name=a.name,
|
||||
default=default,
|
||||
argument=a,
|
||||
)
|
||||
]
|
||||
elif isinstance(a, TensorOptionsArguments):
|
||||
if faithful:
|
||||
return (
|
||||
sub_argument(a.dtype)
|
||||
+ sub_argument(a.layout)
|
||||
+ sub_argument(a.device)
|
||||
+ sub_argument(a.pin_memory)
|
||||
)
|
||||
else:
|
||||
default = None
|
||||
# Enforced by NativeFunction.__post_init__
|
||||
if "options" in cpp_no_default_args:
|
||||
raise AssertionError("'options' should not be in cpp_no_default_args")
|
||||
if all(x.default == "None" for x in a.all()):
|
||||
default = "{}"
|
||||
elif a.dtype.default == "long":
|
||||
default = "at::kLong" # TODO: this is wrong
|
||||
return [
|
||||
Binding(
|
||||
nctype=NamedCType("options", BaseCType(tensorOptionsT)),
|
||||
name="options",
|
||||
default=default,
|
||||
argument=a,
|
||||
)
|
||||
]
|
||||
elif isinstance(a, SelfArgument):
|
||||
if method:
|
||||
# Caller is responsible for installing implicit this in context!
|
||||
return []
|
||||
else:
|
||||
return sub_argument(a.argument)
|
||||
else:
|
||||
assert_never(a)
|
||||
|
||||
|
||||
def arguments(
|
||||
arguments: Arguments,
|
||||
*,
|
||||
faithful: bool,
|
||||
symint: bool = False,
|
||||
method: bool,
|
||||
cpp_no_default_args: set[str],
|
||||
) -> list[Binding]:
|
||||
args: list[Argument | TensorOptionsArguments | SelfArgument] = []
|
||||
if faithful:
|
||||
args.extend(arguments.non_out)
|
||||
args.extend(arguments.out)
|
||||
else:
|
||||
args.extend(arguments.out)
|
||||
args.extend(arguments.non_out)
|
||||
return [
|
||||
r.no_default() if faithful else r
|
||||
for a in args
|
||||
for r in argument(
|
||||
a,
|
||||
faithful=faithful,
|
||||
symint=symint,
|
||||
method=method,
|
||||
has_tensor_options=arguments.tensor_options is not None,
|
||||
cpp_no_default_args=cpp_no_default_args,
|
||||
)
|
||||
]
|
||||
Reference in New Issue
Block a user