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# mypy: ignore-errors
"""
Constant and enum variable tracking in Dynamo.
This module is fundamental to Dynamo's ability to track and propagate constant
values during compilation, ensuring proper handling of Python literals and
maintaining type safety through the compilation process.
"""
import operator
from typing import TYPE_CHECKING
import torch
from torch._dynamo.source import AttrSource, GetItemSource
from .. import graph_break_hints, variables
from ..exc import raise_observed_exception, unimplemented_v2
from ..utils import cmp_name_to_op_mapping, common_constant_types, istype, np
from .base import VariableTracker
if TYPE_CHECKING:
from torch._dynamo.symbolic_convert import InstructionTranslator
class ConstantVariable(VariableTracker):
"""
Variable tracker for Python literals and basic immutable types, with automatic
routing support for collection types (lists, tuples, sets, etc.).
The create() method intelligently constructs appropriate variable types for
nested collections.
"""
@staticmethod
def create(value, **kwargs) -> VariableTracker:
"""
Create a `ConstantVariable` based on the given value, and supports
automatic routing for collection types like `tuple` (in which case we'd
create `ConstantVariable` for the leaf items).
NOTE: the caller must install the proper guards if needed; most often
the guard will be `CONSTANT_MATCH`.
"""
source = kwargs.get("source", None)
# Routing for supported collection literals.
if isinstance(value, set):
items = [ConstantVariable.create(x) for x in value]
return variables.SetVariable(items, **kwargs)
elif isinstance(value, frozenset):
items = [ConstantVariable.create(x) for x in value]
return variables.FrozensetVariable(items, **kwargs)
elif isinstance(value, (list, tuple)):
items = []
for i, x in enumerate(value):
item_source = GetItemSource(source, i) if source else None
items.append(
ConstantVariable.create(
x,
source=item_source,
)
)
return variables.BaseListVariable.cls_for(type(value))(items, **kwargs)
return ConstantVariable(value, **kwargs)
def __init__(self, value, **kwargs) -> None:
super().__init__(**kwargs)
assert ConstantVariable.is_base_literal(value), f"""
Cannot construct `ConstantVariable` for value of type {type(value)}.
This failure likely due to PyTorch-internal use of `ConstantVariable` on
non-literal python values, please try using `VariableTracker.build` instead. If
you believe it's a necessary and legitimate use case (the value is immutable and
can't easily be represented with another `VariableTracker` class), please add
its type to `common_constant_types`.
"""
if np is not None and isinstance(value, np.number):
self.value = value.item()
else:
self.value = value
def as_proxy(self):
return self.value
def __repr__(self) -> str:
return f"ConstantVariable({type(self.value).__name__}: {repr(self.value)})"
def as_python_constant(self):
return self.value
def is_python_constant(self):
return True
@property
def items(self):
"""
Need this when adding a BaseListVariable and a ConstantVariable together.
Happens in detectron2.
"""
return self.unpack_var_sequence(tx=None)
def getitem_const(self, tx: "InstructionTranslator", arg: VariableTracker):
return ConstantVariable.create(
self.value[arg.as_python_constant()],
)
@staticmethod
def is_base_literal(obj):
return type(obj) in common_constant_types
@staticmethod
def is_literal(obj):
if type(obj) in (list, tuple, set, frozenset, torch.Size):
return all(ConstantVariable.is_literal(x) for x in obj)
return ConstantVariable.is_base_literal(obj)
def unpack_var_sequence(self, tx):
try:
return [ConstantVariable.create(x) for x in self.as_python_constant()]
except TypeError as e:
raise NotImplementedError from e
def const_getattr(self, tx: "InstructionTranslator", name):
if not hasattr(self.value, name):
raise NotImplementedError
member = getattr(self.value, name)
if callable(member):
raise NotImplementedError
return member
def call_method(
self,
tx: "InstructionTranslator",
name,
args: "list[VariableTracker]",
kwargs: "dict[str, VariableTracker]",
) -> "VariableTracker":
from .tensor import SymNodeVariable
if name == "format" and istype(self.value, str):
return variables.BuiltinVariable(str.format).call_function(
tx, [self, *args], kwargs
)
elif name == "join" and istype(self.value, str):
assert len(args) == 1 and len(kwargs) == 0
arg_unpacked = args[0].force_unpack_var_sequence(tx)
try:
arg_const = [x.as_python_constant() for x in arg_unpacked]
return ConstantVariable.create(self.value.join(arg_const))
except NotImplementedError:
return super().call_method(tx, name, args, kwargs)
if any(isinstance(x, SymNodeVariable) for x in args):
# Promote to SymNodeVariable for operations involving dynamic shapes.
return variables.SymNodeVariable(self.as_proxy(), self.value).call_method(
tx, name, args, kwargs
)
try:
const_args = [a.as_python_constant() for a in args]
const_kwargs = {k: v.as_python_constant() for k, v in kwargs.items()}
except NotImplementedError:
return super().call_method(tx, name, args, kwargs)
if isinstance(self.value, str) and name in str.__dict__.keys():
method = getattr(self.value, name)
try:
return ConstantVariable.create(method(*const_args, **const_kwargs))
except Exception as e:
raise_observed_exception(type(e), tx)
elif isinstance(self.value, (float, int)):
if not (args or kwargs):
return ConstantVariable.create(getattr(self.value, name)())
if (
hasattr(operator, name)
and len(args) == 1
and args[0].is_python_constant()
):
add_target = const_args[0]
op = getattr(operator, name)
if isinstance(
add_target, (torch.SymBool, torch.SymFloat, torch.SymInt)
):
# Addition between a non sym and sym makes a sym
proxy = tx.output.create_proxy(
"call_function", op, (self.value, add_target), {}
)
return SymNodeVariable.create(tx, proxy, add_target)
else:
try:
return ConstantVariable.create(op(self.value, add_target))
except Exception as e:
raise_observed_exception(
type(e), tx, args=list(map(ConstantVariable.create, e.args))
)
elif isinstance(self.value, bytes) and name == "decode":
method = getattr(self.value, name)
return ConstantVariable.create(method(*const_args, **const_kwargs))
if name == "__len__" and not (args or kwargs):
return ConstantVariable.create(len(self.value))
elif name == "__round__" and len(args) == 1 and args[0].is_python_constant():
return ConstantVariable.create(
round(self.value, args[0].as_python_constant())
)
elif name == "__contains__" and len(args) == 1 and args[0].is_python_constant():
assert not kwargs
search = args[0].as_python_constant()
result = search in self.value
return ConstantVariable.create(result)
return super().call_method(tx, name, args, kwargs)
def call_obj_hasattr(
self, tx: "InstructionTranslator", name: str
) -> "VariableTracker":
result = hasattr(self.value, name)
return variables.ConstantVariable.create(result)
class EnumVariable(VariableTracker):
"""VariableTracker for enum.Enum and enum.IntEnum instances
Provides specialized handling for Python enum types, supporting
both standard Enum and IntEnum with proper value tracking and comparison.
"""
def __init__(self, value, **kwargs) -> None:
super().__init__(**kwargs)
self.value = value
@classmethod
def create(cls, cls_type, value_vt, options):
if isinstance(value_vt, variables.ConstantVariable):
for member in list(cls_type):
if member.value == value_vt.as_python_constant():
return cls(member, **options)
unimplemented_v2(
gb_type="Failed to construct Enum variable",
context=f"value: {value_vt}, allowed enum values: {list(cls_type)}",
explanation="Attempted to construct an Enum value that is non-constant (e.g. int, string) "
"or is not an acceptable value for the Enum. "
f"Acceptable values for Enum `{cls_type}`: {list(cls_type)}.",
hints=[*graph_break_hints.USER_ERROR, *graph_break_hints.SUPPORTABLE],
)
def as_proxy(self):
if isinstance(self.value, int):
return int(self.value) # convert IntEnum to a normal int
return self.value
def __repr__(self) -> str:
return f"EnumVariable({type(self.value)})"
def as_python_constant(self):
return self.value
def var_getattr(self, tx: "InstructionTranslator", name):
if not hasattr(self.value, name):
raise NotImplementedError
if name in cmp_name_to_op_mapping:
return variables.GetAttrVariable(self, name)
member = getattr(self.value, name)
source = self.source and AttrSource(self.source, name)
return VariableTracker.build(tx, member, source=source)
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