blob: 50831df06a3bd09fa395bc59d99358e9562f447f [file] [log] [blame]
import collections
from enum import Enum
from typing import Any, Callable, Dict, List, Optional, Set
from .. import variables
from ..current_scope_id import current_scope_id
from ..exc import unimplemented
from ..source import AttrSource, Source
from ..utils import dict_values, identity, istype, odict_values
class MutableLocalSource(Enum):
"""
If the VariableTracker.mutable_local represents a Variable that:
- already existed that Dynamo began tracking while introspection (Existing)
- is a new variable that is created during Dynamo introspection (Local)
"""
Existing = 0
Local = 1
class MutableLocalBase:
"""
Base class for Variable.mutable_local
"""
def __init__(self, typ: MutableLocalSource):
# In HigherOrderOperator tracing, we need to distinguish
# between MutableLocals inside the HigherOrderOperator and
# ones outside it. For example, it is not safe to mutate
# `a` in the following example because it was constructed
# in a different scope.
#
# def f(x):
# a = 1
# def g(x):
# nonlocal a
# a = 2
# return x
# return wrap(g, x) + a
#
# We use self.scope to distinguish this.
# scope == 0: The object was an existing variable
# scope == 1: The object was created while Dynamo
# was introspecting a function
# (and no HigherOrderOps were involved)
# scope >= 2: The object was created through
# Dynamo introspection of a HigherOrderOp.
# The exact number corresponds to the level
# of nested HigherOrderOps.
if typ is MutableLocalSource.Existing:
self.scope = 0
elif typ is MutableLocalSource.Local:
self.scope = current_scope_id()
else:
unimplemented(f"Unsupported MutableLocalSource: {typ}")
class MutableLocal(MutableLocalBase):
"""
Marker used to indicate this (list, iter, etc) was constructed in
local scope and can be mutated safely in analysis without leaking
state.
"""
def __init__(self):
super().__init__(MutableLocalSource.Local)
def __hash__(self):
return id(self)
def __eq__(self, other):
return self is other
def _is_top_level_scope(scope_id):
return scope_id == 1
def is_side_effect_safe(m: MutableLocalBase):
scope_id = current_scope_id()
# In the top-level scope (if no HigherOrderOperators are involved),
# we are allowed to modify variables created in this scope as well
# as existing variables.
if _is_top_level_scope(scope_id):
return True
# Otherwise, only allow local mutation of variables created in the current scope
return m.scope == scope_id
# metaclass to call post_init
class HasPostInit(type):
def __call__(cls, *args, **kwargs):
obj = type.__call__(cls, *args, **kwargs)
obj.__post_init__(*args, **kwargs)
return obj
class VariableTracker(metaclass=HasPostInit):
"""
Base class for tracked locals and stack values
VariableTracker instances are immutable and should be copied in
order to change them.
"""
# fields to leave unmodified in apply()
_nonvar_fields = {
"value",
"guards",
"source",
"mutable_local",
"recursively_contains",
"user_code_variable_name",
}
@staticmethod
def propagate(*vars: List[List["VariableTracker"]]):
"""Combine the guards from many VariableTracker into **kwargs for a new instance"""
guards = set()
def visit(var):
if type(var) in (list, tuple, dict_values, odict_values):
for i in var:
visit(i)
else:
assert isinstance(var, VariableTracker), typestr(var)
guards.update(var.guards)
visit(vars)
return {
"guards": guards,
}
def clone(self, **kwargs):
"""Shallow copy with some (optional) changes"""
args = dict(self.__dict__)
args.update(kwargs)
return self.__class__(**args)
@classmethod
def copy(cls, value):
"""Deeper (but not full) copy, leaving FX and user objects alone"""
return cls.apply(identity, value)
@classmethod
def apply(
cls,
fn: Callable[["VariableTracker"], "VariableTracker"],
value,
cache=None,
skip_fn=lambda _: False, # Whether we should skip applying to this var
update_contains=False,
):
"""
Walk this object and call fn on all the VariableTracker
instances to produce a new VariableTracker with the results.
"""
if cache is None:
cache = dict()
idx = id(value)
if idx in cache:
return cache[idx][0]
if isinstance(value, VariableTracker):
if not skip_fn(value):
updated_dict = dict(value.__dict__)
for key in updated_dict.keys():
if key not in value._nonvar_fields:
updated_dict[key] = cls.apply(
fn, updated_dict[key], cache, skip_fn
)
result = fn(value.clone(**updated_dict))
if update_contains is False:
result._update_contains()
else:
result = fn(value)
elif istype(value, list):
result = [cls.apply(fn, v, cache, skip_fn, update_contains) for v in value]
elif istype(value, tuple):
result = tuple(
cls.apply(fn, v, cache, skip_fn, update_contains) for v in value
)
elif istype(value, collections.OrderedDict):
result = collections.OrderedDict(
cls.apply(fn, v, cache, skip_fn, update_contains) for v in value.items()
)
elif istype(value, dict):
result = {
k: cls.apply(fn, v, cache, skip_fn, update_contains)
for k, v in list(value.items())
}
else:
result = value
# save `value` to keep it alive and ensure id() isn't reused
cache[idx] = (result, value)
return result
def add_guard(self, guard):
return self.clone(guards=set.union(self.guards, {guard}))
def add_guards(self, guards):
if guards is None:
return self
assert isinstance(guards, set)
return self.clone(guards=set.union(self.guards, guards))
def add_options(self, options, *more):
if more:
return self.add_options(options).add_options(*more)
if isinstance(options, VariableTracker):
return self.add_guards(options.guards)
assert isinstance(options, dict)
return self.add_guards(options.get("guards", set()))
def __str__(self):
return f"{self.__class__.__name__}()"
def __repr__(self):
return str(self)
def python_type(self):
raise NotImplementedError(f"{self} has no type")
def var_type(self):
"""
Similar to python_type but
returns a VariableTracker containing the type.
"""
raise NotImplementedError(f"{self} has no variable tracker-ed type")
def as_python_constant(self):
"""For constants"""
raise NotImplementedError(f"{self} is not a constant")
def is_python_constant(self):
try:
self.as_python_constant()
return True
except NotImplementedError:
return False
def as_specialized(self, tx):
"""
For specialized variables, return itself,
For unspecialized variables, convert to constant variable and return.
"""
return self
def can_make_guard(self):
try:
self.make_guard(None)
return True
except NotImplementedError:
return False
def make_guard(self, fn):
if self.source:
return self.source.make_guard(fn)
raise NotImplementedError()
def replace_guards(self, guards, *fns):
name = self.source.name()
new_guards = {g for g in (guards or []) if g.name != name}
new_guards.update(self.source.make_guard(fn) for fn in fns)
return new_guards
def const_getattr(self, tx, name: str) -> Any:
"""getattr(self, name) returning a python constant"""
raise NotImplementedError()
def var_getattr(self, tx, name: str) -> "VariableTracker":
"""getattr(self, name) returning a new variable"""
options = VariableTracker.propagate(self)
value = self.const_getattr(tx, name)
if not variables.ConstantVariable.is_literal(value):
raise NotImplementedError()
if self.source:
options["source"] = AttrSource(self.source, name)
return variables.ConstantVariable.create(value, **options)
def is_proxy(self):
try:
self.as_proxy()
return True
except NotImplementedError:
return False
def as_proxy(self):
raise NotImplementedError(str(self))
def reconstruct(self, codegen):
raise NotImplementedError()
def unpack_var_sequence(self, tx):
raise NotImplementedError()
def has_unpack_var_sequence(self, tx):
try:
self.unpack_var_sequence(tx)
return True
except NotImplementedError:
return False
def num_parameters(self):
unimplemented(f"num_parameters: {self}")
def call_hasattr(self, tx, name: str) -> "VariableTracker":
unimplemented(f"hasattr: {repr(self)}")
def call_function(
self, tx, args: "List[VariableTracker]", kwargs: "Dict[str, VariableTracker]"
) -> "VariableTracker":
unimplemented(f"call_function {self} {args} {kwargs}")
def call_method(
self,
tx,
name,
args: "List[VariableTracker]",
kwargs: "Dict[str, VariableTracker]",
) -> "VariableTracker":
if name == "__len__" and self.has_unpack_var_sequence(tx):
assert not (args or kwargs)
return variables.ConstantVariable.create(
len(self.unpack_var_sequence(tx)), **VariableTracker.propagate(self)
)
elif (
name == "__getattr__"
and len(args) == 1
and args[0].is_python_constant()
and not kwargs
):
return self.var_getattr(tx, args[0].as_python_constant()).add_options(
self, args[0]
)
raise unimplemented(f"call_method {self} {name} {args} {kwargs}")
def rename(self, tx, name):
new_name = tx.output.new_var(name)
if not self.mutable_local or not isinstance(self.mutable_local, MutableLocal):
# This is fine for objects that are not mutable locals
self.user_code_variable_name = new_name
return self
new_vt = self.clone(user_code_variable_name=new_name)
return tx.replace_all(self, new_vt)
def __init__(
self,
guards: Optional[Set] = None,
source: Source = None,
mutable_local: MutableLocal = None,
recursively_contains: Optional[Set] = None,
user_code_variable_name: str = None,
):
super().__init__()
self.guards = guards or set()
self.source = source
self.mutable_local = mutable_local
self.recursively_contains = (
recursively_contains # provides hint to replace_all when replacing vars
)
self.user_code_variable_name = user_code_variable_name
def __post_init__(self, *args, **kwargs):
if self.recursively_contains is None:
self.recursively_contains = set()
VariableTracker.apply(
self._aggregate_mutables, self, skip_fn=lambda var: var is not self
)
assert None not in self.recursively_contains
def _aggregate_mutables(self, var):
self.recursively_contains.update(var.recursively_contains)
if var.mutable_local is not None:
self.recursively_contains.add(var.mutable_local)
return var
# This is used to forcely update self.recursively_contains
def _update_contains(self):
self.recursively_contains = set()
VariableTracker.apply(
self._aggregate_mutables,
self,
skip_fn=lambda var: var is not self,
update_contains=True,
)
assert None not in self.recursively_contains
def typestr(*objs):
if len(objs) == 1:
(obj,) = objs
if isinstance(obj, VariableTracker):
return str(obj)
else:
return type(obj).__name__
else:
return " ".join(map(typestr, objs))