421 lines
13 KiB
Python
421 lines
13 KiB
Python
# mypy: ignore-errors
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import collections
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from enum import Enum
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from typing import Any, Callable, Dict, List
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from .. import variables
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from ..current_scope_id import current_scope_id
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from ..exc import unimplemented
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from ..source import AttrSource, Source
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from ..utils import identity, istype
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class MutableLocalSource(Enum):
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"""
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If the VariableTracker.mutable_local represents a Variable that:
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- already existed that Dynamo began tracking while introspection (Existing)
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- is a new variable that is created during Dynamo introspection (Local)
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"""
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Existing = 0
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Local = 1
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class ParentsTracker:
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"""
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This is a perf optimization to limit the number of objects we need to visit in tx.replace_all.
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This must be a seperate object so that it is not cloned in apply.
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"""
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def __init__(self):
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# logically this is a set, but we use a dict to ensure deterministic ordering
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self.parents: Dict[ParentsTracker, bool] = dict()
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def add(self, parent):
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self.parents[parent] = True
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def recursive_parents(self):
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rv = dict(self.parents)
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worklist = list(self.parents)
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while worklist:
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for parent in worklist.pop().parents:
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if parent not in rv:
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assert isinstance(parent, ParentsTracker)
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rv[parent] = True
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worklist.append(parent)
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return rv.keys()
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class MutableLocalBase:
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"""
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Base class for Variable.mutable_local
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"""
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def __init__(self, typ: MutableLocalSource):
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# In HigherOrderOperator tracing, we need to distinguish
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# between MutableLocals inside the HigherOrderOperator and
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# ones outside it. For example, it is not safe to mutate
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# `a` in the following example because it was constructed
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# in a different scope.
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#
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# def f(x):
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# a = 1
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# def g(x):
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# nonlocal a
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# a = 2
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# return x
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# return wrap(g, x) + a
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#
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# We use self.scope to distinguish this.
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# scope == 0: The object was an existing variable
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# scope == 1: The object was created while Dynamo
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# was introspecting a function
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# (and no HigherOrderOps were involved)
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# scope >= 2: The object was created through
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# Dynamo introspection of a HigherOrderOp.
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# The exact number corresponds to the level
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# of nested HigherOrderOps.
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if typ is MutableLocalSource.Existing:
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self.scope = 0
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elif typ is MutableLocalSource.Local:
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self.scope = current_scope_id()
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else:
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unimplemented(f"Unsupported MutableLocalSource: {typ}")
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class MutableLocal(MutableLocalBase):
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"""
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Marker used to indicate this (list, iter, etc) was constructed in
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local scope and can be mutated safely in analysis without leaking
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state.
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"""
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def __init__(self):
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super().__init__(MutableLocalSource.Local)
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def __hash__(self):
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return id(self)
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def __eq__(self, other):
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return self is other
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def _is_top_level_scope(scope_id):
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return scope_id == 1
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def is_side_effect_safe(m: MutableLocalBase):
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scope_id = current_scope_id()
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# In the top-level scope (if no HigherOrderOperators are involved),
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# we are allowed to modify variables created in this scope as well
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# as existing variables.
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if _is_top_level_scope(scope_id):
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return True
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# Otherwise, only allow local mutation of variables created in the current scope
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return m.scope == scope_id
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class VariableTrackerMeta(type):
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def __call__(cls, *args, **kwargs):
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"""Call __post_init__"""
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obj = type.__call__(cls, *args, **kwargs)
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obj.__post_init__(*args, **kwargs)
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return obj
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def __instancecheck__(cls, instance) -> bool:
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"""Make isinstance work with LazyVariableTracker"""
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if type.__instancecheck__(
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variables.LazyVariableTracker, instance
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) and cls not in (
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VariableTracker,
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variables.LazyVariableTracker,
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):
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instance = instance.realize()
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return type.__instancecheck__(cls, instance)
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class VariableTracker(metaclass=VariableTrackerMeta):
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"""
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Base class for tracked locals and stack values
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VariableTracker instances are immutable and should be copied in
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order to change them.
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"""
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# fields to leave unmodified in apply()
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_nonvar_fields = {
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"value",
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"guards",
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"source",
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"mutable_local",
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"parents_tracker",
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"user_code_variable_name",
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}
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def clone(self, **kwargs):
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"""Shallow copy with some (optional) changes"""
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args = dict(self.__dict__)
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args.update(kwargs)
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return self.__class__(**args)
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@classmethod
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def copy(cls, value):
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"""Deeper (but not full) copy, leaving FX and user objects alone"""
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return cls.apply(identity, value)
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@classmethod
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def apply(
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cls,
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fn: Callable[["VariableTracker"], "VariableTracker"],
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value,
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cache=None,
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skip_fn=lambda _: False, # Whether we should skip applying to this var
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):
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"""
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Walk this object and call fn on all the VariableTracker
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instances
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"""
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if cache is None:
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cache = dict()
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idx = id(value)
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if idx in cache:
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return cache[idx][0]
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if isinstance(value, VariableTracker):
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if not skip_fn(value):
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def update_object_dict(v):
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changed = False
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rv = v.__dict__
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for key in rv.keys():
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if key not in v._nonvar_fields:
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prior = rv[key]
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rv[key] = cls.apply(fn, prior, cache, skip_fn)
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changed = changed or prior is not rv[key]
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return v
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value = value.unwrap()
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was_realized = value.is_realized()
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result = fn(update_object_dict(value))
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if not was_realized and value.is_realized():
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# running fn() resulted in value getting realized,
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# which means we missed updating the contents of result
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result = update_object_dict(result.unwrap())
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else:
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result = fn(value)
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if result is not None:
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result = result.unwrap()
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elif istype(value, list):
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result = [cls.apply(fn, v, cache, skip_fn) for v in value]
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elif istype(value, tuple):
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result = tuple(cls.apply(fn, v, cache, skip_fn) for v in value)
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elif istype(value, (dict, collections.OrderedDict)):
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result = {
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k: cls.apply(fn, v, cache, skip_fn) for k, v in list(value.items())
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}
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else:
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result = value
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# save `value` to keep it alive and ensure id() isn't reused
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cache[idx] = (result, value)
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return result
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def __repr__(self):
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return f"{self.__class__.__name__}()"
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def python_type(self):
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"""
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Abstract method to be implemented by subclasses of VariableTracker.
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This method should return the type represented by the instance of the subclass.
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The purpose is to provide a standardized way to retrieve the Python type information
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of the variable being tracked.
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Returns:
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type: The Python type (such as int, str, list, etc.) of the variable tracked by
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the subclass. If the type cannot be determined or is not relevant,
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leaving it undefined or invoking super() is always sound.
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Note:
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This is an abstract method and may be overridden in subclasses.
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Example:
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class SetVariable(VariableTracker):
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def python_type(self):
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return set
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Raises:
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NotImplementedError: If the method is not implemented in a subclass.
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"""
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raise NotImplementedError(f"{self} has no type")
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def as_python_constant(self):
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"""For constants"""
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raise NotImplementedError(f"{self} is not a constant")
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def guard_as_python_constant(self):
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"""Similar to as_python_constant(), but add ID_MATCH guards to try to force things to become constants"""
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try:
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return self.as_python_constant()
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except NotImplementedError as e:
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unimplemented(str(e))
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def is_python_constant(self):
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try:
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self.as_python_constant()
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return True
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except NotImplementedError:
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return False
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def make_guard(self, fn):
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if self.source:
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return self.source.make_guard(fn)
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raise NotImplementedError()
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def const_getattr(self, tx, name: str) -> Any:
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"""getattr(self, name) returning a python constant"""
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raise NotImplementedError()
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def var_getattr(self, tx, name: str) -> "VariableTracker":
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"""getattr(self, name) returning a new variable"""
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value = self.const_getattr(tx, name)
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if not variables.ConstantVariable.is_literal(value):
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raise NotImplementedError()
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source = None
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if self.source:
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source = AttrSource(self.source, name)
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return variables.ConstantVariable.create(value, source=source)
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def is_proxy(self):
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try:
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self.as_proxy()
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return True
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except NotImplementedError:
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return False
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def as_proxy(self):
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raise NotImplementedError(str(self))
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def maybe_fx_node(self):
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try:
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proxy = self.as_proxy()
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import torch.fx
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if isinstance(proxy, torch.fx.Proxy):
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return proxy.node
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return None
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except NotImplementedError:
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return None
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def reconstruct(self, codegen):
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raise NotImplementedError()
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def can_reconstruct(self, tx):
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"""If it is possible to reconstruct the Python object this
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VariableTracker represents."""
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assert tx is tx.output.root_tx, "Only root tx can reconstruct"
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try:
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from ..codegen import PyCodegen
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cg = PyCodegen(tx)
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self.reconstruct(cg)
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return True
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except NotImplementedError:
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return False
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def unpack_var_sequence(self, tx) -> List["VariableTracker"]:
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raise NotImplementedError()
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def has_unpack_var_sequence(self, tx) -> bool:
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try:
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self.unpack_var_sequence(tx)
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return True
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except NotImplementedError:
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return False
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def inspect_parameter_names(self) -> List[str]:
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unimplemented(f"inspect_parameter_names: {self}")
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def call_hasattr(self, tx, name: str) -> "VariableTracker":
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unimplemented(f"hasattr {self.__class__.__name__} {name}")
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def call_function(
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self, tx, args: "List[VariableTracker]", kwargs: "Dict[str, VariableTracker]"
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) -> "VariableTracker":
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unimplemented(f"call_function {self} {args} {kwargs}")
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def call_method(
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self,
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tx,
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name,
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args: "List[VariableTracker]",
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kwargs: "Dict[str, VariableTracker]",
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) -> "VariableTracker":
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if name == "__len__" and self.has_unpack_var_sequence(tx):
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assert not (args or kwargs)
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return variables.ConstantVariable.create(len(self.unpack_var_sequence(tx)))
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elif (
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name == "__getattr__"
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and len(args) == 1
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and args[0].is_python_constant()
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and not kwargs
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):
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return self.var_getattr(tx, args[0].as_python_constant())
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raise unimplemented(f"call_method {self} {name} {args} {kwargs}")
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def rename(self, tx, name):
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return self
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def realize(self) -> "VariableTracker":
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"""Used by LazyVariableTracker to build the real VariableTracker"""
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return self
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def recursive_realize(self):
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"""Realize all objects under this"""
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return VariableTracker.apply(lambda x: x.realize(), self)
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def unwrap(self) -> "VariableTracker":
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"""Used by LazyVariableTracker to return the real VariableTracker if it already exists"""
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return self
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def is_realized(self):
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"""Used by LazyVariableTracker to indicate an unrealized node"""
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return True
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def __init__(
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self,
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*,
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source: Source = None,
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mutable_local: MutableLocal = None,
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parents_tracker: ParentsTracker = None,
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):
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super().__init__()
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self.source = source
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self.mutable_local = mutable_local
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self.parents_tracker = parents_tracker
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def __post_init__(self, *args, **kwargs):
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if self.parents_tracker is None:
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self.parents_tracker = ParentsTracker()
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# visit children 1 level deep and ensure parent is set properly
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VariableTracker.apply(
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lambda node: node.parents_tracker.add(self.parents_tracker),
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[v for k, v in self.__dict__.items() if k not in self._nonvar_fields],
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skip_fn=lambda _: True,
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)
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def typestr(*objs):
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if len(objs) == 1:
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(obj,) = objs
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if isinstance(obj, VariableTracker):
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return str(obj)
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else:
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return type(obj).__name__
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else:
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return " ".join(map(typestr, objs))
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